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Wu B, Wu T, Huang Z, Ji S. Advancing Flexible Sensors through On-Demand Regulation of Supramolecular Nanostructures. ACS NANO 2024; 18:22664-22674. [PMID: 39152049 DOI: 10.1021/acsnano.4c08310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/19/2024]
Abstract
The evolution of flexible sensors heavily relies on advances in soft-material design and sensing mechanisms. Supramolecular chemistry offers a powerful toolbox for manipulating nanoscale and molecular structures within soft materials, thus fostering recent advancements in flexible sensors and electronics. Supramolecular interactions have been utilized to nanoengineer functional sensing materials or construct chemical sensors with lower cost and broader targets. In this perspective, we will highlight the use of supramolecular interactions to regulate and optimize nanostructures within functional soft materials and illustrate their importance in expanding the nanocavities of bioreceptors for chemical sensing. Overall, a bridge between tissue-mimicking flexible sensors and cell-mimetic supramolecular chemistry has been built, which will further advance human healthcare innovation.
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Affiliation(s)
- Bohang Wu
- Institute of Functional Nano & Soft Materials (FUNSOM), College of Nano Science and Technology (CNST), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou 215123, P.R. China
- School of Materials Science and Engineering, Peking University, Beijing 100871, P.R. China
| | - Tong Wu
- School of Materials Science and Engineering, Peking University, Beijing 100871, P.R. China
| | - Zehuan Huang
- School of Materials Science and Engineering, Peking University, Beijing 100871, P.R. China
| | - Shaobo Ji
- Institute of Functional Nano & Soft Materials (FUNSOM), College of Nano Science and Technology (CNST), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou 215123, P.R. China
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2
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Li D, Cui T, Xu Z, Xu S, Dong Z, Tao L, Liu H, Yang Y, Ren TL. Designs and Applications for the Multimodal Flexible Hybrid Epidermal Electronic Systems. RESEARCH (WASHINGTON, D.C.) 2024; 7:0424. [PMID: 39130493 PMCID: PMC11310101 DOI: 10.34133/research.0424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Accepted: 06/17/2024] [Indexed: 08/13/2024]
Abstract
Research on the flexible hybrid epidermal electronic system (FHEES) has attracted considerable attention due to its potential applications in human-machine interaction and healthcare. Through material and structural innovations, FHEES combines the advantages of traditional stiff electronic devices and flexible electronic technology, enabling it to be worn conformally on the skin while retaining complex system functionality. FHEESs use multimodal sensing to enhance the identification accuracy of the wearer's motion modes, intentions, or health status, thus realizing more comprehensive physiological signal acquisition. However, the heterogeneous integration of soft and stiff components makes balancing comfort and performance in designing and implementing multimodal FHEESs challenging. Herein, multimodal FHEESs are first introduced in 2 types based on their different system structure: all-in-one and assembled, reflecting totally different heterogeneous integration strategies. Characteristics and the key design issues (such as interconnect design, interface strategy, substrate selection, etc.) of the 2 multimodal FHEESs are emphasized. Besides, the applications and advantages of the 2 multimodal FHEESs in recent research have been presented, with a focus on the control and medical fields. Finally, the prospects and challenges of the multimodal FHEES are discussed.
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Affiliation(s)
- Ding Li
- School of Integrated Circuit,
Tsinghua University, Beijing, China
| | - Tianrui Cui
- School of Integrated Circuit,
Tsinghua University, Beijing, China
| | - Zigan Xu
- School of Integrated Circuit,
Tsinghua University, Beijing, China
| | - Shuoyan Xu
- School of Integrated Circuit,
Tsinghua University, Beijing, China
| | - Zirui Dong
- School of Integrated Circuit,
Tsinghua University, Beijing, China
| | - Luqi Tao
- Beijing National Research Center for Information Science and Technology (BNRist),
Tsinghua University, Beijing, China
| | - Houfang Liu
- Beijing National Research Center for Information Science and Technology (BNRist),
Tsinghua University, Beijing, China
| | - Yi Yang
- School of Integrated Circuit,
Tsinghua University, Beijing, China
- Beijing National Research Center for Information Science and Technology (BNRist),
Tsinghua University, Beijing, China
| | - Tian-Ling Ren
- School of Integrated Circuit,
Tsinghua University, Beijing, China
- Beijing National Research Center for Information Science and Technology (BNRist),
Tsinghua University, Beijing, China
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3
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Koo JH, Lee YJ, Kim HJ, Matusik W, Kim DH, Jeong H. Electronic Skin: Opportunities and Challenges in Convergence with Machine Learning. Annu Rev Biomed Eng 2024; 26:331-355. [PMID: 38959390 DOI: 10.1146/annurev-bioeng-103122-032652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
Recent advancements in soft electronic skin (e-skin) have led to the development of human-like devices that reproduce the skin's functions and physical attributes. These devices are being explored for applications in robotic prostheses as well as for collecting biopotentials for disease diagnosis and treatment, as exemplified by biomedical e-skins. More recently, machine learning (ML) has been utilized to enhance device control accuracy and data processing efficiency. The convergence of e-skin technologies with ML is promoting their translation into clinical practice, especially in healthcare. This review highlights the latest developments in ML-reinforced e-skin devices for robotic prostheses and biomedical instrumentations. We first describe technological breakthroughs in state-of-the-art e-skin devices, emphasizing technologies that achieve skin-like properties. We then introduce ML methods adopted for control optimization and pattern recognition, followed by practical applications that converge the two technologies. Lastly, we briefly discuss the challenges this interdisciplinary research encounters in its clinical and industrial transition.
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Affiliation(s)
- Ja Hoon Koo
- Department of Semiconductor Systems Engineering and Institute of Semiconductor and System IC, Sejong University, Seoul, Republic of Korea
| | - Young Joong Lee
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Hye Jin Kim
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul, Republic of Korea
| | - Wojciech Matusik
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Dae-Hyeong Kim
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul, Republic of Korea
- Department of Materials Science and Engineering, Seoul National University, Seoul, Republic of Korea
- Interdisciplinary Program for Bioengineering, Seoul National University, Seoul, Republic of Korea;
| | - Hyoyoung Jeong
- Department of Electrical and Computer Engineering, University of California, Davis, California, USA;
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4
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Du Y, Kim JH, Kong H, Li AA, Jin ML, Kim DH, Wang Y. Biocompatible Electronic Skins for Cardiovascular Health Monitoring. Adv Healthc Mater 2024; 13:e2303461. [PMID: 38569196 DOI: 10.1002/adhm.202303461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/27/2024] [Indexed: 04/05/2024]
Abstract
Cardiovascular diseases represent a significant threat to the overall well-being of the global population. Continuous monitoring of vital signs related to cardiovascular health is essential for improving daily health management. Currently, there has been remarkable proliferation of technology focused on collecting data related to cardiovascular diseases through daily electronic skin monitoring. However, concerns have arisen regarding potential skin irritation and inflammation due to the necessity for prolonged wear of wearable devices. To ensure comfortable and uninterrupted cardiovascular health monitoring, the concept of biocompatible electronic skin has gained substantial attention. In this review, biocompatible electronic skins for cardiovascular health monitoring are comprehensively summarized and discussed. The recent achievements of biocompatible electronic skin in cardiovascular health monitoring are introduced. Their working principles, fabrication processes, and performances in sensing technologies, materials, and integration systems are highlighted, and comparisons are made with other electronic skins used for cardiovascular monitoring. In addition, the significance of integrating sensing systems and the updating wireless communication for the development of the smart medical field is explored. Finally, the opportunities and challenges for wearable electronic skin are also examined.
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Affiliation(s)
- Yucong Du
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, 266071, China
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Ji Hong Kim
- Department of Chemical Engineering, Hanyang University, Seoul, 04763, Republic of Korea
- Institute of Nano Science and Technology, Hanyang University, Seoul, 04763, Republic of Korea
- Clean-Energy Research Institute, Hanyang University, Seoul, 04763, Republic of Korea
| | - Hui Kong
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Anne Ailina Li
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Ming Liang Jin
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Do Hwan Kim
- Department of Chemical Engineering, Hanyang University, Seoul, 04763, Republic of Korea
- Institute of Nano Science and Technology, Hanyang University, Seoul, 04763, Republic of Korea
- Clean-Energy Research Institute, Hanyang University, Seoul, 04763, Republic of Korea
| | - Yin Wang
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, 266071, China
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5
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Zhou L, Guess M, Kim KR, Yeo WH. Skin-interfacing wearable biosensors for smart health monitoring of infants and neonates. COMMUNICATIONS MATERIALS 2024; 5:72. [PMID: 38737724 PMCID: PMC11081930 DOI: 10.1038/s43246-024-00511-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 04/23/2024] [Indexed: 05/14/2024]
Abstract
Health monitoring of infant patients in intensive care can be especially strenuous for both the patient and their caregiver, as testing setups involve a tangle of electrodes, probes, and catheters that keep the patient bedridden. This has typically involved expensive and imposing machines, to track physiological metrics such as heart rate, respiration rate, temperature, blood oxygen saturation, blood pressure, and ion concentrations. However, in the past couple of decades, research advancements have propelled a world of soft, wearable, and non-invasive systems to supersede current practices. This paper summarizes the latest advancements in neonatal wearable systems and the different approaches to each branch of physiological monitoring, with an emphasis on smart skin-interfaced wearables. Weaknesses and shortfalls are also addressed, with some guidelines provided to help drive the further research needed.
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Affiliation(s)
- Lauren Zhou
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA
- IEN Center for Wearable Intelligent Systems and Healthcare, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332 USA
| | - Matthew Guess
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA
- IEN Center for Wearable Intelligent Systems and Healthcare, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332 USA
| | - Ka Ram Kim
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA
- IEN Center for Wearable Intelligent Systems and Healthcare, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332 USA
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA
- IEN Center for Wearable Intelligent Systems and Healthcare, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332 USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, GA 30332 USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332 USA
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Araki T, Li K, Suzuki D, Abe T, Kawabata R, Uemura T, Izumi S, Tsuruta S, Terasaki N, Kawano Y, Sekitani T. Broadband Photodetectors and Imagers in Stretchable Electronics Packaging. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2304048. [PMID: 37403808 DOI: 10.1002/adma.202304048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 06/22/2023] [Accepted: 07/03/2023] [Indexed: 07/06/2023]
Abstract
The integration of flexible electronics with optics can help realize a powerful tool that facilitates the creation of a smart society wherein internal evaluations can be easily performed nondestructively from the surface of various objects that is used or encountered in daily lives. Here, organic-material-based stretchable optical sensors and imagers that possess both bending capability and rubber-like elasticity are reviewed. The latest trends in nondestructive evaluation equipment that enable simple on-site evaluations of health conditions and abnormalities are discussed without subjecting the targeted living bodies and various objects to mechanical stress. Real-time performance under real-life conditions is becoming increasingly important for creating smart societies interwoven with optical technologies. In particular, the terahertz (THz)-wave region offers a substance- and state-specific fingerprint spectrum that enables instantaneous analyses. However, to make THz sensors accessible, the following issues must be addressed: broadband and high-sensitivity at room temperature, stretchability to follow the surface movements of targets, and digital transformation compatibility. The materials, electronics packaging, and remote imaging systems used to overcome these issues are discussed in detail. Ultimately, stretchable optical sensors and imagers with highly sensitive and broadband THz sensors can facilitate the multifaceted on-site evaluation of solids, liquids, and gases.
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Affiliation(s)
- Teppei Araki
- SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 8-1 Mihogaoka, Ibaraki-shi, 567-0047, Osaka, Japan
- Advanced Photonics and Biosensing Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology (AIST), 2-1 Yamada-Oka, Suita, 565-0871, Osaka, Japan
- Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, 565-0871, Osaka, Japan
| | - Kou Li
- Department of Electrical, Electronic, and Communication Engineering, Faculty of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, 112-8551, Tokyo, Japan
| | - Daichi Suzuki
- Sensing System Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 807-1, Shuku-machi, Tosu, 841-0052, Saga, Japan
| | - Takaaki Abe
- SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 8-1 Mihogaoka, Ibaraki-shi, 567-0047, Osaka, Japan
| | - Rei Kawabata
- SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 8-1 Mihogaoka, Ibaraki-shi, 567-0047, Osaka, Japan
- Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, 565-0871, Osaka, Japan
| | - Takafumi Uemura
- SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 8-1 Mihogaoka, Ibaraki-shi, 567-0047, Osaka, Japan
- Advanced Photonics and Biosensing Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology (AIST), 2-1 Yamada-Oka, Suita, 565-0871, Osaka, Japan
| | - Shintaro Izumi
- SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 8-1 Mihogaoka, Ibaraki-shi, 567-0047, Osaka, Japan
- Graduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai-cho, Nada-ku, 657-8501, Kobe, Japan
| | - Shuichi Tsuruta
- SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 8-1 Mihogaoka, Ibaraki-shi, 567-0047, Osaka, Japan
| | - Nao Terasaki
- Sensing System Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 807-1, Shuku-machi, Tosu, 841-0052, Saga, Japan
| | - Yukio Kawano
- Department of Electrical, Electronic, and Communication Engineering, Faculty of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, 112-8551, Tokyo, Japan
- National Institute of Informatics, Tokyo, 101-8430, Japan
| | - Tsuyoshi Sekitani
- SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 8-1 Mihogaoka, Ibaraki-shi, 567-0047, Osaka, Japan
- Advanced Photonics and Biosensing Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology (AIST), 2-1 Yamada-Oka, Suita, 565-0871, Osaka, Japan
- Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, 565-0871, Osaka, Japan
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7
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Zhao Z, Yang C, Li D. Skin Electrodes Based on TPU Fiber Scaffolds with Conductive Nanocomposites with Stretchability, Breathability, and Washability. MICROMACHINES 2024; 15:598. [PMID: 38793171 PMCID: PMC11122800 DOI: 10.3390/mi15050598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/25/2024] [Accepted: 04/26/2024] [Indexed: 05/26/2024]
Abstract
In the context of an aging population and escalating work pressures, cardiovascular diseases pose increasing health risks. Electrocardiogram (ECG) monitoring presents a preventive tool, but conventional devices often compromise comfort. This study proposes an approach using Ag NW/TPU composites for flexible and breathable epidermal electronics. In this new structure, TPU fibers are used to support Ag NWs/TPU nanocomposites. The TPU fiber-reinforced Ag NW/TPU (TFRAT) nanocomposites exhibit excellent conductivity, stretchability, and electromechanical durability. The composite ensures high steam permeability, maintaining stable electrical performance after washing cycles. Employing this technology, a flexible ECG detection system is developed, augmented with a convolutional neural network (CNN) for automated signal analysis. The experimental results demonstrate the system's reliability in capturing physiological signals. Additionally, a CNN model trained on ECG data achieves over 99% accuracy in diagnosing arrhythmias. This study presents TFRAT as a promising solution for wearable electronics, offering both comfort and functionality in long-term epidermal applications, with implications for healthcare and beyond.
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Affiliation(s)
| | - Chaopeng Yang
- School of Chemical Engineering and Technology, Hebei University of Technology, No. 5340, Xiping Road, Tianjin 300130, China;
| | - Dongchan Li
- School of Chemical Engineering and Technology, Hebei University of Technology, No. 5340, Xiping Road, Tianjin 300130, China;
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8
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Babangida AA, Uddin A, Stephen KT, Yusuf BA, Zhang L, Ge D. A Roadmap from Functional Materials to Plant Health Monitoring (PHM). Macromol Biosci 2024; 24:e2300283. [PMID: 37815087 DOI: 10.1002/mabi.202300283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 10/05/2023] [Indexed: 10/11/2023]
Abstract
Soft bioelectronics have great potential for the early diagnosis of plant diseases and the mitigation of adverse outcomes such as reduced crop yields and stunted growth. Over the past decade, bioelectronic interfaces have evolved into miniaturized conformal electronic devices that integrate flexible monitoring systems with advanced electronic functionality. This development is largely attributable to advances in materials science, and micro/nanofabrication technology. The approach uses the mechanical and electronic properties of functional materials (polymer substrates and sensing elements) to create interfaces for plant monitoring. In addition to ensuring biocompatibility, several other factors need to be considered when developing these interfaces. These include the choice of materials, fabrication techniques, precision, electrical performance, and mechanical stability. In this review, some of the benefits plants can derive from several of the materials used to develop soft bioelectronic interfaces are discussed. The article describes how they can be used to create biocompatible monitoring devices that can enhance plant growth and health. Evaluation of these devices also takes into account features that ensure their long-term durability, sensitivity, and reliability. This article concludes with a discussion of the development of reliable soft bioelectronic systems for plants, which has the potential to advance the field of bioelectronics.
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Affiliation(s)
- Abubakar A Babangida
- Institute of Intelligent Flexible Mechatronics, School of Mechanical Engineering, Jiangsu University, Zhenjiang, 212013, P. R. China
| | - Azim Uddin
- Institute for Composites Science Innovation (InCSI), School of Materials Science and Engineering, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, P. R. China
| | - Kukwi Tissan Stephen
- School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, 710072, P. R. China
| | - Bashir Adegbemiga Yusuf
- Institute of Intelligent Flexible Mechatronics, School of Mechanical Engineering, Jiangsu University, Zhenjiang, 212013, P. R. China
| | - Liqiang Zhang
- Institute of Intelligent Flexible Mechatronics, School of Mechanical Engineering, Jiangsu University, Zhenjiang, 212013, P. R. China
- Center of Energy Storage Materials & Technology, College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, National Laboratory of Solid-State Microstructures, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu, 210093, China
- Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi, Jiangsu, 214126, China
| | - Daohan Ge
- Institute of Intelligent Flexible Mechatronics, School of Mechanical Engineering, Jiangsu University, Zhenjiang, 212013, P. R. China
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9
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Kim SH, Jeanne E, Shalish W, Yoo J, Rogers JA. Wireless wearable devices for continuous monitoring of body sounds and motions. Clin Transl Med 2024; 14:e1593. [PMID: 38362612 PMCID: PMC10870079 DOI: 10.1002/ctm2.1593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 02/05/2024] [Indexed: 02/17/2024] Open
Affiliation(s)
- Sun Hong Kim
- Querrey Simpson Institute for BioelectronicsNorthwestern UniversityEvanstonIllinoisUSA
| | - Emily Jeanne
- Neonatal DivisionDepartment of PediatricsMcGill University Health CenterMontrealQuebecCanada
| | - Wissam Shalish
- Neonatal DivisionDepartment of PediatricsMcGill University Health CenterMontrealQuebecCanada
| | - Jae‐Young Yoo
- Department of Semiconductor Convergence EngineeringSungkyunkwan UniversitySuwonRepublic of Korea
| | - John A. Rogers
- Querrey Simpson Institute for BioelectronicsNorthwestern UniversityEvanstonIllinoisUSA
- Department of Biomedical EngineeringNorthwestern UniversityEvanstonIllinoisUSA
- Department of Materials Science and EngineeringNorthwestern UniversityEvanstonIllinoisUSA
- Department of Neurological SurgeryNorthwestern UniversityChicagoIllinoisUSA
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10
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Ban S, Lee CW, Sakthivelpathi V, Chung JH, Kim JH. Continuous Biopotential Monitoring via Carbon Nanotubes Paper Composites (CPC) for Sustainable Health Analysis. SENSORS (BASEL, SWITZERLAND) 2023; 23:9727. [PMID: 38139573 PMCID: PMC10748204 DOI: 10.3390/s23249727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 12/06/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023]
Abstract
Skin-based wearable devices have gained significant attention due to advancements in soft materials and thin-film technologies. Nevertheless, traditional wearable electronics often entail expensive and intricate manufacturing processes and rely on metal-based substrates that are susceptible to corrosion and lack flexibility. In response to these challenges, this paper has emerged with an alternative substrate for wearable electrodes due to its cost-effectiveness and scalability in manufacturing. Paper-based electrodes offer an attractive solution with their inherent properties of high breathability, flexibility, biocompatibility, and tunability. In this study, we introduce carbon nanotube-based paper composites (CPC) electrodes designed for the continuous detection of biopotential signals, such as electrooculography (EOG), electrocardiogram (ECG), and electroencephalogram (EEG). To prevent direct skin contact with carbon nanotubes, we apply various packaging materials, including polydimethylsiloxane (PDMS), Eco-flex, polyimide (PI), and polyurethane (PU). We conduct a comparative analysis of their signal-to-noise ratios in comparison to conventional gel electrodes. Our system demonstrates real-time biopotential monitoring for continuous health tracking, utilizing CPC in conjunction with a portable data acquisition system. The collected data are analyzed to provide accurate heart rates, respiratory rates, and heart rate variability metrics. Additionally, we explore the feasibility using CPC for sleep monitoring by collecting EEG signals.
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Affiliation(s)
- Seunghyeb Ban
- School of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA;
| | - Chang Woo Lee
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA; (C.W.L.); (J.-H.C.)
| | - Vigneshwar Sakthivelpathi
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA; (C.W.L.); (J.-H.C.)
| | - Jae-Hyun Chung
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA; (C.W.L.); (J.-H.C.)
| | - Jong-Hoon Kim
- School of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA;
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA; (C.W.L.); (J.-H.C.)
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11
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Zhang K, Li W, Li H, Luo Y, Li Z, Wang X, Chen X. A Leaf-Patchable Reflectance Meter for In Situ Continuous Monitoring of Chlorophyll Content. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2305552. [PMID: 37797172 PMCID: PMC10724420 DOI: 10.1002/advs.202305552] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Indexed: 10/07/2023]
Abstract
Plant wearable sensors facilitate the real-time monitoring of plant physiological status. In situ monitoring of the plant chlorophyll content over days can provide valuable information on the photosynthetic capacity, nitrogen content, and general plant health. However, it cannot be achieved by current chlorophyll measuring methods. Here, a miniaturized and plant-wearable chlorophyll meter for rapid, non-destructive, in situ, and long-term chlorophyll monitoring is developed. The reflectance-based chlorophyll sensor with 1.5 mm thickness and 0.2 g weight (1000 times lighter than the commercial chlorophyll meter), includes a light emitting diode (LED) and two symmetric photodetectors (PDs) on a flexible substrate, and is patched onto the leaf upper epidermis with a conformal light guiding layer. A chlorophyll content index (CCI) calculated based on the sensor shows a better linear relationship with the leaf chlorophyll content (r2 > 0.9) than the traditional chlorophyll meter. This meter can wirelessly communicate with a smartphone to monitor the leaf chlorophyll change under various stresses and indicate the unhealthy status of plants for long-term application of plants under various stresses earlier than chlorophyll meter and naked-eye observation. This wearable chlorophyll sensing patch is promising in smart and precision agriculture.
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Affiliation(s)
- Kaiyi Zhang
- Innovative Center for Flexible Devices (iFLEX)School of Materials Science and EngineeringNanyang Technological University50 Nanyang AvenueSingapore639798Republic of Singapore
| | - Wenlong Li
- Institute of Materials Research and Engineering (IMRE)Agency for Science, Technology and Research (A*STAR)2 Fusionopolis Way, Innovis #08‐03Singapore138634Republic of Singapore
| | - Haicheng Li
- Innovative Center for Flexible Devices (iFLEX)School of Materials Science and EngineeringNanyang Technological University50 Nanyang AvenueSingapore639798Republic of Singapore
| | - Yifei Luo
- Institute of Materials Research and Engineering (IMRE)Agency for Science, Technology and Research (A*STAR)2 Fusionopolis Way, Innovis #08‐03Singapore138634Republic of Singapore
| | - Zheng Li
- Innovative Center for Flexible Devices (iFLEX)School of Materials Science and EngineeringNanyang Technological University50 Nanyang AvenueSingapore639798Republic of Singapore
| | - Xiaoshi Wang
- Innovative Center for Flexible Devices (iFLEX)School of Materials Science and EngineeringNanyang Technological University50 Nanyang AvenueSingapore639798Republic of Singapore
| | - Xiaodong Chen
- Innovative Center for Flexible Devices (iFLEX)School of Materials Science and EngineeringNanyang Technological University50 Nanyang AvenueSingapore639798Republic of Singapore
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12
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Sun T, Feng B, Huo J, Xiao Y, Wang W, Peng J, Li Z, Du C, Wang W, Zou G, Liu L. Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses. NANO-MICRO LETTERS 2023; 16:14. [PMID: 37955844 PMCID: PMC10643743 DOI: 10.1007/s40820-023-01235-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 09/24/2023] [Indexed: 11/14/2023]
Abstract
The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.
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Affiliation(s)
- Tianming Sun
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
- College of Materials Science and Engineering, Shanxi Province, Taiyuan University of Technology, Taiyuan, 030024, People's Republic of China
| | - Bin Feng
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Jinpeng Huo
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Yu Xiao
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Wengan Wang
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Jin Peng
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Zehua Li
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Chengjie Du
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Wenxian Wang
- College of Materials Science and Engineering, Shanxi Province, Taiyuan University of Technology, Taiyuan, 030024, People's Republic of China.
| | - Guisheng Zou
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China.
| | - Lei Liu
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China.
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13
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Gagnon-Turcotte G, Cote-Allard U, Mascret Q, Torresen J, Gosselin B. Photoplethysmography-based derivation of physiological information using the BioPoint. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38083646 DOI: 10.1109/embc40787.2023.10340642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The BioPoint is a new wireless and wearable device, targeting both the ambulatory and on-site monitoring of biosignals. It is described as being capable of streaming and recording the i) electromyography, ii) electrocardiography, iii) electrodermal activity, iv) photoplethysmography, v) skin temperature and vi) actigraphy simultaneously, while making the raw signals recorded by the sensors readily available. However, an in-depth assessment of the biophysical signals recorded by this device, as well as its ability to derive vital signs and other health metrics, remains to be carried out. Consequently, this work proposes a preliminary study to evaluate the quality of the signals that can be acquired by this wearable with a focus on the derivation of heart rate and peripheral blood oxygenation via photoplethysmography. The device is quantitatively compared to the medical-grade pulse oximeter NoninConnect 3245, by Nonin inc. This study was performed with participants wearing the BioPoint at different positions on the body (finger, wrist, forearm, biceps and plantar arch), while the NoninConnect was worn on the fingertip and used as the ground truth. The results show that the BioPoint can accurately determine both heart rate and oxygen saturation from various locations on the body. However, as the BioPoint's photoplethysmograph is not calibrated it cannot be used for medical purposes (non-medical-grade).
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14
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Kwon S, Kim HS, Kwon K, Kim H, Kim YS, Lee SH, Kwon YT, Jeong JW, Trotti LM, Duarte A, Yeo WH. At-home wireless sleep monitoring patches for the clinical assessment of sleep quality and sleep apnea. SCIENCE ADVANCES 2023; 9:eadg9671. [PMID: 37224243 DOI: 10.1126/sciadv.adg9671] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/17/2023] [Indexed: 05/26/2023]
Abstract
Although many people suffer from sleep disorders, most are undiagnosed, leading to impairments in health. The existing polysomnography method is not easily accessible; it's costly, burdensome to patients, and requires specialized facilities and personnel. Here, we report an at-home portable system that includes wireless sleep sensors and wearable electronics with embedded machine learning. We also show its application for assessing sleep quality and detecting sleep apnea with multiple patients. Unlike the conventional system using numerous bulky sensors, the soft, all-integrated wearable platform offers natural sleep wherever the user prefers. In a clinical study, the face-mounted patches that detect brain, eye, and muscle signals show comparable performance with polysomnography. When comparing healthy controls to sleep apnea patients, the wearable system can detect obstructive sleep apnea with an accuracy of 88.5%. Furthermore, deep learning offers automated sleep scoring, demonstrating portability, and point-of-care usability. At-home wearable electronics could ensure a promising future supporting portable sleep monitoring and home healthcare.
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Affiliation(s)
- Shinjae Kwon
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Hyeon Seok Kim
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Kangkyu Kwon
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Hodam Kim
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Yun Soung Kim
- Department of Radiology, Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute, New York, NY 10029, USA
| | - Sung Hoon Lee
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Young-Tae Kwon
- Metal Powder Department, Korea Institute of Materials Science, Changwon 51508, Republic of Korea
| | - Jae-Woong Jeong
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
| | - Lynn Marie Trotti
- Emory Sleep Center and Department of Neurology, Emory University School of Medicine, Atlanta, GA 30329, USA
| | - Audrey Duarte
- Department of Psychology, University of Texas at Austin, Austin, TX 78712, USA
| | - Woon-Hong Yeo
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA 30332, USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Institute for Materials, Neural Engineering Center, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
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15
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Lee Y, Pokharel S, Muslim AA, KC DB, Lee KH, Yeo WH. Experimental Study: Deep Learning-Based Fall Monitoring among Older Adults with Skin-Wearable Electronics. SENSORS (BASEL, SWITZERLAND) 2023; 23:3983. [PMID: 37112326 PMCID: PMC10140987 DOI: 10.3390/s23083983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/10/2023] [Accepted: 04/11/2023] [Indexed: 06/19/2023]
Abstract
Older adults are more vulnerable to falling due to normal changes due to aging, and their falls are a serious medical risk with high healthcare and societal costs. However, there is a lack of automatic fall detection systems for older adults. This paper reports (1) a wireless, flexible, skin-wearable electronic device for both accurate motion sensing and user comfort, and (2) a deep learning-based classification algorithm for reliable fall detection of older adults. The cost-effective skin-wearable motion monitoring device is designed and fabricated using thin copper films. It includes a six-axis motion sensor and is directly laminated on the skin without adhesives for the collection of accurate motion data. To study accurate fall detection using the proposed device, different deep learning models, body locations for the device placement, and input datasets are investigated using motion data based on various human activities. Our results indicate the optimal location to place the device is the chest, achieving accuracy of more than 98% for falls with motion data from older adults. Moreover, our results suggest a large motion dataset directly collected from older adults is essential to improve the accuracy of fall detection for the older adult population.
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Affiliation(s)
- Yongkuk Lee
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA;
| | - Suresh Pokharel
- Department of Computer Science, Michigan Technological University, Houghton, MI 49931, USA; (S.P.)
| | - Asra Al Muslim
- Department of Biomedical Engineering, Wichita State University, Wichita, KS 67260, USA;
| | - Dukka B. KC
- Department of Computer Science, Michigan Technological University, Houghton, MI 49931, USA; (S.P.)
| | - Kyoung Hag Lee
- School of Social Work, Wichita State University, Wichita, KS 67260, USA;
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA;
- IEN Center for Human-Centric Interfaces and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
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16
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Kim H, Song J, Kim S, Lee S, Park Y, Lee S, Lee S, Kim J. Recent Advances in Multiplexed Wearable Sensor Platforms for Real-Time Monitoring Lifetime Stress: A Review. BIOSENSORS 2023; 13:bios13040470. [PMID: 37185545 PMCID: PMC10136450 DOI: 10.3390/bios13040470] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/06/2023] [Accepted: 04/09/2023] [Indexed: 05/17/2023]
Abstract
Researchers are interested in measuring mental stress because it is linked to a variety of diseases. Real-time stress monitoring via wearable sensor systems can aid in the prevention of stress-related diseases by allowing stressors to be controlled immediately. Physical tests, such as heart rate or skin conductance, have recently been used to assess stress; however, these methods are easily influenced by daily life activities. As a result, for more accurate stress monitoring, validations requiring two or more stress-related biomarkers are demanded. In this review, the combinations of various types of sensors (hereafter referred to as multiplexed sensor systems) that can be applied to monitor stress are discussed, referring to physical and chemical biomarkers. Multiplexed sensor systems are classified as multiplexed physical sensors, multiplexed physical-chemical sensors, and multiplexed chemical sensors, with the effect of measuring multiple biomarkers and the ability to measure stress being the most important. The working principles of multiplexed sensor systems are subdivided, with advantages in measuring multiple biomarkers. Furthermore, stress-related chemical biomarkers are still limited to cortisol; however, we believe that by developing multiplexed sensor systems, it will be possible to explore new stress-related chemical biomarkers by confirming their correlations to cortisol. As a result, the potential for further development of multiplexed sensor systems, such as the development of wearable electronics for mental health management, is highlighted in this review.
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Affiliation(s)
- Heena Kim
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
| | - Jaeyoon Song
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
| | - Sehyeon Kim
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
| | - Suyoung Lee
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
| | - Yejin Park
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
| | - Seungjun Lee
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
| | - Seunghee Lee
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
| | - Jinsik Kim
- Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea
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17
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Qiao Y, Luo J, Cui T, Liu H, Tang H, Zeng Y, Liu C, Li Y, Jian J, Wu J, Tian H, Yang Y, Ren TL, Zhou J. Soft Electronics for Health Monitoring Assisted by Machine Learning. NANO-MICRO LETTERS 2023; 15:66. [PMID: 36918452 PMCID: PMC10014415 DOI: 10.1007/s40820-023-01029-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/05/2023] [Indexed: 06/18/2023]
Abstract
Due to the development of the novel materials, the past two decades have witnessed the rapid advances of soft electronics. The soft electronics have huge potential in the physical sign monitoring and health care. One of the important advantages of soft electronics is forming good interface with skin, which can increase the user scale and improve the signal quality. Therefore, it is easy to build the specific dataset, which is important to improve the performance of machine learning algorithm. At the same time, with the assistance of machine learning algorithm, the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis. The soft electronics and machining learning algorithms complement each other very well. It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future. Therefore, in this review, we will give a careful introduction about the new soft material, physiological signal detected by soft devices, and the soft devices assisted by machine learning algorithm. Some soft materials will be discussed such as two-dimensional material, carbon nanotube, nanowire, nanomesh, and hydrogel. Then, soft sensors will be discussed according to the physiological signal types (pulse, respiration, human motion, intraocular pressure, phonation, etc.). After that, the soft electronics assisted by various algorithms will be reviewed, including some classical algorithms and powerful neural network algorithms. Especially, the soft device assisted by neural network will be introduced carefully. Finally, the outlook, challenge, and conclusion of soft system powered by machine learning algorithm will be discussed.
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Affiliation(s)
- Yancong Qiao
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China.
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China.
| | - Jinan Luo
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Tianrui Cui
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Haidong Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Hao Tang
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Yingfen Zeng
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Chang Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Yuanfang Li
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Jinming Jian
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Jingzhi Wu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - He Tian
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Yi Yang
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Tian-Ling Ren
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China.
| | - Jianhua Zhou
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, People's Republic of China.
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China.
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18
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Ban S, Lee YJ, Kwon S, Kim YS, Chang JW, Kim JH, Yeo WH. Soft Wireless Headband Bioelectronics and Electrooculography for Persistent Human-Machine Interfaces. ACS APPLIED ELECTRONIC MATERIALS 2023; 5:877-886. [PMID: 36873262 PMCID: PMC9979786 DOI: 10.1021/acsaelm.2c01436] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/29/2023] [Indexed: 06/18/2023]
Abstract
Recent advances in wearable technologies have enabled ways for people to interact with external devices, known as human-machine interfaces (HMIs). Among them, electrooculography (EOG), measured by wearable devices, is used for eye movement-enabled HMI. Most prior studies have utilized conventional gel electrodes for EOG recording. However, the gel is problematic due to skin irritation, while separate bulky electronics cause motion artifacts. Here, we introduce a low-profile, headband-type, soft wearable electronic system with embedded stretchable electrodes, and a flexible wireless circuit to detect EOG signals for persistent HMIs. The headband with dry electrodes is printed with flexible thermoplastic polyurethane. Nanomembrane electrodes are prepared by thin-film deposition and laser cutting techniques. A set of signal processing data from dry electrodes demonstrate successful real-time classification of eye motions, including blink, up, down, left, and right. Our study shows that the convolutional neural network performs exceptionally well compared to other machine learning methods, showing 98.3% accuracy with six classes: the highest performance till date in EOG classification with only four electrodes. Collectively, the real-time demonstration of continuous wireless control of a two-wheeled radio-controlled car captures the potential of the bioelectronic system and the algorithm for targeting various HMI and virtual reality applications.
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Affiliation(s)
- Seunghyeb Ban
- School
of Engineering and Computer Science, Washington
State University, Vancouver, Washington 98686, United States
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yoon Jae Lee
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
- School
of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Shinjae Kwon
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
- George
W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yun-Soung Kim
- BioMedical
Engineering and Imaging Institute, Icahn
School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Jae Won Chang
- Department
of Otolaryngology Head and Neck Surgery, School of Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea
| | - Jong-Hoon Kim
- School
of Engineering and Computer Science, Washington
State University, Vancouver, Washington 98686, United States
- Department
of Mechanical Engineering, University of
Washington, Seattle, Washington 98195, United States
| | - Woon-Hong Yeo
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
- George
W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, Georgia 30332, United States
- Parker
H. Petit Institute for Bioengineering and Biosciences, Institute for
Materials, Neural Engineering Center, Institute for Robotics and Intelligent
Machines, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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19
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Moshawrab M, Adda M, Bouzouane A, Ibrahim H, Raad A. Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23020828. [PMID: 36679626 PMCID: PMC9865666 DOI: 10.3390/s23020828] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 12/27/2022] [Accepted: 01/09/2023] [Indexed: 06/02/2023]
Abstract
Background: The advancement of information and communication technologies and the growing power of artificial intelligence are successfully transforming a number of concepts that are important to our daily lives. Many sectors, including education, healthcare, industry, and others, are benefiting greatly from the use of such resources. The healthcare sector, for example, was an early adopter of smart wearables, which primarily serve as diagnostic tools. In this context, smart wearables have demonstrated their effectiveness in detecting and predicting cardiovascular diseases (CVDs), the leading cause of death worldwide. Objective: In this study, a systematic literature review of smart wearable applications for cardiovascular disease detection and prediction is presented. After conducting the required search, the documents that met the criteria were analyzed to extract key criteria such as the publication year, vital signs recorded, diseases studied, hardware used, smart models used, datasets used, and performance metrics. Methods: This study followed the PRISMA guidelines by searching IEEE, PubMed, and Scopus for publications published between 2010 and 2022. Once records were located, they were reviewed to determine which ones should be included in the analysis. Finally, the analysis was completed, and the relevant data were included in the review along with the relevant articles. Results: As a result of the comprehensive search procedures, 87 papers were deemed relevant for further review. In addition, the results are discussed to evaluate the development and use of smart wearable devices for cardiovascular disease management, and the results demonstrate the high efficiency of such wearable devices. Conclusions: The results clearly show that interest in this topic has increased. Although the results show that smart wearables are quite accurate in detecting, predicting, and even treating cardiovascular disease, further research is needed to improve their use.
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Affiliation(s)
- Mohammad Moshawrab
- Département de Mathématiques, Informatique et Génie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
| | - Mehdi Adda
- Département de Mathématiques, Informatique et Génie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
| | - Abdenour Bouzouane
- Département d’Informatique et de Mathématique, Université du Québec à Chicoutimi, 555 Boulevard de l’Université, Chicoutimi, QC G7H 2B1, Canada
| | - Hussein Ibrahim
- Institut Technologique de Maintenance Industrielle, 175 Rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada
| | - Ali Raad
- Faculty of Arts & Sciences, Islamic University of Lebanon, Wardaniyeh P.O. Box 30014, Lebanon
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20
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Park S, Ban S, Zavanelli N, Bunn AE, Kwon S, Lim HR, Yeo WH, Kim JH. Fully Screen-Printed PI/PEG Blends Enabled Patternable Electrodes for Scalable Manufacturing of Skin-Conformal, Stretchable, Wearable Electronics. ACS APPLIED MATERIALS & INTERFACES 2023; 15:2092-2103. [PMID: 36594669 DOI: 10.1021/acsami.2c17653] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Recent advances in soft materials and nano-microfabrication have enabled the development of flexible wearable electronics. At the same time, printing technologies have been demonstrated to be efficient and compatible with polymeric materials for manufacturing wearable electronics. However, wearable device manufacturing still counts on a costly, complex, multistep, and error-prone cleanroom process. Here, we present fully screen-printable, skin-conformal electrodes for low-cost and scalable manufacturing of wearable electronics. The screen printing of the polyimide (PI) layer enables facile, low-cost, scalable, high-throughput manufacturing. PI mixed with poly(ethylene glycol) exhibits a shear-thinning behavior, significantly improving the printability of PI. The premixed Ag/AgCl ink is then used for conductive layer printing. The serpentine pattern of the screen-printed electrode accommodates natural deformation under stretching (30%) and bending conditions (180°), which are verified by computational and experimental studies. Real-time wireless electrocardiogram monitoring is also successfully demonstrated using the printed electrodes with a flexible printed circuit. The algorithm developed in this study can calculate accurate heart rates, respiratory rates, and heart rate variability metrics for arrhythmia detection.
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Affiliation(s)
- Sehyun Park
- School of Engineering and Computer Science, Washington State University, Vancouver, Washington98686, United States
| | - Seunghyeb Ban
- School of Engineering and Computer Science, Washington State University, Vancouver, Washington98686, United States
| | - Nathan Zavanelli
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia30332, United States
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, Georgia30332, United States
| | - Andrew E Bunn
- School of Engineering and Computer Science, Washington State University, Vancouver, Washington98686, United States
| | - Shinjae Kwon
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia30332, United States
| | - Hyo-Ryoung Lim
- Major of Human Bioconvergence, Division of Smart Healthcare, College of Information Technology and Convergence, Pukyong National University, Busan48513, Republic of Korea
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia30332, United States
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, Georgia30332, United States
- Parker H. Petit Institute for Bioengineering and Biosciences, Institute for Materials, Neural Engineering Center, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, Georgia30332, United States
| | - Jong-Hoon Kim
- School of Engineering and Computer Science, Washington State University, Vancouver, Washington98686, United States
- Department of Mechanical Engineering, University of Washington, Seattle, Washington98195, United States
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21
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Xie L, Zhang Z, Wu Q, Gao Z, Mi G, Wang R, Sun HB, Zhao Y, Du Y. Intelligent wearable devices based on nanomaterials and nanostructures for healthcare. NANOSCALE 2023; 15:405-433. [PMID: 36519286 DOI: 10.1039/d2nr04551f] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Emerging classes of flexible electronic sensors as alternatives to conventional rigid sensors offer a powerful set of capabilities for detecting and quantifying physiological and physical signals from human skin in personal healthcare. Unfortunately, the practical applications and commercialization of flexible sensors are generally limited by certain unsatisfactory aspects of their performance, such as biocompatibility, low sensing range, power supply, or single sensory function. This review intends to provide up-to-date literature on wearable devices for smart healthcare. A systematic review is provided, from sensors based on nanomaterials and nanostructures, algorithms, to multifunctional integrated devices with stretchability, self-powered performance, and biocompatibility. Typical electromechanical sensors are investigated with a specific focus on the strategies for constructing high-performance sensors based on nanomaterials and nanostructures. Then, the review emphasizes the importance of tailoring the fabrication techniques in order to improve stretchability, biocompatibility, and self-powered performance. The construction of wearable devices with high integration, high performance, and multi-functionalization for multiparameter healthcare is discussed in depth. Integrating wearable devices with appropriate machine learning algorithms is summarized. After interpretation of the algorithms, intelligent predictions are produced to give instructions or predictions for smart implementations. It is desired that this review will offer guidance for future excellence in flexible wearable sensing technologies and provide insight into commercial wearable sensors.
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Affiliation(s)
- Liping Xie
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Zelin Zhang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Qiushuo Wu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Zhuxuan Gao
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Gaotian Mi
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Renqiao Wang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Hong-Bin Sun
- Department of Chemistry, Northeastern University, Shenyang, 110819, China
| | - Yue Zhao
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Yanan Du
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China
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22
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Social-Ecological Measurement of Daily Life: How Relationally Focused Ambulatory Assessment can Advance Clinical Intervention Science. REVIEW OF GENERAL PSYCHOLOGY 2022. [DOI: 10.1177/10892680221142802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Individuals’ daily behaviors and social interactions play a central role in the diagnosis and treatment of psychological disorders. Despite this, observational ambulatory assessment methods—research methods that allow for direct and passive assessment of individuals’ momentary activities and interactions—have a remarkably scant history in the clinical science field. Prior discussions of ambulatory assessment methods in clinical science have focused on subjective methods (e.g., ecological momentary assessment) and physiological methods (e.g., wearable heart rate monitoring). Comparatively less attention has been dedicated to ambulatory assessment methods that collect objective, relational data about individuals’ social behaviors and their interactions with their momentary environmental contexts. Drawing on extant social-ecological measurement frameworks, this article first provides a conceptual and psychometric rationale for the integration of daily relational data into clinical science research. Next, the nascent research applying such methods to clinical science is reviewed, and priorities for further research organized by the NIH Stage Model for Clinical Science Research are recommended. These data can provide unique information about the social contexts of diverse patient populations; identify social-ecological targets for transdiagnostic, precision, and culturally responsive interventions; and contribute novel data about the effectiveness of established interventions at creating behavioral and relational change.
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23
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Bu Y, Kurniawan JF, Prince J, Nguyen AKL, Ho B, Sit NLJ, Pham T, Wu VM, Tjhia B, Shin AJ, Wu TC, Tu XM, Rao R, Coleman TP, Lerman I. A flexible adhesive surface electrode array capable of cervical electroneurography during a sequential autonomic stress challenge. Sci Rep 2022; 12:19467. [PMID: 36376365 PMCID: PMC9663551 DOI: 10.1038/s41598-022-21817-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 10/04/2022] [Indexed: 11/16/2022] Open
Abstract
This study introduces a flexible, adhesive-integrated electrode array that was developed to enable non-invasive monitoring of cervical nerve activity. The device uses silver-silver chloride as the electrode material of choice and combines it with an electrode array consisting of a customized biopotential data acquisition unit and integrated graphical user interface (GUI) for visualization of real-time monitoring. Preliminary testing demonstrated this electrode design can achieve a high signal to noise ratio during cervical neural recordings. To demonstrate the capability of the surface electrodes to detect changes in cervical neuronal activity, the cold-pressor test (CPT) and a timed respiratory challenge were employed as stressors to the autonomic nervous system. This sensor system recording, a new technique, was termed Cervical Electroneurography (CEN). By applying a custom spike sorting algorithm to the electrode measurements, neural activity was classified in two ways: (1) pre-to-post CPT, and (2) during a timed respiratory challenge. Unique to this work: (1) rostral to caudal channel position-specific (cephalad to caudal) firing patterns and (2) cross challenge biotype-specific change in average CEN firing, were observed with both CPT and the timed respiratory challenge. Future work is planned to develop an ambulatory CEN recording device that could provide immediate notification of autonomic nervous system activity changes that might indicate autonomic dysregulation in healthy subjects and clinical disease states.
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Affiliation(s)
- Yifeng Bu
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA.
| | - Jonas F Kurniawan
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA, 92093, USA
| | - Jacob Prince
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Andrew K L Nguyen
- Department of Physics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Brandon Ho
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Nathan L J Sit
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Timothy Pham
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Vincent M Wu
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Boris Tjhia
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Andrew J Shin
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, 94305, USA
| | - Tsung-Chin Wu
- Division of Biostatistics and Bioinformatics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Xin M Tu
- Division of Biostatistics and Bioinformatics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Ramesh Rao
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Todd P Coleman
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Imanuel Lerman
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Anesthesiology, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Psychiatry, Center for Stress and Mental Health, VA San Diego, La Jolla, CA, 92093, USA
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24
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Oh JY, Hwang CS, Yang YS, Song M, Kim J, Kim TS, Kim S, Oh H, Kang SY, Pi JE, Koo JB, Park CW, Lee H. Dual-Functional Self-Attachable and Stretchable Interface for Universal Three-Dimensional Modular Electronics. ACS APPLIED MATERIALS & INTERFACES 2022; 14:49303-49312. [PMID: 36241609 DOI: 10.1021/acsami.2c13803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Stretchable electronics have become essential for custom-built electronics, self-assembling robotics, and wearable devices. Although many stretchable electronics contain integrated systems, they still limit bulky connection systems. We introduce a new dual-functioned self-attachable and stretchable interface (SASI), allowing a direct and instant interconnection between rigid and soft electronics. The SASI consists of a sticky and stretchable substrate and surface-embedded serpentine conductors with the single-sided polyimide fabricated using the embedded transfer process. The adhesion property of the SASI is controlled by the mixed elastomer ratio. The resulting sticky and conductive SASI can instantly adhere to a metal surface and create conductive paths. The SASI serpentine conductors exhibit high stretchability (∼290%) and provide self-attachable, re-attachable, and low-resistant electrical contacts (0.85 ohms in 0.25 mm2) between interfaces without pressure, heat, or extra solder. In addition, three-dimensional curved and modular electronics can be formed with the SASI by compiling functional blocks. SASI provides a novel strategy for assembling functional chips or modules for stretchable electronics, opening a path to onboard integrated electronics that are customizable by users for real-world stretchable electronics.
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Affiliation(s)
- Ji-Young Oh
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Chi-Sun Hwang
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Yong Suk Yang
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Myoung Song
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Junmo Kim
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Taek-Soo Kim
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Sujung Kim
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Himchan Oh
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Seung Youl Kang
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Jae-Eun Pi
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Jae Bon Koo
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Chan Woo Park
- Reality Device Research Division, ICT Creative Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea
| | - Hyoyoung Lee
- Department of Chemistry, Sungkyunkwan University (SKKU), 2066 Seoburo, Jangan-Gu, Suwon 16419, Republic of Korea
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25
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Li BM, Reese BL, Ingram K, Huddleston ME, Jenkins M, Zaets A, Reuter M, Grogg MW, Nelson MT, Zhou Y, Ju B, Sennik B, Farrell ZJ, Jur JS, Tabor CE. Textile-Integrated Liquid Metal Electrodes for Electrophysiological Monitoring. Adv Healthc Mater 2022; 11:e2200745. [PMID: 35734914 DOI: 10.1002/adhm.202200745] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 05/12/2022] [Indexed: 01/27/2023]
Abstract
Next generation textile-based wearable sensing systems will require flexibility and strength to maintain capabilities over a wide range of deformations. However, current material sets used for textile-based skin contacting electrodes lack these key properties, which hinder applications such as electrophysiological sensing. In this work, a facile spray coating approach to integrate liquid metal nanoparticle systems into textile form factors for conformal, flexible, and robust electrodes is presented. The liquid metal system employs functionalized liquid metal nanoparticles that provide a simple "peel-off to activate" means of imparting conductivity. The spray coating approach combined with the functionalized liquid metal system enables the creation of long-term reusable textile-integrated liquid metal electrodes (TILEs). Although the TILEs are dry electrodes by nature, they show equal skin-electrode impedances and sensing capabilities with improved wearability compared to commercial wet electrodes. Biocompatibility of TILEs in an in vivo skin environment is demonstrated, while providing improved sensing performance compared to previously reported textile-based dry electrodes. The "spray on dry-behave like wet" characteristics of TILEs opens opportunities for textile-based wearable health monitoring, haptics, and augmented/virtual reality applications that require the use of flexible and conformable dry electrodes.
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Affiliation(s)
- Braden M Li
- Department of Textile Engineering, Chemistry and Science, North Carolina State University, Raleigh, NC, 27606, USA.,Air Force Research Laboratory, Materials and Manufacturing Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA.,Air Force Life Cycle Management Center, Human Systems Division, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - Brandon L Reese
- Department of Physics, Miami University, Oxford, OH, 45056, USA.,UES Inc, Dayton, OH, 45432, USA
| | - Katherine Ingram
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - Mary E Huddleston
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - Meghan Jenkins
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - Allison Zaets
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - Matthew Reuter
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - Matthew W Grogg
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - M Tyler Nelson
- Air Force Research Laboratory, 711th Human Performance Wing, Airman Systems Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
| | - Ying Zhou
- Department of Textile Engineering, Chemistry and Science, North Carolina State University, Raleigh, NC, 27606, USA
| | - Beomjun Ju
- Department of Textile Engineering, Chemistry and Science, North Carolina State University, Raleigh, NC, 27606, USA
| | - Busra Sennik
- Department of Textile Engineering, Chemistry and Science, North Carolina State University, Raleigh, NC, 27606, USA
| | - Zachary J Farrell
- Air Force Research Laboratory, Materials and Manufacturing Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA.,UES Inc, Dayton, OH, 45432, USA
| | - Jesse S Jur
- Department of Textile Engineering, Chemistry and Science, North Carolina State University, Raleigh, NC, 27606, USA
| | - Christopher E Tabor
- Air Force Research Laboratory, Materials and Manufacturing Directorate, Wright-Patterson AFB, Dayton, OH, 45433, USA
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26
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Ji S, Chen X. Enhancing the interfacial binding strength between modular stretchable electronic components. Natl Sci Rev 2022; 10:nwac172. [PMID: 36684519 PMCID: PMC9843131 DOI: 10.1093/nsr/nwac172] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 07/14/2022] [Accepted: 08/19/2022] [Indexed: 01/25/2023] Open
Abstract
Stretchable electronics are emerging for personalized and decentralized clinics, wearable devices and human-machine interactions. Nowadays, separated stretchable functional parts have been well developed and are approaching practical usage. However, the production of whole stretchable devices with full functions still faces a huge challenge: the integration of different components, which was hindered by the mechanical mismatch and stress/strain concentration at the connection interfaces. To avoid connection failure in stretchable devices, a new research focus is to improve the interfacial binding strength between different components. In this review, recent developments to enhance interfacial strength in wearable/implantable electronics are introduced and catalogued into three major strategies: (i) covalent bonding between different device parts, (ii) molecular interpenetration or mechanical interlocking at the interfaces and (iii) covalent connection between the human body and devices. Besides reviewing current methods, we also discuss the existing challenges and possible improvements for stretchable devices from the aspect of interfacial connections.
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Affiliation(s)
- Shaobo Ji
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University,Singapore 639798, Singapore
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27
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Wu H, Huang Y, Yin Z. Flexible hybrid electronics: Enabling integration techniques and applications. SCIENCE CHINA. TECHNOLOGICAL SCIENCES 2022; 65:1995-2006. [PMID: 35892001 PMCID: PMC9302228 DOI: 10.1007/s11431-022-2074-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/05/2022] [Indexed: 06/15/2023]
Abstract
The conventional electronic systems enabled by rigid electronic are prone to malfunction under deformation, greatly limiting their application prospects. As an emerging platform for applications in healthcare monitoring and human-machine interface (HMI), flexible electronics have attracted growing attention due to its remarkable advantages, such as stretchability, flexibility, conformability, and wearing comfort. However, to realize the overall electronic systems, rigid components are also required for functions such as signal acquisition and transmission. Therefore, flexible hybrid electronics (FHE), which simultaneously possesses the desirable flexibility and enables the integration of rigid components for functionality, has been emerging as a promising strategy. This paper reviews the enabling integration techniques for FHE, including technologies for two-dimensional/three-dimensional (2D/3D) interconnects, bonding of rigid integrated circuit (IC) chips to soft substrate, stress-isolation structures, and representative applications of FHE. In addition, future challenges and opportunities involved in FHE-based systems are also discussed.
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Affiliation(s)
- Hao Wu
- Flexible Electronics Research Center, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074 China
| | - YongAn Huang
- Flexible Electronics Research Center, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074 China
| | - ZhouPing Yin
- Flexible Electronics Research Center, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074 China
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28
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Lee SH, Kim YS, Yeo MK, Mahmood M, Zavanelli N, Chung C, Heo JY, Kim Y, Jung SS, Yeo WH. Fully portable continuous real-time auscultation with a soft wearable stethoscope designed for automated disease diagnosis. SCIENCE ADVANCES 2022; 8:eabo5867. [PMID: 35613271 PMCID: PMC9132462 DOI: 10.1126/sciadv.abo5867] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Modern auscultation, using digital stethoscopes, provides a better solution than conventional methods in sound recording and visualization. However, current digital stethoscopes are too bulky and nonconformal to the skin for continuous auscultation. Moreover, motion artifacts from the rigidity cause friction noise, leading to inaccurate diagnoses. Here, we report a class of technologies that offers real-time, wireless, continuous auscultation using a soft wearable system as a quantitative disease diagnosis tool for various diseases. The soft device can detect continuous cardiopulmonary sounds with minimal noise and classify real-time signal abnormalities. A clinical study with multiple patients and control subjects captures the unique advantage of the wearable auscultation method with embedded machine learning for automated diagnoses of four types of lung diseases: crackle, wheeze, stridor, and rhonchi, with a 95% accuracy. The soft system also demonstrates the potential for a sleep study by detecting disordered breathing for home sleep and apnea detection.
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Affiliation(s)
- Sung Hoon Lee
- School of Electrical and Computer Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Yun-Soung Kim
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Min-Kyung Yeo
- Department of Pathology, Chungnam National University School of Medicine, Daejeon 35015, Republic of Korea
| | - Musa Mahmood
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Nathan Zavanelli
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Chaeuk Chung
- Division of Pulmonology, Department of Internal Medicine, Chungnam National University School of Medicine, Daejeon 35015, Republic of Korea
| | - Jun Young Heo
- Department of Biochemistry, Chungnam National University School of Medicine, Daejeon 35015, Republic of Korea
| | - Yoonjoo Kim
- Division of Pulmonology, Department of Internal Medicine, Chungnam National University School of Medicine, Daejeon 35015, Republic of Korea
| | - Sung-Soo Jung
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea
- Corresponding author. (W.-H.Y.); (S.-S.J.)
| | - Woon-Hong Yeo
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Neural Engineering Center, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Corresponding author. (W.-H.Y.); (S.-S.J.)
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29
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Kurniawan JF, Allegra AB, Pham T, Nguyen AKL, Sit NLJ, Tjhia B, Shin AJ, Coleman TP. Electrochemical performance study of Ag/AgCl and Au flexible electrodes for unobtrusive monitoring of human biopotentials. NANO SELECT 2022. [DOI: 10.1002/nano.202100345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Jonas F. Kurniawan
- Material Science and Engineering Program, University of California San Diego, La Jolla California USA
- Department of Bioengineering, University of California San Diego, La Jolla California USA
| | - Alexis B. Allegra
- Department of Bioengineering, University of California San Diego, La Jolla California USA
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla California USA
| | - Timothy Pham
- Department of Nanoengineering, University of California San Diego, La Jolla California USA
| | - Andrew K. L. Nguyen
- Department of Physic, University of California San Diego, La Jolla California USA
| | - Nathan L. J. Sit
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla California USA
| | - Boris Tjhia
- Department of Nanoengineering, University of California San Diego, La Jolla California USA
| | - Andrew J. Shin
- Department of Nanoengineering, University of California San Diego, La Jolla California USA
| | - Todd P. Coleman
- Department of Bioengineering, University of California San Diego, La Jolla California USA
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30
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Kim H, Kim E, Choi C, Yeo WH. Advances in Soft and Dry Electrodes for Wearable Health Monitoring Devices. MICROMACHINES 2022; 13:mi13040629. [PMID: 35457934 PMCID: PMC9029742 DOI: 10.3390/mi13040629] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 01/20/2023]
Abstract
Electrophysiology signals are crucial health status indicators as they are related to all human activities. Current demands for mobile healthcare have driven considerable interest in developing skin-mounted electrodes for health monitoring. Silver-Silver chloride-based (Ag-/AgCl) wet electrodes, commonly used in conventional clinical practice, provide excellent signal quality, but cannot monitor long-term signals due to gel evaporation and skin irritation. Therefore, the focus has shifted to developing dry electrodes that can operate without gels and extra adhesives. Compared to conventional wet electrodes, dry ones offer various advantages in terms of ease of use, long-term stability, and biocompatibility. This review outlines a systematic summary of the latest research on high-performance soft and dry electrodes. In addition, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, strategies to promote physical adhesion, methods for higher breathability, and their applications in wearable biomedical devices. Finally, we discuss the developmental challenges and advantages of various dry electrodes, while suggesting research directions for future studies.
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Affiliation(s)
- Hyeonseok Kim
- Georgia Institute of Technology, George W. Woodruff School of Mechanical Engineering, Atlanta, GA 30332, USA; (H.K.); (E.K.); (C.C.)
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Eugene Kim
- Georgia Institute of Technology, George W. Woodruff School of Mechanical Engineering, Atlanta, GA 30332, USA; (H.K.); (E.K.); (C.C.)
| | - Chanyeong Choi
- Georgia Institute of Technology, George W. Woodruff School of Mechanical Engineering, Atlanta, GA 30332, USA; (H.K.); (E.K.); (C.C.)
| | - Woon-Hong Yeo
- Georgia Institute of Technology, George W. Woodruff School of Mechanical Engineering, Atlanta, GA 30332, USA; (H.K.); (E.K.); (C.C.)
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Neural Engineering Center, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Correspondence: ; Tel.: +1-404-385-5710
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Kim Y, Kim J, Chicas R, Xiuhtecutli N, Matthews J, Zavanelli N, Kwon S, Lee SH, Hertzberg VS, Yeo W. Soft Wireless Bioelectronics Designed for Real-Time, Continuous Health Monitoring of Farmworkers. Adv Healthc Mater 2022; 11:e2200170. [PMID: 35306761 DOI: 10.1002/adhm.202200170] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/08/2022] [Indexed: 12/23/2022]
Abstract
Hotter summers caused by global warming and increased workload and duration are endangering the health of farmworkers, a high-risk population for heat-related illness (HRI), and deaths. Although prior studies using wearable sensors show the feasibility of employing field-collected data for HRI monitoring, existing devices still have limitations, such as data loss from motion artifacts, device discomfort from rigid electronics, difficulties with administering ingestible sensors, and low temporal resolution. Here, this paper introduces a wireless, wearable bioelectronic system with functionalities for continuous monitoring of skin temperature, electrocardiograms (ECG), heart rates (HR), and activities, configured in a single integrated package. Advanced nanomanufacturing based on laser machining allows rapid device fabrication and direct incorporation of sensors with a highly breathable substrate, allowing for managing excessive sweating and multimodal stresses. To validate the device's performance in agricultural settings, the device is applied to multiple farmworkers at various operations, including fernery, nursery, and crop. The accurate data recording, including high-fidelity ECG (signal-to-noise ratio: >20 dB), accurate HR (r = 0.89, r2 = 0.65 in linear correlation), and reliable temperature/activity, confirms the device's capability for multiparameter health monitoring of farmworkers.
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Affiliation(s)
- Yun‐Soung Kim
- George W. Woodruff School of Mechanical Engineering and IEN Center for Human‐Centric Interfaces and Engineering Georgia Institute of Technology Atlanta GA 30332 USA
| | - Jihoon Kim
- George W. Woodruff School of Mechanical Engineering and IEN Center for Human‐Centric Interfaces and Engineering Georgia Institute of Technology Atlanta GA 30332 USA
| | - Roxana Chicas
- Parker H. Petit Institute for Bioengineering and Biosciences Georgia Institute of Technology Atlanta GA 30332 USA
| | - Nezahualcoyotl Xiuhtecutli
- Farmworker Association of Florida Apopka FL 32703 USA
- Department of Anthropology Tulane University New Orleans LA 70118 USA
| | - Jared Matthews
- George W. Woodruff School of Mechanical Engineering and IEN Center for Human‐Centric Interfaces and Engineering Georgia Institute of Technology Atlanta GA 30332 USA
| | - Nathan Zavanelli
- George W. Woodruff School of Mechanical Engineering and IEN Center for Human‐Centric Interfaces and Engineering Georgia Institute of Technology Atlanta GA 30332 USA
| | - Shinjae Kwon
- George W. Woodruff School of Mechanical Engineering and IEN Center for Human‐Centric Interfaces and Engineering Georgia Institute of Technology Atlanta GA 30332 USA
| | - Sung Hoon Lee
- George W. Woodruff School of Mechanical Engineering and IEN Center for Human‐Centric Interfaces and Engineering Georgia Institute of Technology Atlanta GA 30332 USA
| | - Vicki S. Hertzberg
- Parker H. Petit Institute for Bioengineering and Biosciences Georgia Institute of Technology Atlanta GA 30332 USA
| | - Woon‐Hong Yeo
- George W. Woodruff School of Mechanical Engineering and IEN Center for Human‐Centric Interfaces and Engineering Georgia Institute of Technology Atlanta GA 30332 USA
- Parker H. Petit Institute for Bioengineering and Biosciences Georgia Institute of Technology Atlanta GA 30332 USA
- Wallace H. Coulter Department of Biomedical Engineering Georgia Tech and Emory University Atlanta GA 30332 USA
- Institute for Materials Georgia Institute of Technology Atlanta GA 30332 USA
- Neural Engineering Center Georgia Institute of Technology Atlanta GA 30332 USA
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Oh J, Jang SG, Moon S, Kim J, Park HK, Kim HS, Park S, Jeong U. Air-Permeable Waterproofing Electrocardiogram Patch to Monitor Full-Day Activities for Multiple Days. Adv Healthc Mater 2022; 11:e2102703. [PMID: 35285162 DOI: 10.1002/adhm.202102703] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 02/14/2022] [Indexed: 11/10/2022]
Abstract
On-skin healthcare patch-type devices have great technological challenges in monitoring full-day activities and wearing for multiple days without detachment. These challenges can be overcome when the sensor is air permeable but waterproof. This study presents a light-weight, highly stable, and stretchable Au electrode that is fabricated by sputtering on an imidized nanofiber mat. The contact surface of the electrode is hydro-wetting and the outer surface of the electrode is hydrophobic, so the porous electrode simultaneously has excellent sweat permeability and waterproofing capabilities. The electrode is applied to the electrocardiogram sensor for monitoring the cardiac signals for five consecutive days without detaching while doing various full-day activities such as relaxing, exercising, showering, and sleeping. This study suggests a modular setup of the electrodes and the cardiac signal processing unit for activating the device when cardiac monitoring is required.
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Affiliation(s)
- Joosung Oh
- Department of Materials Science and Engineering Pohang University of Science and Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
| | - Seok Geun Jang
- Department of Electrical Engineering Pohang University of Science Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
| | - Sungmin Moon
- Department of Materials Science and Engineering Pohang University of Science and Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
| | - Junho Kim
- School of Interdisciplinary Bioscience and Bioengineering Pohang University of Science Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
| | - Hyung Keun Park
- Department of Materials Science and Engineering Pohang University of Science and Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
| | - Hyoung Seop Kim
- Department of Materials Science and Engineering Pohang University of Science and Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
| | - Sung‐Min Park
- Department of convergence IT engineering Electrical Engineering and Mechanical Engineering Pohang University of Science Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
| | - Unyong Jeong
- Department of Materials Science and Engineering Pohang University of Science and Technology 77 Cheongam‐Ro Nam‐Gu Pohang 37673 Korea
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Kwon K, Kwon S, Yeo WH. Automatic and Accurate Sleep Stage Classification via a Convolutional Deep Neural Network and Nanomembrane Electrodes. BIOSENSORS 2022; 12:155. [PMID: 35323425 PMCID: PMC8946692 DOI: 10.3390/bios12030155] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 02/09/2022] [Accepted: 02/28/2022] [Indexed: 05/13/2023]
Abstract
Sleep stage classification is an essential process of diagnosing sleep disorders and related diseases. Automatic sleep stage classification using machine learning has been widely studied due to its higher efficiency compared with manual scoring. Typically, a few polysomnography data are selected as input signals, and human experts label the corresponding sleep stages manually. However, the manual process includes human error and inconsistency in the scoring and stage classification. Here, we present a convolutional neural network (CNN)-based classification method that offers highly accurate, automatic sleep stage detection, validated by a public dataset and new data measured by wearable nanomembrane dry electrodes. First, our study makes a training and validation model using a public dataset with two brain signal and two eye signal channels. Then, we validate this model with a new dataset measured by a set of nanomembrane electrodes. The result of the automatic sleep stage classification shows that our CNN model with multi-taper spectrogram pre-processing achieved 88.85% training accuracy on the validation dataset and 81.52% prediction accuracy on our laboratory dataset. These results validate the reliability of our classification method on the standard polysomnography dataset and the transferability of our CNN model for other datasets measured with the wearable electrodes.
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Affiliation(s)
- Kangkyu Kwon
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA;
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA;
| | - Shinjae Kwon
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA;
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Woon-Hong Yeo
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA;
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Neural Engineering Center, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Qiao Y, Li X, Wang J, Ji S, Hirtz T, Tian H, Jian J, Cui T, Dong Y, Xu X, Wang F, Wang H, Zhou J, Yang Y, Someya T, Ren TL. Intelligent and Multifunctional Graphene Nanomesh Electronic Skin with High Comfort. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2022; 18:e2104810. [PMID: 34882950 DOI: 10.1002/smll.202104810] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/21/2021] [Indexed: 05/15/2023]
Abstract
As the aging population increases in many countries, electronic skin (e-skin) for health monitoring has been attracting much attention. However, to realize the industrialization of e-skin, two factors must be optimized. The first is to achieve high comfort, which can significantly improve the user experience. The second is to make the e-skin intelligent, so it can detect and analyze physiological signals at the same time. In this article, intelligent and multifunctional e-skin consisting of laser-scribed graphene and polyurethane (PU) nanomesh is realized with high comfort. The e-skin can be used as a strain sensor with large measurement range (>60%), good sensitivity (GF≈40), high linearity range (60%), and excellent stability (>1000 cycles). By analyzing the morphology of e-skin, a parallel networks model is proposed to express the mechanism of the strain sensor. In addition, laser scribing is also applied to etch the insulating PU, which greatly decreases the impedance in detecting electrophysiology signals. Finally, the e-skin is applied to monitor the electrocardiogram, electroencephalogram (EEG), and electrooculogram signals. A time- and frequency-domain concatenated convolution neural network is built to analyze the EEG signal detected using the e-skin on the forehead and classify the attention level of testers.
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Affiliation(s)
- Yancong Qiao
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518707, China
| | - Xiaoshi Li
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Jiabin Wang
- Electrical and Electronic Engineering and Information Systems, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Shourui Ji
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Thomas Hirtz
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - He Tian
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Jinming Jian
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Tianrui Cui
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Ying Dong
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Xinwei Xu
- Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Fei Wang
- School of Microelectronics, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Hong Wang
- Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Jianhua Zhou
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518707, China
| | - Yi Yang
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Takao Someya
- Electrical and Electronic Engineering and Information Systems, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Tian-Ling Ren
- School of Integrated Circuits (SIC) and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
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Zhang Z, Su R, Han F, Zheng Z, Liu Y, Zhou X, Li Q, Zhai X, Wu J, Pan X, Pan H, Guo P, Li Z, Liu Z, Zhao X. A soft intelligent dressing with pH and temperature sensors for early detection of wound infection. RSC Adv 2022; 12:3243-3252. [PMID: 35425400 PMCID: PMC8979260 DOI: 10.1039/d1ra08375a] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 01/16/2022] [Indexed: 12/28/2022] Open
Abstract
Wound infection is a common clinical problem. Traditional detection methods can not provide infection early warning information in time. With the development of flexible electronics, flexible wearable devices have been widely used in the field of intelligent monitoring. Here, we describe the development of a soft wound infection monitoring system with pH sensors and temperature sensors. The measurement range of pH was 4-10, the fitting accuracy was 99.8%, and the response time was less than 6 s. The temperature sensor array showed good accuracy and short response times in the range of 30 °C to 40 °C. A series of in vitro tests and the use of a rat model of Staphylococcus aureus infection confirmed that this flexible detection system can monitor the pH and temperature changes occurring in the early stage of infection, which provides an effective reference for clinical application.
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Affiliation(s)
- Zhiyang Zhang
- School of Materials Science and Engineering, Tianjin Key Laboratory of Composite and Functional Materials, Tianjin University Tianjin 300350 PR China
- Research Center for Human Tissue and Organs Degeneration, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Rui Su
- Research Center for Human Tissue and Organs Degeneration, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 PR China
- Institute of Materials for Energy and Environment, State Key Laboratory of Bio-fibers and Eco-textiles, School of Materials Science and Engineering, Qingdao University Qingdao 266071 PR China
| | - Fei Han
- Neural Engineering Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Zhiqiang Zheng
- Research Center for Human Tissue and Organs Degeneration, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Yuan Liu
- Research Center for Human Tissue and Organs Degeneration, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Xiaomeng Zhou
- Neural Engineering Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Qingsong Li
- Neural Engineering Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Xinyun Zhai
- Center for Rare Earth and Inorganic Functional Materials, School of Materials Science and Engineering, National Institute for Advanced Materials, Nankai University Tianjin 300350 PR China
| | - Jun Wu
- Shenzhen Key Laboratory for Innovative Technology in Orthopaedic Trauma, The University of Hong Kong-Shenzhen Hospital Shenzhen 518053 PR China
| | - Xiaohua Pan
- Southern Medical University, Shenzhen Bao'an People's Hospital, Dept Orthoped & Traumatol Shenzhen 518101 PR China
| | - Haobo Pan
- Research Center for Human Tissue and Organs Degeneration, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Peizhi Guo
- Institute of Materials for Energy and Environment, State Key Laboratory of Bio-fibers and Eco-textiles, School of Materials Science and Engineering, Qingdao University Qingdao 266071 PR China
| | - Zhaoyang Li
- School of Materials Science and Engineering, Tianjin Key Laboratory of Composite and Functional Materials, Tianjin University Tianjin 300350 PR China
| | - Zhiyuan Liu
- Neural Engineering Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 PR China
| | - Xiaoli Zhao
- Research Center for Human Tissue and Organs Degeneration, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 PR China
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Guess M, Zavanelli N, Yeo WH. Recent Advances in Materials and Flexible Sensors for Arrhythmia Detection. MATERIALS 2022; 15:ma15030724. [PMID: 35160670 PMCID: PMC8836661 DOI: 10.3390/ma15030724] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/06/2022] [Accepted: 01/16/2022] [Indexed: 12/24/2022]
Abstract
Arrhythmias are one of the leading causes of death in the United States, and their early detection is essential for patient wellness. However, traditional arrhythmia diagnosis by expert evaluation from intermittent clinical examinations is time-consuming and often lacks quantitative data. Modern wearable sensors and machine learning algorithms have attempted to alleviate this problem by providing continuous monitoring and real-time arrhythmia detection. However, current devices are still largely limited by the fundamental mismatch between skin and sensor, giving way to motion artifacts. Additionally, the desirable qualities of flexibility, robustness, breathability, adhesiveness, stretchability, and durability cannot all be met at once. Flexible sensors have improved upon the current clinical arrhythmia detection methods by following the topography of skin and reducing the natural interface mismatch between cardiac monitoring sensors and human skin. Flexible bioelectric, optoelectronic, ultrasonic, and mechanoelectrical sensors have been demonstrated to provide essential information about heart-rate variability, which is crucial in detecting and classifying arrhythmias. In this review, we analyze the current trends in flexible wearable sensors for cardiac monitoring and the efficacy of these devices for arrhythmia detection.
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Affiliation(s)
- Matthew Guess
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.G.); (N.Z.)
- Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Nathan Zavanelli
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.G.); (N.Z.)
- Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.G.); (N.Z.)
- Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Neural Engineering Center, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Correspondence: ; Tel.: +1-404-385-5710
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Zavanelli N, Kim H, Kim J, Herbert R, Mahmood M, Kim YS, Kwon S, Bolus NB, Torstrick FB, Lee CSD, Yeo WH. At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch. SCIENCE ADVANCES 2021; 7:eabl4146. [PMID: 34936438 PMCID: PMC8694628 DOI: 10.1126/sciadv.abl4146] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 11/04/2021] [Indexed: 05/06/2023]
Abstract
Obstructive sleep apnea (OSA) affects more than 900 million adults globally and can create serious health complications when untreated; however, 80% of cases remain undiagnosed. Critically, current diagnostic techniques are fundamentally limited by low throughputs and high failure rates. Here, we report a wireless, fully integrated, soft patch with skin-like mechanics optimized through analytical and computational studies to capture seismocardiograms, electrocardiograms, and photoplethysmograms from the sternum, allowing clinicians to investigate the cardiovascular response to OSA during home sleep tests. In preliminary trials with symptomatic and control subjects, the soft device demonstrated excellent ability to detect blood-oxygen saturation, respiratory effort, respiration rate, heart rate, cardiac pre-ejection period and ejection timing, aortic opening mechanics, heart rate variability, and sleep staging. Last, machine learning is used to autodetect apneas and hypopneas with 100% sensitivity and 95% precision in preliminary at-home trials with symptomatic patients, compared to data scored by professionally certified sleep clinicians.
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Affiliation(s)
- Nathan Zavanelli
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Hojoong Kim
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Jongsu Kim
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Robert Herbert
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Musa Mahmood
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Yun-Soung Kim
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Shinjae Kwon
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | | | | | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Institute for Robotics and Intelligent Machines, Neural Engineering Center, Flexible and Wearable Electronics Advanced Research, Institute for Materials, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Song S, Kim KY, Lee SH, Kim KK, Lee K, Lee W, Jeon H, Ko SH. Recent Advances in 1D Nanomaterial‐Based Bioelectronics for Healthcare Applications. ADVANCED NANOBIOMED RESEARCH 2021. [DOI: 10.1002/anbr.202100111] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Affiliation(s)
- Sangmin Song
- Applied Nano and Thermal Science Lab Department of Mechanical Engineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 151-742 Korea
- Center for Biomaterials Biomedical Research Institute Korea Institute of Science and Technology (KIST) 5, Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Korea
| | - Kyung Yeun Kim
- Applied Nano and Thermal Science Lab Department of Mechanical Engineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 151-742 Korea
- Center for Biomaterials Biomedical Research Institute Korea Institute of Science and Technology (KIST) 5, Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Korea
| | - Sun Hee Lee
- Center for Biomaterials Biomedical Research Institute Korea Institute of Science and Technology (KIST) 5, Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Korea
| | - Kyun Kyu Kim
- Department of Chemical Engineering Stanford University Stanford CA 94305 USA
| | - Kyungwoo Lee
- Center for Biomaterials Biomedical Research Institute Korea Institute of Science and Technology (KIST) 5, Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Korea
| | - Wonryung Lee
- Center for Biomaterials Biomedical Research Institute Korea Institute of Science and Technology (KIST) 5, Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Korea
| | - Hojeong Jeon
- Center for Biomaterials Biomedical Research Institute Korea Institute of Science and Technology (KIST) 5, Hwarang-ro 14-gil Seongbuk-gu Seoul 02792 Korea
- KU-KIST Graduate School of Converging Science and Technology Korea University 145, Anam-ro Seongbuk-gu Seoul 02841 Korea
| | - Seung Hwan Ko
- Applied Nano and Thermal Science Lab Department of Mechanical Engineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 151-742 Korea
- Institute of Advanced Machines and Design/Institute of Engineering Research Seoul National University Seoul 08826 Korea
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Zhao D, Zhao J, Liu L, Guo W, Zhu K, Yang G, Li Z, Wu H. Flexible hybrid integration enabled on-skin electronics for wireless monitoring of electrophysiology and motion. IEEE Trans Biomed Eng 2021; 69:1340-1348. [PMID: 34596530 DOI: 10.1109/tbme.2021.3115464] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
On-skin electronics are promising in human motion and vital sign monitoring, disease diagnosis and treatment. On-skin systems are soft and stretchable, and can maintain electrical performances during bending, stretching or twisting, etc. However, current integrated circuit based fabrication processes are not compatible with stretchable substrate, and recently proposed flexible hybrid integration methods typically involve complicated fabrication processes or structural design, and do not support high integration density. Herein, we report a series of flexible hybrid integration strategies which endow the on-skin electronics with advantages of high integration density of electric components, facile fabrications, high stretchability and reliability. Proposed strategies include: 1. High I/O density with highly stretchable and conductive composite materials as interconnects; 2. Multi-layer structures enabled by stretchable and conductive via-holes; 3. High reliability approach for chip attachment onto stretchable substrate; 4. Design and fabrication of strain separation structure. Based on these methods, an on-skin flexible hybrid electronic system (FHES) is fabricated to collect electrocardiogram (ECG) and acceleration data, wirelessly transmit and display the data in real time on a mobile phone application through Bluetooth communication. We also verify the accuracy and stability of the FHES through the measurements of ECG and acceleration data from human skin under various conditions. The flexible hybrid integration schemes proposed can be adopted for the development of a variety of on-skin systems for biomedical applications.
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Kim H, Kwon Y, Zhu C, Wu F, Kwon S, Yeo W, Choo HJ. Real-Time Functional Assay of Volumetric Muscle Loss Injured Mouse Masseter Muscles via Nanomembrane Electronics. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2101037. [PMID: 34218527 PMCID: PMC8425913 DOI: 10.1002/advs.202101037] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 04/28/2021] [Indexed: 05/11/2023]
Abstract
Skeletal muscle has a remarkable regeneration capacity to recover its structure and function after injury, except for the traumatic loss of critical muscle volume, called volumetric muscle loss (VML). Although many extremity VML models have been conducted, craniofacial VML has not been well-studied due to unavailable in vivo assay tools. Here, this paper reports a wireless, noninvasive nanomembrane system that integrates skin-wearable printed sensors and electronics for real-time, continuous monitoring of VML on craniofacial muscles. The craniofacial VML model, using biopsy punch-induced masseter muscle injury, shows impaired muscle regeneration. To measure the electrophysiology of small and round masseter muscles of active mice during mastication, a wearable nanomembrane system with stretchable graphene sensors that can be laminated to the skin over target muscles is utilized. The noninvasive system provides highly sensitive electromyogram detection on masseter muscles with or without VML injury. Furthermore, it is demonstrated that the wireless sensor can monitor the recovery after transplantation surgery for craniofacial VML. Overall, the presented study shows the enormous potential of the masseter muscle VML injury model and wearable assay tool for the mechanism study and the therapeutic development of craniofacial VML.
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Affiliation(s)
- Hojoong Kim
- George W. Woodruff School of Mechanical EngineeringCollege of EngineeringGeorgia Institute of TechnologyAtlantaGA30332USA
- Center for Human‐Centric Interfaces and EngineeringInstitute for Electronics and NanotechnologyGeorgia Institute of TechnologyAtlantaGA30332USA
| | - Young‐Tae Kwon
- Department for Metal PowderKorea Institute of Materials ScienceChangwon51508South Korea
| | - Carol Zhu
- Department of Cell BiologySchool of MedicineEmory UniversityAtlantaGA30322USA
| | - Fang Wu
- Department of Cell BiologySchool of MedicineEmory UniversityAtlantaGA30322USA
| | - Shinjae Kwon
- George W. Woodruff School of Mechanical EngineeringCollege of EngineeringGeorgia Institute of TechnologyAtlantaGA30332USA
- Center for Human‐Centric Interfaces and EngineeringInstitute for Electronics and NanotechnologyGeorgia Institute of TechnologyAtlantaGA30332USA
| | - Woon‐Hong Yeo
- George W. Woodruff School of Mechanical EngineeringCollege of EngineeringGeorgia Institute of TechnologyAtlantaGA30332USA
- Center for Human‐Centric Interfaces and EngineeringInstitute for Electronics and NanotechnologyGeorgia Institute of TechnologyAtlantaGA30332USA
- Wallace H. Coulter Department of Biomedical EngineeringParker H. Petit Institute for Bioengineering and BiosciencesInstitute for MaterialsNeural Engineering CenterInstitute for Robotics and Intelligent MachinesGeorgia Institute of TechnologyAtlantaGA30332USA
| | - Hyojung J. Choo
- Department of Cell BiologySchool of MedicineEmory UniversityAtlantaGA30322USA
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Drynan D, Leroux TS, Zywiel MG. Acute Postoperative Pulmonary Embolism Detected at Home by a Patient's Personal Activity Monitor: A Case Report. JBJS Case Connect 2021; 11:01709767-202106000-00097. [PMID: 34101671 DOI: 10.2106/jbjs.cc.20.00841] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
CASE The increase in smart technology and integration into health care is inevitable. We present a case of a smart wristwatch prompting a patient readmission to the emergency department for postoperative pulmonary embolism investigation and management. This prompted the assessment for community-based smart technology use and integration to the postoperative monitoring and the associated issues. CONCLUSION Community-based smart technology is here to stay and is developing at a staggering rate, specifically with the cross-over to health monitoring. Constant patient monitoring and alerts are advantages, with smart technology and medical attention in this case. Surrounding issues of the technology must be considered with implementation.
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Affiliation(s)
- David Drynan
- Division of Orthopaedic Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Timothy S Leroux
- Division of Orthopaedic Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Michael G Zywiel
- Division of Orthopaedic Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
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Abstract
Despite the increasing awareness of the importance of sleep, the number of people suffering from insufficient sleep has increased every year. The gold-standard sleep assessment uses polysomnography (PSG) with various sensors to identify sleep patterns and disorders. However, due to the high cost of PSG and limited availability, many people with sleep disorders are left undiagnosed. Recent wearable sensors and electronics enable portable, continuous monitoring of sleep at home, overcoming the limitations of PSG. This report reviews the advances in wearable sensors, miniaturized electronics, and system packaging for home sleep monitoring. New devices available in the market and systems are collectively summarized based on their overall structure, form factor, materials, and sleep assessment method. It is expected that this review provides a comprehensive view of newly developed technologies and broad insights on wearable sensors and portable electronics toward advanced sleep monitoring as well as at-home sleep assessment.
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Affiliation(s)
- Shinjae Kwon
- George W. Woodruff School of Mechanical Engineering, Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Hojoong Kim
- George W. Woodruff School of Mechanical Engineering, Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Neural Engineering Center, Flexible and Wearable Electronics Advanced Research, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, USA
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Navaz AN, Serhani MA, El Kassabi HT, Al-Qirim N, Ismail H. Trends, Technologies, and Key Challenges in Smart and Connected Healthcare. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2021; 9:74044-74067. [PMID: 34812394 PMCID: PMC8545204 DOI: 10.1109/access.2021.3079217] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 05/05/2021] [Indexed: 05/04/2023]
Abstract
Cardio Vascular Diseases (CVD) is the leading cause of death globally and is increasing at an alarming rate, according to the American Heart Association's Heart Attack and Stroke Statistics-2021. This increase has been further exacerbated because of the current coronavirus (COVID-19) pandemic, thereby increasing the pressure on existing healthcare resources. Smart and Connected Health (SCH) is a viable solution for the prevalent healthcare challenges. It can reshape the course of healthcare to be more strategic, preventive, and custom-designed, making it more effective with value-added services. This research endeavors to classify state-of-the-art SCH technologies via a thorough literature review and analysis to comprehensively define SCH features and identify the enabling technology-related challenges in SCH adoption. We also propose an architectural model that captures the technological aspect of the SCH solution, its environment, and its primary involved stakeholders. It serves as a reference model for SCH acceptance and implementation. We reflected the COVID-19 case study illustrating how some countries have tackled the pandemic differently in terms of leveraging the power of different SCH technologies, such as big data, cloud computing, Internet of Things, artificial intelligence, robotics, blockchain, and mobile applications. In combating the pandemic, SCH has been used efficiently at different stages such as disease diagnosis, virus detection, individual monitoring, tracking, controlling, and resource allocation. Furthermore, this review highlights the challenges to SCH acceptance, as well as the potential research directions for better patient-centric healthcare.
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Affiliation(s)
- Alramzana Nujum Navaz
- Department of Information Systems and SecurityCollege of Information TechnologyUnited Arab Emirates UniversityAl AinUnited Arab Emirates
| | - Mohamed Adel Serhani
- Department of Information Systems and SecurityCollege of Information TechnologyUnited Arab Emirates UniversityAl AinUnited Arab Emirates
| | - Hadeel T. El Kassabi
- Department of Computer Science and Software EngineeringCollege of Information TechnologyUAE UniversityAl AinUnited Arab Emirates
| | - Nabeel Al-Qirim
- Department of Information Systems and SecurityCollege of Information TechnologyUnited Arab Emirates UniversityAl AinUnited Arab Emirates
| | - Heba Ismail
- Department of Computer Science and Information Technology (CS-IT)College of EngineeringAbu Dhabi UniversityAl AinUnited Arab Emirates
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Xu K, Fujita Y, Lu Y, Honda S, Shiomi M, Arie T, Akita S, Takei K. A Wearable Body Condition Sensor System with Wireless Feedback Alarm Functions. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2008701. [PMID: 33772894 DOI: 10.1002/adma.202008701] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 01/30/2021] [Indexed: 05/21/2023]
Abstract
Emerging feedback systems based on tracking body conditions can save human lives. In particular, vulnerable populations such as disabled people, elderly, and infants often require special care. For example, the high global mortality of infants primarily owing to sudden infant death syndrome while sleeping makes request for extraordinary attentions in neonatal intensive care units or daily lives. Here, a versatile laser-induced graphene (LIG)-based integrated flexible sensor system, which can wirelessly monitor the sleeping postures, respiration rate, and diaper moisture with feedback alarm notifications, is reported. A tilt sensor based on confining a liquid metal droplet inside a cavity can track at least 18 slanting orientations. A rapid and scalable laser direct writing method realizes LIG patterning in both the in-plane and out-of-plane configurations as well as the formation of nonstick conductive structures to the liquid metal. By rationally merging the LIG-based tilt, strain, and humidity sensors on a thin flexible film, the multimodal sensor device is applied to a diaper as a real-time feedback tracking system of the sleeping posture, respiration, and wetness toward secure and comfortable lives. User-friendly interfaces, which incorporate alarming functions, provide timely feedback for caregivers tending to vulnerable populations with limited self-care capabilities.
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Affiliation(s)
- Kaichen Xu
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
| | - Yusuke Fujita
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
| | - Yuyao Lu
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
| | - Satoko Honda
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
| | - Mao Shiomi
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
| | - Takayuki Arie
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
| | - Seiji Akita
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
| | - Kuniharu Takei
- Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka, 599-8531, Japan
- JST PRESTO, Kawaguchi, Saitama, 332-0012, Japan
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45
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Kim H, Kim YS, Mahmood M, Kwon S, Epps F, Rim YS, Yeo WH. Wireless, continuous monitoring of daily stress and management practice via soft bioelectronics. Biosens Bioelectron 2021; 173:112764. [PMID: 33190046 PMCID: PMC8093317 DOI: 10.1016/j.bios.2020.112764] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 10/15/2020] [Accepted: 10/23/2020] [Indexed: 12/21/2022]
Abstract
Stress has become a significant factor, directly affecting human health. Due to the numerous sources of stress that are inevitable in daily life, effective management of stress is essential to maintain a healthy life. Recent advancements in wearable devices allow monitoring stress levels via the detection of galvanic skin response on the skin. Some of these devices show the capability of assessing stress relief methods. However, prior works have been limited in a controlled laboratory setting with a short period assessment (<1 h) of stress intervention. The existing systems' main issues include motion artifacts and discomfort caused by rigid and bulky electronics and mandatory device connection on active fingers. Here, we introduce soft, wireless, skin-like electronics (SKINTRONICS) that offers continuous, portable daily stress and management practice monitoring. The ultrathin, lightweight, all-in-one device captures the change of a subject's stress over six continuous hours during everyday activities, including desk work, cleaning, and resting. At the same time, the SKINTRONICS proves that typical stress alleviation methods (mindfulness and meditation) can reduce stress levels, even in the middle of the day, which is supported by statistical analysis. The low-profile, wireless, gel-free device shows enhanced breathability and minimized motion artifacts compared to a commercial stress monitor. Collectively, this study shows the first demonstration of soft, nanomembrane bioelectronics for long-term, continuous assessment of stress and intervention effectiveness throughout daily life.
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Affiliation(s)
- Hojoong Kim
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Department of Intelligent Mechatronics Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Yun-Soung Kim
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Musa Mahmood
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Shinjae Kwon
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Fayron Epps
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, 30322, USA
| | - You Seung Rim
- Department of Intelligent Mechatronics Engineering, Sejong University, Seoul, 05006, Republic of Korea.
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Center for Human-Centric Interfaces and Engineering, Neural Engineering Center, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
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46
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Wu H, Yang G, Zhu K, Liu S, Guo W, Jiang Z, Li Z. Materials, Devices, and Systems of On-Skin Electrodes for Electrophysiological Monitoring and Human-Machine Interfaces. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:2001938. [PMID: 33511003 PMCID: PMC7816724 DOI: 10.1002/advs.202001938] [Citation(s) in RCA: 100] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 09/19/2020] [Indexed: 05/05/2023]
Abstract
On-skin electrodes function as an ideal platform for collecting high-quality electrophysiological (EP) signals due to their unique characteristics, such as stretchability, conformal interfaces with skin, biocompatibility, and wearable comfort. The past decade has witnessed great advancements in performance optimization and function extension of on-skin electrodes. With continuous development and great promise for practical applications, on-skin electrodes are playing an increasingly important role in EP monitoring and human-machine interfaces (HMI). In this review, the latest progress in the development of on-skin electrodes and their integrated system is summarized. Desirable features of on-skin electrodes are briefly discussed from the perspective of performances. Then, recent advances in the development of electrode materials, followed by the analysis of strategies and methods to enhance adhesion and breathability of on-skin electrodes are examined. In addition, representative integrated electrode systems and practical applications of on-skin electrodes in healthcare monitoring and HMI are introduced in detail. It is concluded with the discussion of key challenges and opportunities for on-skin electrodes and their integrated systems.
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Affiliation(s)
- Hao Wu
- Flexible Electronics Research CenterState Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China
| | - Ganguang Yang
- Flexible Electronics Research CenterState Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China
| | - Kanhao Zhu
- Flexible Electronics Research CenterState Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China
| | - Shaoyu Liu
- Flexible Electronics Research CenterState Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China
| | - Wei Guo
- Flexible Electronics Research CenterState Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China
| | - Zhuo Jiang
- Department of Materials ScienceFudan UniversityShanghai200433China
| | - Zhuo Li
- Department of Materials ScienceFudan UniversityShanghai200433China
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Zhang Q, Sun Y, He C, Shi F, Cheng M. Fabrication of 3D Ordered Structures with Multiple Materials via Macroscopic Supramolecular Assembly. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2020; 7:2002025. [PMID: 33304756 PMCID: PMC7709987 DOI: 10.1002/advs.202002025] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/30/2020] [Indexed: 05/05/2023]
Abstract
Integration of diverse materials into 3D ordered structures is urgently required for advanced manufacture owing to increase in demand for high-performance products. Most additive manufacturing techniques mainly focus on simply combining different equipment, while interfacial binding of distinctive materials remains a fundamental problem. Increasing studies on macroscopic supramolecular assembly (MSA) have revealed efficient interfacial interactions based on multivalency of supramolecular interactions facilitated by a "flexible spacing coating." To demonstrate facile fabrication of 3D heterogeneous ordered structures, the combination of MSA and magnetic field-assisted alignment has been developed as a new methodology for in situ integration of a wide range of materials, including elastomer, resin, plastics, metal, and quartz glass, with modulus ranging from tens of MPa to over 70 GPa. Assembly of single material, coassembly of two to four distinctive materials, and 3D alignment of "bridge-like" and "cross-stacked" heterogeneous structures are demonstrated. This methodology has provided a new solution to mild and efficient assembly of multiple materials at the macroscopic scale, which holds promise for advanced fabrication in fields of tissue engineering, electronic devices, and actuators.
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Affiliation(s)
- Qian Zhang
- State Key Laboratory of Chemical Resource Engineering & Beijing Laboratory of Biomedical Materials & Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing100029China
| | - Yingzhi Sun
- State Key Laboratory of Chemical Resource Engineering & Beijing Laboratory of Biomedical Materials & Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing100029China
| | - Chengzhi He
- State Key Laboratory of Chemical Resource Engineering & Beijing Laboratory of Biomedical Materials & Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing100029China
| | - Feng Shi
- State Key Laboratory of Chemical Resource Engineering & Beijing Laboratory of Biomedical Materials & Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing100029China
| | - Mengjiao Cheng
- State Key Laboratory of Chemical Resource Engineering & Beijing Laboratory of Biomedical Materials & Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing100029China
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48
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Qiao Y, Li X, Jian J, Wu Q, Wei Y, Shuai H, Hirtz T, Zhi Y, Deng G, Wang Y, Gou G, Xu J, Cui T, Tian H, Yang Y, Ren TL. Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis. ACS APPLIED MATERIALS & INTERFACES 2020; 12:49945-49956. [PMID: 33090758 DOI: 10.1021/acsami.0c12440] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Current wearable sensors are fabricated with substrates, which limits the comfort, flexibility, stretchability, and induces interface mismatch. In addition, the substrate prevents the evaporation of sweat and is harmful to skin health. In this work, we have enabled the substrate-free laser scribed graphene (SFG) electronic skin (e-skin) with multifunctions. Compared with the e-skin with the substrate, the SFG has good gas permeability, low impedance, and flexibility. Only assisted using water, the SFG can be transferred to almost any objects including silicon and human skin and it can even be suspended. Many through-holes like stomas in leaf can be formed in the SFG, which make it breathable. After designing the pattern, the gauge factor (GF) of graphene electronic skin (GES) can be designed as the strain sensor. Physiological signals such as respiration, human motion, and electrocardiogram (ECG) can be detected. Moreover, the suspended SFG detect vibrations with high sensitivity. Due to the substrate-free structure, the impedance between SFG e-skin and the human body decreases greatly. Finally, an ECG detecting system has been designed based on the GES, which can monitor the body condition in real time. To analyze the ECG signals automatically, a convolutional neural network (CNN) was built and trained successfully. This work has high potential in the field of health telemonitoring.
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Affiliation(s)
- Yancong Qiao
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Xiaoshi Li
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jinming Jian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Qi Wu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yuhong Wei
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Hua Shuai
- Department of Physics, Engineering Physics, The Ohio State University, 191 West Woodruff Avenue, Columbus, Ohio 43210, United States
| | - Thomas Hirtz
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yao Zhi
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Ge Deng
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yunfan Wang
- Institute of Electronics, Tsinghua University, Beijing 100084, China
| | - Guangyang Gou
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jiandong Xu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tianrui Cui
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - He Tian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yi Yang
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tian-Ling Ren
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
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49
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Mahmood M, Kwon S, Berkmen GK, Kim YS, Scorr L, Jinnah HA, Yeo WH. Soft Nanomembrane Sensors and Flexible Hybrid Bioelectronics for Wireless Quantification of Blepharospasm. IEEE Trans Biomed Eng 2020; 67:3094-3100. [PMID: 32091988 PMCID: PMC7604814 DOI: 10.1109/tbme.2020.2975773] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Blepharospasm (BL) is characterized by involuntary closures of the eyelids due to spasms of the orbicularis oculi muscle. The gold standard for clinical evaluation of BL involves visual inspection for manual rating scales. This approach is highly subjective and error prone. Unfortunately, there are currently no simple quantitative systems for accurate and objective diagnostics of BL. Here, we introduce a soft, flexible hybrid bioelectronic system that offers highly conformal, gentle lamination on the skin, while enabling wireless, quantitative detection of electrophysiological signals. Computational and experimental studies of soft materials and flexible mechanics provide a set of key fundamental design factors for a low-profile bioelectronic system. The nanomembrane soft electrodes, mounted around the eyes, are capable of accurately measuring clinical symptoms, including the frequency of blinking, the duration of eye closures during spasms, as well as combinations of blinking and spasms. The use of a deep-learning, convolutional neural network, with the bioelectronics offers objective, real-time classification of key pathological features in BL. The wearable bioelectronics outperform the conventional manual clinical rating, as shown by a pilot study with 13 patients. In vivo demonstration of the bioelectronics with these patients indicates the device as an easy-to-use solution for objective quantification of BL.
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50
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Kwon YT, Norton JJS, Cutrone A, Lim HR, Kwon S, Choi JJ, Kim HS, Jang YC, Wolpaw JR, Yeo WH. Breathable, large-area epidermal electronic systems for recording electromyographic activity during operant conditioning of H-reflex. Biosens Bioelectron 2020; 165:112404. [PMID: 32729524 PMCID: PMC7484316 DOI: 10.1016/j.bios.2020.112404] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/28/2020] [Accepted: 06/20/2020] [Indexed: 10/24/2022]
Abstract
Operant conditioning of Hoffmann's reflex (H-reflex) is a non-invasive and targeted therapeutic intervention for patients with movement disorders following spinal cord injury. The reflex-conditioning protocol uses electromyography (EMG) to measure reflexes from specific muscles elicited using transcutaneous electrical stimulation. Despite recent advances in wearable electronics, existing EMG systems that measure muscle activity for operant conditioning of spinal reflexes still use rigid metal electrodes with conductive gels and aggressive adhesives, while requiring precise positioning to ensure reliability of data across experimental sessions. Here, we present the first large-area epidermal electronic system (L-EES) and demonstrate its use in every step of the reflex-conditioning protocol. The L-EES is a stretchable and breathable composite of nanomembrane electrodes (16 electrodes in a four by four array), elastomer, and fabric. The nanomembrane electrode array enables EMG recording from a large surface area on the skin and the breathable elastomer with fabric is biocompatible and comfortable for patients. We show that L-EES can record direct muscle responses (M-waves) and H-reflexes, both of which are comparable to those recorded using conventional EMG recording systems. In addition, L-EES may improve the reflex-conditioning protocol; it has potential to automatically optimize EMG electrode positioning, which may reduce setup time and error across experimental sessions.
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Affiliation(s)
- Young-Tae Kwon
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - James J S Norton
- National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, 12208, USA; Stratton VA Medical Center, Albany, NY, 12208, USA
| | - Andrew Cutrone
- National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, 12208, USA
| | - Hyo-Ryoung Lim
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Shinjae Kwon
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Jeongmoon J Choi
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Hee Seok Kim
- Department of Mechanical Engineering, University of South Alabama, Mobile, AL, 36608, USA
| | - Young C Jang
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Wallace H. Coulter Department of Biomedical Engineering and Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Jonathan R Wolpaw
- National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, 12208, USA; Stratton VA Medical Center, Albany, NY, 12208, USA
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Wallace H. Coulter Department of Biomedical Engineering and Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Flexible and Wearable Electronics Advanced Research Program, Neural Engineering Center, Institute for Materials, and Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
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