1
|
Sunnucks EJ, Thurn B, Brown AO, Zhang W, Liu T, Forbes SL, Su S, Ueland M. Performance of a Novel Electronic Nose for the Detection of Volatile Organic Compounds Relating to Starvation or Human Decomposition Post-Mass Disaster. SENSORS (BASEL, SWITZERLAND) 2024; 24:5918. [PMID: 39338662 PMCID: PMC11435962 DOI: 10.3390/s24185918] [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: 07/02/2024] [Revised: 09/06/2024] [Accepted: 09/10/2024] [Indexed: 09/30/2024]
Abstract
There has been a recent increase in the frequency of mass disaster events. Following these events, the rapid location of victims is paramount. Currently, the most reliable search method is scent detection dogs, which use their sense of smell to locate victims accurately and efficiently. Despite their efficacy, they have limited working times, can give false positive responses, and involve high costs. Therefore, alternative methods for detecting volatile compounds are needed, such as using electronic noses (e-noses). An e-nose named the 'NOS.E' was developed and has been used successfully to detect VOCs released from human remains in an open-air environment. However, the system's full capabilities are currently unknown, and therefore, this work aimed to evaluate the NOS.E to determine the efficacy of detection and expected sensor response. This was achieved using analytical standards representative of known human ante-mortem and decomposition VOCs. Standards were air diluted in Tedlar gas sampling bags and sampled using the NOS.E. This study concluded that the e-nose could detect and differentiate a range of VOCs prevalent in ante-mortem and decomposition VOC profiles, with an average LOD of 7.9 ppm, across a range of different chemical classes. The NOS.E was then utilized in a simulated mass disaster scenario using donated human cadavers, where the system showed a significant difference between the known human donor and control samples from day 3 post-mortem. Overall, the NOS.E was advantageous: the system had low detection limits while offering portability, shorter sampling times, and lower costs than dogs and benchtop analytical instruments.
Collapse
Affiliation(s)
- Emily J Sunnucks
- Centre for Forensic Sciences, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Bridget Thurn
- Centre for Forensic Sciences, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
- Hyphenated Mass Spectrometry Laboratory, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Amber O Brown
- Centre for Forensic Sciences, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Wentian Zhang
- Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia
- College of Artificial Intelligence and Big Data for Medical Sciences, Shandong First Medical University, Jinan 250117, China
| | - Taoping Liu
- Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an 710071, China
| | - Shari L Forbes
- Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, Canada
| | - Steven Su
- Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia
- College of Artificial Intelligence and Big Data for Medical Sciences, Shandong First Medical University, Jinan 250117, China
| | - Maiken Ueland
- Centre for Forensic Sciences, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
- Hyphenated Mass Spectrometry Laboratory, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
| |
Collapse
|
2
|
Chen G, Zhang Y, Li S, Zheng J, Yang H, Ren J, Zhu C, Zhou Y, Chen Y, Fu J. Flexible Artificial Tactility with Excellent Robustness and Temperature Tolerance Based on Organohydrogel Sensor Array for Robot Motion Detection and Object Shape Recognition. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2408193. [PMID: 39255513 DOI: 10.1002/adma.202408193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Revised: 08/09/2024] [Indexed: 09/12/2024]
Abstract
Hydrogel-based flexible artificial tactility is equipped to intelligent robots to mimic human mechanosensory perception. However, it remains a great challenge for hydrogel sensors to maintain flexibility and sensory performances during cyclic loadings at high or low temperatures due to water loss or freezing. Here, a flexible robot tactility is developed with high robustness based on organohydrogel sensor arrays with negligent hysteresis and temperature tolerance. Conductive polyaniline chains are interpenetrated through a poly(acrylamide-co-acrylic acid) network with glycerin/water mixture with interchain electrostatic interactions and hydrogen bonds, yielding a high dissipated energy of 1.58 MJ m-3, and ultralow hysteresis during 1000 cyclic loadings. Moreover, the binary solvent provides the gels with outstanding tolerance from -100 to 60 °C and the organohydrogel sensors remain flexible, fatigue resistant, conductive (0.27 S m-1), highly strain sensitive (GF of 3.88) and pressure sensitive (35.8 MPa-1). The organohydrogel sensor arrays are equipped on manipulator finger dorsa and pads to simultaneously monitor the finger motions and detect the pressure distribution exerted by grasped objects. A machine learning model is used to train the system to recognize the shape of grasped objects with 100% accuracy. The flexible robot tactility based on organohydrogels is promising for novel intelligent robots.
Collapse
Affiliation(s)
- Guoqi Chen
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Yunting Zhang
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Shengnan Li
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Jingxia Zheng
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Hailong Yang
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Jiayuan Ren
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Chanjie Zhu
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Yecheng Zhou
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Yongming Chen
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Jun Fu
- Guangdong Engineering Technology Research Centre for Functional Biomaterials, Key Laboratory of Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| |
Collapse
|
3
|
Tang H, Li Y, Liao S, Liu H, Qiao Y, Zhou J. Multifunctional Conductive Hydrogel Interface for Bioelectronic Recording and Stimulation. Adv Healthc Mater 2024; 13:e2400562. [PMID: 38773929 DOI: 10.1002/adhm.202400562] [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: 02/14/2024] [Revised: 05/11/2024] [Indexed: 05/24/2024]
Abstract
The past few decades have witnessed the rapid advancement and broad applications of flexible bioelectronics, in wearable and implantable electronics, brain-computer interfaces, neural science and technology, clinical diagnosis, treatment, etc. It is noteworthy that soft and elastic conductive hydrogels, owing to their multiple similarities with biological tissues in terms of mechanics, electronics, water-rich, and biological functions, have successfully bridged the gap between rigid electronics and soft biology. Multifunctional hydrogel bioelectronics, emerging as a new generation of promising material candidates, have authentically established highly compatible and reliable, high-quality bioelectronic interfaces, particularly in bioelectronic recording and stimulation. This review summarizes the material basis and design principles involved in constructing hydrogel bioelectronic interfaces, and systematically discusses the fundamental mechanism and unique advantages in bioelectrical interfacing with the biological surface. Furthermore, an overview of the state-of-the-art manufacturing strategies for hydrogel bioelectronic interfaces with enhanced biocompatibility and integration with the biological system is presented. This review finally exemplifies the unprecedented advancement and impetus toward bioelectronic recording and stimulation, especially in implantable and integrated hydrogel bioelectronic systems, and concludes with a perspective expectation for hydrogel bioelectronics in clinical and biomedical applications.
Collapse
Affiliation(s)
- Hao Tang
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, P. R. China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, P. R. China
| | - Yuanfang Li
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, P. R. China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, P. R. China
| | - Shufei Liao
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, P. R. China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, P. R. China
| | - Houfang Liu
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Yancong Qiao
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, P. R. China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, P. R. China
| | - Jianhua Zhou
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, P. R. China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510275, P. R. China
| |
Collapse
|
4
|
Liu Y, Peng N, Kang J, Onodera T, Yatabe R. Identification of Beef Odors under Different Storage Day and Processing Temperature Conditions Using an Odor Sensing System. SENSORS (BASEL, SWITZERLAND) 2024; 24:5590. [PMID: 39275501 PMCID: PMC11397898 DOI: 10.3390/s24175590] [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: 07/24/2024] [Revised: 08/20/2024] [Accepted: 08/27/2024] [Indexed: 09/16/2024]
Abstract
This study used an odor sensing system with a 16-channel electrochemical sensor array to measure beef odors, aiming to distinguish odors under different storage days and processing temperatures for quality monitoring. Six storage days ranged from purchase (D0) to eight days (D8), with three temperature conditions: no heat (RT), boiling (100 °C), and frying (180 °C). Gas chromatography-mass spectrometry (GC-MS) analysis showed that odorants in the beef varied under different conditions. Compounds like acetoin and 1-hexanol changed significantly with the storage days, while pyrazines and furans were more detectable at higher temperatures. The odor sensing system data were visualized using principal component analysis (PCA) and uniform manifold approximation and projection (UMAP). PCA and unsupervised UMAP clustered beef odors by storage days but struggled with the processing temperatures. Supervised UMAP accurately clustered different temperatures and dates. Machine learning analysis using six classifiers, including support vector machine, achieved 57% accuracy for PCA-reduced data, while unsupervised UMAP reached 49.1% accuracy. Supervised UMAP significantly enhanced the classification accuracy, achieving over 99.5% with the dimensionality reduced to three or above. Results suggest that the odor sensing system can sufficiently enhance non-destructive beef quality and safety monitoring. This research advances electronic nose applications and explores data downscaling techniques, providing valuable insights for future studies.
Collapse
Affiliation(s)
- Yuanchang Liu
- Research and Development Center for Five-Sense Devices, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
| | - Nan Peng
- Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
| | - Jinlong Kang
- Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
| | - Takeshi Onodera
- Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
| | - Rui Yatabe
- Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
| |
Collapse
|
5
|
Dong L, Xue B, Wei G, Yuan S, Chen M, Liu Y, Su Y, Niu Y, Xu B, Wang P. Highly Promising 2D/1D BP-C/CNT Bionic Opto-Olfactory Co-Sensory Artificial Synapses for Multisensory Integration. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2403665. [PMID: 38828870 PMCID: PMC11304314 DOI: 10.1002/advs.202403665] [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: 04/08/2024] [Revised: 05/08/2024] [Indexed: 06/05/2024]
Abstract
The development of high-performance artificial synaptic neuromorphic devices poses a significant challenge in the creation of biomimetic sensing neural systems that seamlessly integrate both sensory and computational functionalities. In pursuit of this objective, promising bionic opto-olfactory co-sensory artificial synapse devices are constructed utilizing the BP-C/CNT (2D/1D) hybrid filter membrane as the resistive layer. Experimental results demonstrated that the devices seamlessly integrated the light modulation, gas detection, and biological synaptic functions into a single device while addressing the challenge with separating artificial synaptic devices from sensors. These devices offered the following advantages: 1) Simulating visual synapses, they can effectively replicate fundamental synaptic functions under both electrical and optical stimulation. 2) By emulating olfactory synapse responses to specific gases, they can achieve ultra-low detection limits and rapid identification of ethanol and acetone gases. 3) They enable photo-olfactory co-sensing simulations that mimic synaptic function under light-modulated pulse conditions in distinct gas environments, facilitating the study of synaptic learning rules and Pavlovian responses. This work provides a pioneering approach for exploring highly stable 2D BP-based optoelectronics and advancing the development of biomimetic neural systems.
Collapse
Affiliation(s)
- Liyan Dong
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| | - Baojing Xue
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| | - Guodong Wei
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
- Shanxi‐Zheda Institute of Advanced Materials and Chemical EngineeringTaiyuan030024P. R. China
| | - Shuai Yuan
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| | - Mi Chen
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| | - Yue Liu
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| | - Ying Su
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| | - Yong Niu
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| | - Bingshe Xu
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
- Shanxi‐Zheda Institute of Advanced Materials and Chemical EngineeringTaiyuan030024P. R. China
| | - Pan Wang
- Xi 'an Key Laboratory of Compound Semiconductor Materials and DevicesSchool of Physics & Information ScienceShaanxi University of Science and TechnologyXi'an710021P. R. China
| |
Collapse
|
6
|
Liang Y, Wu S, Lin L, Jia P, Zhong Z. Solvent-assisted strategy for the design of multifunctional and ultrafast healable eutectogels. POLYMER 2024; 308:127392. [DOI: 10.1016/j.polymer.2024.127392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2024]
|
7
|
Borowik P, Tkaczyk M, Pluta P, Okorski A, Stocki M, Tarakowski R, Oszako T. Distinguishing between Wheat Grains Infested by Four Fusarium Species by Measuring with a Low-Cost Electronic Nose. SENSORS (BASEL, SWITZERLAND) 2024; 24:4312. [PMID: 39001090 PMCID: PMC11244303 DOI: 10.3390/s24134312] [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: 06/07/2024] [Revised: 06/26/2024] [Accepted: 07/01/2024] [Indexed: 07/16/2024]
Abstract
An electronic device based on the detection of volatile substances was developed in response to the need to distinguish between fungal infestations in food and was applied to wheat grains. The most common pathogens belong to the fungi of the genus Fusarium: F. avenaceum, F. langsethiae, F. poae, and F. sporotrichioides. The electronic nose prototype is a low-cost device based on commercially available TGS series sensors from Figaro Corp. Two types of gas sensors that respond to the perturbation are used to collect signals useful for discriminating between the samples under study. First, an electronic nose detects the transient response of the sensors to a change in operating conditions from clean air to the presence of the gas being measured. A simple gas chamber was used to create a sudden change in gas composition near the sensors. An inexpensive pneumatic system consisting of a pump and a carbon filter was used to supply the system with clean air. It was also used to clean the sensors between measurement cycles. The second function of the electronic nose is to detect the response of the sensor to temperature disturbances of the sensor heater in the presence of the gas to be measured. It has been shown that features extracted from the transient response of the sensor to perturbations by modulating the temperature of the sensor heater resulted in better classification performance than when the machine learning model was built from features extracted from the response of the sensor in the gas adsorption phase. By combining features from both phases of the sensor response, a further improvement in classification performance was achieved. The E-nose enabled the differentiation of F. poae from the other fungal species tested with excellent performance. The overall classification rate using the Support Vector Machine model reached 70 per cent between the four fungal categories tested.
Collapse
Affiliation(s)
- Piotr Borowik
- Faculty of Physics, Warsaw University of Technology, Ul. Koszykowa 75, 00-662 Warszawa, Poland;
| | - Miłosz Tkaczyk
- Forest Protection Department, Forest Research Institute, Ul. Braci Leśnej 3, 05-090 Sękocin Stary, Poland; (M.T.); (T.O.)
| | - Przemysław Pluta
- Forestry Students’ Scientific Association, Forest Department, Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warszawa, Poland;
| | - Adam Okorski
- Department of Entomology, Phytopathology and Molecular Diagnostics, Faculty of Agriculture and Forestry, University of Warmia and Mazury in Olsztyn, Pl. Łódzki 5, 10-727 Olsztyn, Poland;
| | - Marcin Stocki
- Institute of Forest Sciences, Faculty of Civil Engineering and Environmental Sciences, Białystok University of Technology, Ul. Wiejska 45E, 15-351 Białystok, Poland;
| | - Rafał Tarakowski
- Faculty of Physics, Warsaw University of Technology, Ul. Koszykowa 75, 00-662 Warszawa, Poland;
| | - Tomasz Oszako
- Forest Protection Department, Forest Research Institute, Ul. Braci Leśnej 3, 05-090 Sękocin Stary, Poland; (M.T.); (T.O.)
| |
Collapse
|
8
|
Xue J, Liu D, Li D, Hong T, Li C, Zhu Z, Sun Y, Gao X, Guo L, Shen X, Ma P, Zheng Q. New Carbon Materials for Multifunctional Soft Electronics. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2312596. [PMID: 38490737 DOI: 10.1002/adma.202312596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/19/2024] [Indexed: 03/17/2024]
Abstract
Soft electronics are garnering significant attention due to their wide-ranging applications in artificial skin, health monitoring, human-machine interaction, artificial intelligence, and the Internet of Things. Various soft physical sensors such as mechanical sensors, temperature sensors, and humidity sensors are the fundamental building blocks for soft electronics. While the fast growth and widespread utilization of electronic devices have elevated life quality, the consequential electromagnetic interference (EMI) and radiation pose potential threats to device precision and human health. Another substantial concern pertains to overheating issues that occur during prolonged operation. Therefore, the design of multifunctional soft electronics exhibiting excellent capabilities in sensing, EMI shielding, and thermal management is of paramount importance. Because of the prominent advantages in chemical stability, electrical and thermal conductivity, and easy functionalization, new carbon materials including carbon nanotubes, graphene and its derivatives, graphdiyne, and sustainable natural-biomass-derived carbon are particularly promising candidates for multifunctional soft electronics. This review summarizes the latest advancements in multifunctional soft electronics based on new carbon materials across a range of performance aspects, mainly focusing on the structure or composite design, and fabrication method on the physical signals monitoring, EMI shielding, and thermal management. Furthermore, the device integration strategies and corresponding intriguing applications are highlighted. Finally, this review presents prospects aimed at overcoming current barriers and advancing the development of state-of-the-art multifunctional soft electronics.
Collapse
Affiliation(s)
- Jie Xue
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Dan Liu
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Da Li
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Tianzeng Hong
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Chuanbing Li
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Zifu Zhu
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Yuxuan Sun
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Xiaobo Gao
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Lei Guo
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| | - Xi Shen
- Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, China
- The Research Institute for Sports Science and Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, China
| | - Pengcheng Ma
- Laboratory of Environmental Science and Technology, The Xinjiang Technical Institute of Physics and Chemistry, Key Laboratory of Functional Materials and Devices for Special Environments, Chinese Academy of Sciences, Urumqi, 830011, China
| | - Qingbin Zheng
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China
| |
Collapse
|
9
|
Chung KY, Xu B, Tan D, Yang Q, Li Z, Fu H. Naturally Crosslinked Biocompatible Carbonaceous Liquid Metal Aqueous Ink Printing Wearable Electronics for Multi-Sensing and Energy Harvesting. NANO-MICRO LETTERS 2024; 16:149. [PMID: 38466478 DOI: 10.1007/s40820-024-01362-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/19/2024] [Indexed: 03/13/2024]
Abstract
Achieving flexible electronics with comfort and durability comparable to traditional textiles is one of the ultimate pursuits of smart wearables. Ink printing is desirable for e-textile development using a simple and inexpensive process. However, fabricating high-performance atop textiles with good dispersity, stability, biocompatibility, and wearability for high-resolution, large-scale manufacturing, and practical applications has remained challenging. Here, water-based multi-walled carbon nanotubes (MWCNTs)-decorated liquid metal (LM) inks are proposed with carbonaceous gallium-indium micro-nanostructure. With the assistance of biopolymers, the sodium alginate-encapsulated LM droplets contain high carboxyl groups which non-covalently crosslink with silk sericin-mediated MWCNTs. E-textile can be prepared subsequently via printing technique and natural waterproof triboelectric coating, enabling good flexibility, hydrophilicity, breathability, wearability, biocompatibility, conductivity, stability, and excellent versatility, without any artificial chemicals. The obtained e-textile can be used in various applications with designable patterns and circuits. Multi-sensing applications of recognizing complex human motions, breathing, phonation, and pressure distribution are demonstrated with repeatable and reliable signals. Self-powered and energy-harvesting capabilities are also presented by driving electronic devices and lighting LEDs. As proof of concept, this work provides new opportunities in a scalable and sustainable way to develop novel wearable electronics and smart clothing for future commercial applications.
Collapse
Affiliation(s)
- King Yan Chung
- Nanotechnology Center, School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong, 999077, People's Republic of China
| | - Bingang Xu
- Nanotechnology Center, School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong, 999077, People's Republic of China.
| | - Di Tan
- Nanotechnology Center, School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong, 999077, People's Republic of China
| | - Qingjun Yang
- Nanotechnology Center, School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong, 999077, People's Republic of China
| | - Zihua Li
- Nanotechnology Center, School of Fashion and Textiles, The Hong Kong Polytechnic University, Hong Kong, 999077, People's Republic of China
| | - Hong Fu
- Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong, People's Republic of China
| |
Collapse
|
10
|
Xiang Y, Shi K, Li Y, Xue J, Tong Z, Li H, Li Z, Teng C, Fang J, Hu N. Active Micro-Nano-Collaborative Bioelectronic Device for Advanced Electrophysiological Recording. NANO-MICRO LETTERS 2024; 16:132. [PMID: 38411852 PMCID: PMC10899154 DOI: 10.1007/s40820-024-01336-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 12/28/2023] [Indexed: 02/28/2024]
Abstract
The development of precise and sensitive electrophysiological recording platforms holds the utmost importance for research in the fields of cardiology and neuroscience. In recent years, active micro/nano-bioelectronic devices have undergone significant advancements, thereby facilitating the study of electrophysiology. The distinctive configuration and exceptional functionality of these active micro-nano-collaborative bioelectronic devices offer the potential for the recording of high-fidelity action potential signals on a large scale. In this paper, we review three-dimensional active nano-transistors and planar active micro-transistors in terms of their applications in electro-excitable cells, focusing on the evaluation of the effects of active micro/nano-bioelectronic devices on electrophysiological signals. Looking forward to the possibilities, challenges, and wide prospects of active micro-nano-devices, we expect to advance their progress to satisfy the demands of theoretical investigations and medical implementations within the domains of cardiology and neuroscience research.
Collapse
Affiliation(s)
- Yuting Xiang
- Department of Chemistry, Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, People's Republic of China
- Department of Obstetrics and Gynecology, The Tenth Affiliated Hospital, Southern Medical University, Dongguan, 523059, People's Republic of China
- Dongguan Key Laboratory of Major Diseases in Obstetrics and Gynecology, Dongguan, 523059, People's Republic of China
| | - Keda Shi
- Department of Lung Transplantation and General Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People's Republic of China
| | - Ying Li
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, People's Republic of China
| | - Jiajin Xue
- General Surgery Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children's Health, Hangzhou, 310052, People's Republic of China
| | - Zhicheng Tong
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China
| | - Huiming Li
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China
| | - Zhongjun Li
- Department of Obstetrics and Gynecology, The Tenth Affiliated Hospital, Southern Medical University, Dongguan, 523059, People's Republic of China.
- Dongguan Key Laboratory of Major Diseases in Obstetrics and Gynecology, Dongguan, 523059, People's Republic of China.
| | - Chong Teng
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China.
| | - Jiaru Fang
- School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China.
| | - Ning Hu
- Department of Chemistry, Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, People's Republic of China.
- General Surgery Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children's Health, Hangzhou, 310052, People's Republic of China.
| |
Collapse
|
11
|
Fu J, Deng Z, Liu C, Liu C, Luo J, Wu J, Peng S, Song L, Li X, Peng M, Liu H, Zhou J, Qiao Y. Intelligent, Flexible Artificial Throats with Sound Emitting, Detecting, and Recognizing Abilities. SENSORS (BASEL, SWITZERLAND) 2024; 24:1493. [PMID: 38475029 DOI: 10.3390/s24051493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/22/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024]
Abstract
In recent years, there has been a notable rise in the number of patients afflicted with laryngeal diseases, including cancer, trauma, and other ailments leading to voice loss. Currently, the market is witnessing a pressing demand for medical and healthcare products designed to assist individuals with voice defects, prompting the invention of the artificial throat (AT). This user-friendly device eliminates the need for complex procedures like phonation reconstruction surgery. Therefore, in this review, we will initially give a careful introduction to the intelligent AT, which can act not only as a sound sensor but also as a thin-film sound emitter. Then, the sensing principle to detect sound will be discussed carefully, including capacitive, piezoelectric, electromagnetic, and piezoresistive components employed in the realm of sound sensing. Following this, the development of thermoacoustic theory and different materials made of sound emitters will also be analyzed. After that, various algorithms utilized by the intelligent AT for speech pattern recognition will be reviewed, including some classical algorithms and neural network algorithms. Finally, the outlook, challenge, and conclusion of the intelligent AT will be stated. The intelligent AT presents clear advantages for patients with voice impairments, demonstrating significant social values.
Collapse
Affiliation(s)
- Junxin Fu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Zhikang Deng
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Chang Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Chuting Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Jinan Luo
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Jingzhi Wu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Shiqi Peng
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Lei Song
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Xinyi Li
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Minli Peng
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Houfang Liu
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Jianhua Zhou
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| | - Yancong Qiao
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
| |
Collapse
|
12
|
Zhou H, Li S, Ang KW, Zhang YW. Recent Advances in In-Memory Computing: Exploring Memristor and Memtransistor Arrays with 2D Materials. NANO-MICRO LETTERS 2024; 16:121. [PMID: 38372805 PMCID: PMC10876512 DOI: 10.1007/s40820-024-01335-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 12/25/2023] [Indexed: 02/20/2024]
Abstract
The conventional computing architecture faces substantial challenges, including high latency and energy consumption between memory and processing units. In response, in-memory computing has emerged as a promising alternative architecture, enabling computing operations within memory arrays to overcome these limitations. Memristive devices have gained significant attention as key components for in-memory computing due to their high-density arrays, rapid response times, and ability to emulate biological synapses. Among these devices, two-dimensional (2D) material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing, thanks to their exceptional performance driven by the unique properties of 2D materials, such as layered structures, mechanical flexibility, and the capability to form heterojunctions. This review delves into the state-of-the-art research on 2D material-based memristive arrays, encompassing critical aspects such as material selection, device performance metrics, array structures, and potential applications. Furthermore, it provides a comprehensive overview of the current challenges and limitations associated with these arrays, along with potential solutions. The primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing, leveraging the potential of 2D material-based memristive devices.
Collapse
Affiliation(s)
- Hangbo Zhou
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore
| | - Sifan Li
- Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117583, Republic of Singapore
| | - Kah-Wee Ang
- Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117583, Republic of Singapore.
- Institute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Singapore, 138634, Republic of Singapore.
| | - Yong-Wei Zhang
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore.
| |
Collapse
|
13
|
Ma H, Fang H, Xie X, Liu Y, Tian H, Chai Y. Optoelectronic Synapses Based on MXene/Violet Phosphorus van der Waals Heterojunctions for Visual-Olfactory Crossmodal Perception. NANO-MICRO LETTERS 2024; 16:104. [PMID: 38300424 PMCID: PMC10834395 DOI: 10.1007/s40820-024-01330-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/11/2023] [Indexed: 02/02/2024]
Abstract
The crossmodal interaction of different senses, which is an important basis for learning and memory in the human brain, is highly desired to be mimicked at the device level for developing neuromorphic crossmodal perception, but related researches are scarce. Here, we demonstrate an optoelectronic synapse for vision-olfactory crossmodal perception based on MXene/violet phosphorus (VP) van der Waals heterojunctions. Benefiting from the efficient separation and transport of photogenerated carriers facilitated by conductive MXene, the photoelectric responsivity of VP is dramatically enhanced by 7 orders of magnitude, reaching up to 7.7 A W-1. Excited by ultraviolet light, multiple synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, short/long-term plasticity and "learning-experience" behavior, were demonstrated with a low power consumption. Furthermore, the proposed optoelectronic synapse exhibits distinct synaptic behaviors in different gas environments, enabling it to simulate the interaction of visual and olfactory information for crossmodal perception. This work demonstrates the great potential of VP in optoelectronics and provides a promising platform for applications such as virtual reality and neurorobotics.
Collapse
Affiliation(s)
- Hailong Ma
- Center for Advancing Materials Performance From the Nanoscale (CAMP-Nano), State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China
| | - Huajing Fang
- Center for Advancing Materials Performance From the Nanoscale (CAMP-Nano), State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.
| | - Xinxing Xie
- Center for Advancing Materials Performance From the Nanoscale (CAMP-Nano), State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China
| | - Yanming Liu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - He Tian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China.
| | - Yang Chai
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.
| |
Collapse
|
14
|
Gong S, Lu Y, Yin J, Levin A, Cheng W. Materials-Driven Soft Wearable Bioelectronics for Connected Healthcare. Chem Rev 2024; 124:455-553. [PMID: 38174868 DOI: 10.1021/acs.chemrev.3c00502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
In the era of Internet-of-things, many things can stay connected; however, biological systems, including those necessary for human health, remain unable to stay connected to the global Internet due to the lack of soft conformal biosensors. The fundamental challenge lies in the fact that electronics and biology are distinct and incompatible, as they are based on different materials via different functioning principles. In particular, the human body is soft and curvilinear, yet electronics are typically rigid and planar. Recent advances in materials and materials design have generated tremendous opportunities to design soft wearable bioelectronics, which may bridge the gap, enabling the ultimate dream of connected healthcare for anyone, anytime, and anywhere. We begin with a review of the historical development of healthcare, indicating the significant trend of connected healthcare. This is followed by the focal point of discussion about new materials and materials design, particularly low-dimensional nanomaterials. We summarize material types and their attributes for designing soft bioelectronic sensors; we also cover their synthesis and fabrication methods, including top-down, bottom-up, and their combined approaches. Next, we discuss the wearable energy challenges and progress made to date. In addition to front-end wearable devices, we also describe back-end machine learning algorithms, artificial intelligence, telecommunication, and software. Afterward, we describe the integration of soft wearable bioelectronic systems which have been applied in various testbeds in real-world settings, including laboratories that are preclinical and clinical environments. Finally, we narrate the remaining challenges and opportunities in conjunction with our perspectives.
Collapse
Affiliation(s)
- Shu Gong
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Yan Lu
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Jialiang Yin
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Arie Levin
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Wenlong Cheng
- Department of Chemical & Biological Engineering, Monash University, Clayton, Victoria 3800, Australia
| |
Collapse
|
15
|
Tian F, Zhu L, Shi Q, Wang R, Zhang L, Dong Q, Qian K, Zhao Q, Hu B. The Three-Lead EEG Sensor: Introducing an EEG-Assisted Depression Diagnosis System Based on Ant Lion Optimization. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2023; 17:1305-1318. [PMID: 37402182 DOI: 10.1109/tbcas.2023.3292237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/06/2023]
Abstract
For depression diagnosis, traditional methods such as interviews and clinical scales have been widely leveraged in the past few decades, but they are subjective, time-consuming, and labor-consuming. With the development of affective computing and Artificial Intelligence (AI) technologies, Electroencephalogram (EEG)-based depression detection methods have emerged. However, previous research has virtually neglected practical application scenarios, as most studies have focused on analyzing and modeling EEG data. Furthermore, EEG data is typically obtained from specialized devices that are large, complex to operate, and poorly ubiquitous. To address these challenges, a wearable three-lead EEG sensor with flexible electrodes was developed to obtain prefrontal-lobe EEG data. Experimental measurements show that the EEG sensor achieves promising performance (background noise of no more than 0.91 μVpp, Signal-to-Noise Ratio (SNR) of 26--48 dB, and electrode-skin contact impedance of less than 1 K Ω). In addition, EEG data from 70 depressed patients and 108 healthy controls were collected using the EEG sensor, and the linear and nonlinear features were extracted. The features were then weighted and selected using the Ant Lion Optimization (ALO) algorithm to improve classification performance. The experimental results show that the k-NN classifier achieves a classification accuracy of 90.70%, specificity of 96.53%, and sensitivity of 81.79%, indicating the promising potential of the three-lead EEG sensor combined with the ALO algorithm and the k-NN classifier for EEG-assisted depression diagnosis.
Collapse
|
16
|
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.
Collapse
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.
| |
Collapse
|
17
|
Kazanskiy NL, Khonina SN, Butt MA. Smart Contact Lenses-A Step towards Non-Invasive Continuous Eye Health Monitoring. BIOSENSORS 2023; 13:933. [PMID: 37887126 PMCID: PMC10605521 DOI: 10.3390/bios13100933] [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: 09/08/2023] [Revised: 10/10/2023] [Accepted: 10/17/2023] [Indexed: 10/28/2023]
Abstract
According to the age-old adage, while eyes are often considered the gateway to the soul, they might also provide insights into a more pragmatic aspect of our health: blood sugar levels. This potential breakthrough could be realized through the development of smart contact lenses (SCLs). Although contact lenses were first developed for eyesight correction, new uses have recently become available. In the near future, it might be possible to monitor a variety of ocular and systemic disorders using contact lens sensors. Within the realm of glaucoma, SCLs present a novel prospect, offering a potentially superior avenue compared to traditional management techniques. These lenses introduce the possibility of non-invasive and continuous monitoring of intraocular pressure (IOP) while also enabling the personalized administration of medication as and when needed. This convergence holds great promise for advancing glaucoma care. In this review, recent developments in SCLs, including their potential applications, such as IOP and glucose monitoring, are briefly discussed.
Collapse
Affiliation(s)
- Nikolay L. Kazanskiy
- Samara National Research University, 443086 Samara, Russia
- IPSI RAS-Branch of the FSRC “Crystallography and Photonics” RAS, 443001 Samara, Russia
| | - Svetlana N. Khonina
- Samara National Research University, 443086 Samara, Russia
- IPSI RAS-Branch of the FSRC “Crystallography and Photonics” RAS, 443001 Samara, Russia
| | | |
Collapse
|
18
|
Wu KY, Mina M, Carbonneau M, Marchand M, Tran SD. Advancements in Wearable and Implantable Intraocular Pressure Biosensors for Ophthalmology: A Comprehensive Review. MICROMACHINES 2023; 14:1915. [PMID: 37893352 PMCID: PMC10609220 DOI: 10.3390/mi14101915] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/27/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023]
Abstract
Glaucoma, marked by its intricate association with intraocular pressure (IOP), stands as a predominant cause of non-reversible vision loss. In this review, the physiological relevance of IOP is detailed, alongside its potential pathological consequences. The review further delves into innovative engineering solutions for IOP monitoring, highlighting the latest advancements in wearable and implantable sensors and their potential in enhancing glaucoma management. These technological innovations are interwoven with clinical practice, underscoring their real-world applications, patient-centered strategies, and the prospects for future development in IOP control. By synthesizing theoretical concepts, technological innovations, and practical clinical insights, this review contributes a cohesive and comprehensive perspective on the IOP biosensor's role in glaucoma, serving as a reference for ophthalmological researchers, clinicians, and professionals.
Collapse
Affiliation(s)
- Kevin Y. Wu
- Department of Surgery, Division of Ophthalmology, University of Sherbrooke, Sherbrooke, QC J1G 2E8, Canada; (K.Y.W.)
| | - Mina Mina
- Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Marjorie Carbonneau
- Department of Surgery, Division of Ophthalmology, University of Sherbrooke, Sherbrooke, QC J1G 2E8, Canada; (K.Y.W.)
| | - Michael Marchand
- Department of Surgery, Division of Ophthalmology, University of Sherbrooke, Sherbrooke, QC J1G 2E8, Canada; (K.Y.W.)
| | - Simon D. Tran
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, QC H3A 1G1, Canada
| |
Collapse
|
19
|
Wei C, Lin W, Wang L, Cao Z, Huang Z, Liao Q, Guo Z, Su Y, Zheng Y, Liao X, Chen Z. Conformal Human-Machine Integration Using Highly Bending-Insensitive, Unpixelated, and Waterproof Epidermal Electronics Toward Metaverse. NANO-MICRO LETTERS 2023; 15:199. [PMID: 37582974 PMCID: PMC10427580 DOI: 10.1007/s40820-023-01176-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 07/21/2023] [Indexed: 08/17/2023]
Abstract
Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals, which is critical to the breakthrough development of metaverse. Interactive electronics face common dilemmas, which realize high-precision and stable touch detection but are rigid, bulky, and thick or achieve high flexibility to wear but lose precision. Here, we construct highly bending-insensitive, unpixelated, and waterproof epidermal interfaces (BUW epidermal interfaces) and demonstrate their interactive applications of conformal human-machine integration. The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection, high flexibility, rapid response time, excellent stability, and versatile "cut-and-paste" character. Regardless of whether being flat or bent, the BUW epidermal interface can be conformally attached to the human skin for real-time, comfortable, and unrestrained interactions. This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics, which offers a new technology route and may further broaden human-machine interactions toward metaverse.
Collapse
Affiliation(s)
- Chao Wei
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China
| | - Wansheng Lin
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China
| | - Liang Wang
- Department of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China
| | - Zhicheng Cao
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China
| | - Zijian Huang
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China
| | - Qingliang Liao
- Academy for Advanced Interdisciplinary Science and Technology, Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing, 100083, People's Republic of China
- Beijing Key Laboratory for Advanced Energy Materials and Technologies, School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083, People's Republic of China
| | - Ziquan Guo
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China
| | - Yuhan Su
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China
| | - Yuanjin Zheng
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Xinqin Liao
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China.
| | - Zhong Chen
- Department of Electronic Science, Xiamen University, Xiamen, 361005, People's Republic of China.
| |
Collapse
|