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Zhou W, Yu Y, Xiao P, Deng F, Zhang Y, Chen T. A Suspended, 3D Morphing Sensory System for Robots to Feel and Protect. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2403447. [PMID: 38728424 DOI: 10.1002/adma.202403447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 04/22/2024] [Indexed: 05/12/2024]
Abstract
Artificial sensory systems with synergistic touch and pain perception hold substantial promise for environment interaction and human-robot communication. However, the realization of biological skin-like functional integration of sensors with sensitive touch and pain perception still remains a challenge. Here, a concept is proposed of suspended electronic skins enabling 3D deformation-mechanical contact interactions for achieving synergetic ultrasensitive touch and adjustable pain perception. The suspended sensory system can sensitively capture tiny touch stimuli as low as 0.02 Pa and actively perceive pain response with reliable 5200 cycles via 3D deformation and mechanical contact mechanism, respectively. Based on the touch-pain effect, a visualized feedback demo with miniaturized sensor arrays on artificial fingers is rationally designed to give a pain perception mapping on sharp surfaces. Furthermore, the capability is shown of the suspended electronic skin serving as a safe human-robot communication interface from active and passive view through a feedback control system, demonstrating potential in bionic electronics and intelligent robotics.
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Affiliation(s)
- Wei Zhou
- Key Laboratory of Advanced Marine Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- School of Chemical Sciences, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, China
| | - Yi Yu
- Key Laboratory of Advanced Marine Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- School of Chemical Sciences, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, China
| | - Peng Xiao
- Key Laboratory of Advanced Marine Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- School of Chemical Sciences, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, China
| | - Feng Deng
- Key Laboratory of Advanced Marine Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- School of Chemical Sciences, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, China
| | - Yi Zhang
- Key Laboratory of Advanced Marine Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- School of Chemical Sciences, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, China
| | - Tao Chen
- Key Laboratory of Advanced Marine Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- School of Chemical Sciences, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, China
- College of Material Chemistry and Chemical Engineering, Key Laboratory of Organosilicon Chemistry and Material Technology, Ministry of Education, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China
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2
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Suo J, Liu Y, Wang J, Chen M, Wang K, Yang X, Yao K, Roy VAL, Yu X, Daoud WA, Liu N, Wang J, Wang Z, Li WJ. AI-Enabled Soft Sensing Array for Simultaneous Detection of Muscle Deformation and Mechanomyography for Metaverse Somatosensory Interaction. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2305025. [PMID: 38376001 DOI: 10.1002/advs.202305025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/25/2023] [Indexed: 02/21/2024]
Abstract
Motion recognition (MR)-based somatosensory interaction technology, which interprets user movements as input instructions, presents a natural approach for promoting human-computer interaction, a critical element for advancing metaverse applications. Herein, this work introduces a non-intrusive muscle-sensing wearable device, that in conjunction with machine learning, enables motion-control-based somatosensory interaction with metaverse avatars. To facilitate MR, the proposed device simultaneously detects muscle mechanical activities, including dynamic muscle shape changes and vibrational mechanomyogram signals, utilizing a flexible 16-channel pressure sensor array (weighing ≈0.38 g). Leveraging the rich information from multiple channels, a recognition accuracy of ≈96.06% is achieved by classifying ten lower-limb motions executed by ten human subjects. In addition, this work demonstrates the practical application of muscle-sensing-based somatosensory interaction, using the proposed wearable device, for enabling the real-time control of avatars in a virtual space. This study provides an alternative approach to traditional rigid inertial measurement units and electromyography-based methods for achieving accurate human motion capture, which can further broaden the applications of motion-interactive wearable devices for the coming metaverse age.
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Affiliation(s)
- Jiao Suo
- Dept. of Mechanical Engineering, City University of Hong Kong, Hong Kong, 999077, China
| | - Yifan Liu
- Dept. of Electrical and Computer Engineering, Michigan State University, MI, 48840, USA
| | - Jianfei Wang
- The Int. Research Centre for Nano Handling and Manufacturing of China, Changchun University of Science and Technology, Changchun, 130022, China
| | - Meng Chen
- Dept. of Mechanical Engineering, City University of Hong Kong, Hong Kong, 999077, China
| | - Keer Wang
- Dept. of Mechanical Engineering, City University of Hong Kong, Hong Kong, 999077, China
| | - Xiaomeng Yang
- Dept. of Mechanical Engineering, City University of Hong Kong, Hong Kong, 999077, China
| | - Kuanming Yao
- Dept. of Biomedical Engineering, City University of Hong Kong, Hong Kong, 999077, China
| | - Vellaisamy A L Roy
- James Watt School of Engineering, University of Glasgow, Scotland, G12 8QQ, UK
| | - Xinge Yu
- Dept. of Biomedical Engineering, City University of Hong Kong, Hong Kong, 999077, China
| | - Walid A Daoud
- Dept. of Mechanical Engineering, City University of Hong Kong, Hong Kong, 999077, China
| | - Na Liu
- Sch. of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China
| | - Jianping Wang
- Dept. of Computer Science, City University of Hong Kong, Hong Kong, 999077, China
| | - Zuobin Wang
- The Int. Research Centre for Nano Handling and Manufacturing of China, Changchun University of Science and Technology, Changchun, 130022, China
| | - Wen Jung Li
- Dept. of Mechanical Engineering, City University of Hong Kong, Hong Kong, 999077, China
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Zhang T, Zhu J, Wang Q, Xie M, Meng K, Mao L, Yang L, Pan T, Gao M, Yao G, Lin Y. Flexible Antibacterial Respiratory Monitoring Sensor Based on Controllable Au-Modified Surface of Highly {001} Preferred Anatase Titanium Dioxide Thin Film. ACS Biomater Sci Eng 2024; 10:1722-1733. [PMID: 38373308 DOI: 10.1021/acsbiomaterials.3c01164] [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: 02/21/2024]
Abstract
Respiratory signals are critical clinical diagnostic criteria for respiratory diseases and health conditions, and respiratory sensors play a crucial role in achieving the desired respiratory monitoring effect. High sensitivity to a single factor can improve the reliability of respiratory monitoring, and maintaining the hygiene of the sensors is also important for daily health monitoring. Herein, we propose a flexible Au-modified anatase titanium dioxide resistive respiratory sensor, which can be mechanically compliantly attached to curved surfaces for respiratory monitoring in different modalities (i.e., respiratory intensity, frequency, and rate). The uniform and preferentially oriented anatase titanium dioxide films gained by the polymer-assisted deposition technique can be fabricated on flexible substrates through a liquid-assisted transferring process. The Au modification can enhance surface plasmon resonance to facilitate the photocatalytic activity of titanium dioxide, and the optimized distribution of Au on the surface of titanium dioxide film made the sensor have an excellent antibacterial effect. The uniquely designed encapsulation can effectively control the contact between the surface of titanium dioxide films and electrodes, allowing the flexible sensor to exhibit fast response time (0.71 s) and recovery time (1.06 s) to respiratory as well as insensitivity or low sensitivity to other factors (i.e., gas composition, humidity, temperature, stress, and strain). This work provided an effective strategy for flexible wearable respiratory sensors and has great potential in daily respiratory monitoring for health management and pandemic control.
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Affiliation(s)
- Tianyao Zhang
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, Zhejiang 324000, China
| | - Jia Zhu
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Qian Wang
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Maowen Xie
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Ke Meng
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Longbiao Mao
- Department of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Li Yang
- Department of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Taisong Pan
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Min Gao
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Guang Yao
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
- Medico-Engineering Cooperation on Applied Medicine Research Center, University of Electronics Science and Technology of China, Chengdu 610054, China
| | - Yuan Lin
- School of Material and Energy, University of Electronic Science and Technology of China, Chengdu 610054, China
- Medico-Engineering Cooperation on Applied Medicine Research Center, University of Electronics Science and Technology of China, Chengdu 610054, China
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Zhao T, Xiao X, Wu Y, Ma J, Li Y, Lu C, Shokoohi C, Xu Y, Zhang X, Zhang Y, Ge G, Zhang G, Chen J, Zeng Y. Tracing the Flu Symptom Progression via a Smart Face Mask. NANO LETTERS 2023; 23:8960-8969. [PMID: 37750614 DOI: 10.1021/acs.nanolett.3c02492] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
Respiration and body temperature are largely influenced by the highly contagious influenza virus, which poses persistent global public health challenges. Here, we present a wireless all-in-one sensory face mask (WISE mask) made of ultrasensitive fibrous temperature sensors. The WISE mask shows exceptional thermosensitivity, excellent breathability, and wearing comfort. It offers highly sensitive body temperature monitoring and respiratory detection capabilities. Capitalizing on the advances in the Internet of Things and artificial intelligence, the WISE mask is further demonstrated by customized flexible circuitry, deep learning algorithms, and a user-friendly interface to continuously recognize the abnormalities of both the respiration and body temperature. The WISE mask represents a compelling approach to tracing flu symptom progression in a cost-effective and convenient manner, serving as a powerful solution for personalized health monitoring and point-of-care systems in the face of ongoing influenza-related public health concerns.
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Affiliation(s)
- Tienan Zhao
- College of Textiles, Donghua University, Shanghai 201620, China
| | - Xiao Xiao
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Yuchen Wu
- College of Information Science and Technology, Donghua University, Shanghai 201620, China
| | - Jiajia Ma
- College of Textiles, Donghua University, Shanghai 201620, China
| | - Ying Li
- College of Textiles, Donghua University, Shanghai 201620, China
| | - Chengyue Lu
- Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Cyrus Shokoohi
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Yuanqiang Xu
- College of Textiles, Donghua University, Shanghai 201620, China
| | - Xiaomin Zhang
- College of Textiles, Donghua University, Shanghai 201620, China
| | - Yuze Zhang
- College of Textiles, Donghua University, Shanghai 201620, China
| | - Gang Ge
- Department of Electrical and Computer Engineering, National University of Singapore,117583, Singapore
| | - Guanglin Zhang
- College of Information Science and Technology, Donghua University, Shanghai 201620, China
| | - Jun Chen
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Yongchun Zeng
- College of Textiles, Donghua University, Shanghai 201620, China
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Hatta MHM, Matmin J, Malek NANN, Kamisan FH, Badruzzaman A, Batumalaie K, Ling Lee S, Abdul Wahab R. COVID‐19: Prevention, Detection, and Treatment by Using Carbon Nanotubes‐Based Materials. ChemistrySelect 2023. [DOI: 10.1002/slct.202204615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Affiliation(s)
- Mohd Hayrie Mohd Hatta
- Centre for Research and Development Asia Metropolitan University 81750 Johor Bahru Johor Malaysia
| | - Juan Matmin
- Department of Chemistry Faculty of Science Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia
- Centre for Sustainable Nanomaterials Ibnu Sina Institute for Scientific and Industrial Research Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia
| | - Nik Ahmad Nizam Nik Malek
- Centre for Sustainable Nanomaterials Ibnu Sina Institute for Scientific and Industrial Research Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia
- Department of Biosciences, Faculty of Science Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia
| | - Farah Hidayah Kamisan
- Department of Biomedical Sciences Faculty of Health Sciences Asia Metropolitan University 81750 Johor Bahru Johor Malaysia
| | - Aishah Badruzzaman
- Centre for Foundation, Language and General Studies Asia Metropolitan University 81750 Johor Bahru Johor Malaysia
| | - Kalaivani Batumalaie
- Department of Biomedical Sciences Faculty of Health Sciences Asia Metropolitan University 81750 Johor Bahru Johor Malaysia
| | - Siew Ling Lee
- Department of Chemistry Faculty of Science Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia
- Centre for Sustainable Nanomaterials Ibnu Sina Institute for Scientific and Industrial Research Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia
| | - Roswanira Abdul Wahab
- Department of Chemistry Faculty of Science Universiti Teknologi Malaysia 81310 UTM Johor Bahru Johor Malaysia
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Li J, Yin J, Ramakrishna S, Ji D. Smart Mask as Wearable for Post-Pandemic Personal Healthcare. BIOSENSORS 2023; 13:205. [PMID: 36831971 PMCID: PMC9953568 DOI: 10.3390/bios13020205] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 01/26/2023] [Accepted: 01/27/2023] [Indexed: 06/18/2023]
Abstract
A mask serves as a simple external barrier that protects humans from infectious particles from poor air conditions in the surrounding environment. As an important personal protective equipment (PPE) to protect our respiratory system, masks are able not only to filter pathogens and dust particles but also to sense, reflect or even respond to environmental conditions. This smartness is of particular interest among academia and industries due to its potential in disease detection, health monitoring and caring aspects. In this review, we provide an overlook of the current air filtration strategies used in masks, from structural designs to integrated functional modules that empower the mask's ability to sense and transfer physiological or environmental information to become smart. Specifically, we discussed recent developments in masks designed to detect macroscopic physiological signals from the wearer and mask-based disease diagnoses, such as COVID-19. Further, we propose the concept of next-generation smart masks and the requirements from material selection and function design perspectives that enable masks to interact and play crucial roles in health-caring wearables.
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Affiliation(s)
- Jingcheng Li
- Centre for Nanotechnology and Sustainability, Department of Mechanical Engineering, National University of Singapore, Singapore 117081, Singapore
| | - Jing Yin
- National Engineering Laboratory for Modern Silk, College of Textile and Clothing Engineering, Soochow University, Suzhou 215021, China
| | - Seeram Ramakrishna
- Centre for Nanotechnology and Sustainability, Department of Mechanical Engineering, National University of Singapore, Singapore 117081, Singapore
| | - Dongxiao Ji
- College of Textiles, Donghua University, Shanghai 201620, China
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