Wireless, Skin-Mountable EMG Sensor for Human–Machine Interface Application
Open accessAbstract
The development of advanced technologies for wireless data collection and the analysis of quantitative data, with application to a human–machine interface (HMI), is of growing interest. In particular, various wearable devices related to HMIs are being developed. These devices require a customization process that considers the physical characteristics of each individual, such as mounting positions of electrodes, muscle masses, and so forth. Here, the authors report device and calculation concepts for flexible platforms that can measure electrical signals changed through electromyography (EMG). This soft, flexible, and lightweight EMG sensor can be attached to curved surfaces such as the forearm, biceps, back, legs, etc., and optimized biosignals can be obtained continuously through post-processing. In addition to the measurement of EMG signals, the application of the HMI has stable performance and high accuracy of more than 95%, as confirmed by 50 trials per case. The result of this study shows the possibility of application to various fields such as entertainment, the military, robotics, and healthcare in the future.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The attachable skin format of these sensors improves the portability of otherwise cumbersome devices and can optimise bioelectrical signals obtained from users.
“Additionally, the attachable skin format of these sensors improves the portability of the otherwise cumbersome devices, and can optimise bioelectrical signals obtained from users [7].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [7]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Materials and Optimized Designs for Human‐Machine Interfaces Via Epidermal Electronics
Jeong, J., Yeo, W., Akhtar, A., Norton, J. J. S., Kwack, Y., Li, S., Jung, S., Su, Y., Lee, W., Xia, J., et al. (2013) · Advanced Materials · doi:10.1002/adma.201301921 · Cited by 827 · see citing works
Roni, P., Beechie, T. J., Bilby, R. E., Leonetti, F. E., Pollock, M. M., & Pess, G. R. (2002) · North American Journal of Fisheries Management · doi:10.1577/1548-8675(2002)022 · Cited by 623 · see citing works
An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot
Kiguchi, K., & Hayashi, Y. (2012) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2012.2185843 · Cited by 532 · see citing works
Self-assembled three dimensional network designs for soft electronics
Jang, K.-I., Li, K., Chung, H. U., Xu, S., Jung, H. N., Yang, Y., Kwak, J. W., Jung, H. H., Song, J., Yang, C., et al. (2017) · Nature Communications · doi:10.1038/ncomms15894 · Cited by 445 · see citing works
Self-citationCasson, A. J. (2019) · Biomedical Engineering Letters · doi:10.1007/s13534-018-00093-6 · Cited by 345 · see citing works
Miniaturized Battery‐Free Wireless Systems for Wearable Pulse Oximetry
Kim, J., Gutruf, P., Chiarelli, A. M., Heo, S. Y., Cho, K., Xie, Z., Banks, A. R., Han, S., Jang, K., Lee, J. W., et al. (2016) · Advanced Functional Materials · doi:10.1002/adfm.201604373 · Cited by 334 · see citing works
Self-citationThe status of spectral EEG abnormality as a diagnostic test for schizophrenia
Boutros, N. N., Arfken, C. L., Galderisi, S., Warrick, J. I., Pratt, G., & Iacono, W. G. (2007) · Schizophrenia Research · doi:10.1016/j.schres.2007.11.020 · Cited by 324 · see citing works
Compliant and stretchable thermoelectric coils for energy harvesting in miniature flexible devices
Nan, K., Kang, S. D., Li, K., Yu, K. J., Zhu, F., Wang, J., Dunn, A. C., Zhou, C., Xie, Z., Agne, M. T., et al. (2018) · Science Advances · doi:10.1126/sciadv.aau5849 · Cited by 282 · see citing works
Self-citationEpidermal Electronics with Advanced Capabilities in Near-Field Communication
Kim, J., Banks, A., Cheng, H., Xie, Z., Xu, S., Jang, K.-I., Lee, J. W., Liu, Z., Gutruf, P., Huang, X., et al. (2015) · Small · doi:10.1002/smll.201402495 · Cited by 274 · see citing works
Self-citationEMG-Based Control of a Robot Arm Using Low-Dimensional Embeddings
Artemiadis, P., & Kyriakopoulos, K. J. (2010) · IEEE Transactions on Robotics · doi:10.1109/tro.2009.2039378 · Cited by 268 · see citing works
ECG Criteria to Identify Epicardial Ventricular Tachycardia in Nonischemic Cardiomyopathy
Vallès, E., Bazán, V., & Marchlinski, F. E. (2009) · Circulation Arrhythmia and Electrophysiology · doi:10.1161/circep.109.859942 · Cited by 266 · see citing works
Koo, J. H., Jeong, S., Shim, H. J., Son, D., Kim, J., Kim, D. C., Choi, S., Hong, J., & Kim, D. (2017) · ACS Nano · doi:10.1021/acsnano.7b04292 · Cited by 261 · see citing works
Self-citationAn EMG-Controlled Exoskeleton for Hand Rehabilitation
Mulas, M., Folgheraiter, M., & Gini, G. C. (2005) · doi:10.1109/icorr.2005.1501122 · Cited by 225 · see citing works
Xia, P., Hu, J., & Peng, Y. (2017) · Artificial Organs · doi:10.1111/aor.13004 · Cited by 225 · see citing works
Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors
Zhang, X., Chen, X. '., Wang, W., Yang, J., Lantz, V., & Wang, K. (2009) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/1502650.1502708 · Cited by 212 · see citing works
Xu, G., Cheng, C., Liu, Z., Yuan, W., Wu, X., Lu, Y., Low, S. S., Liu, J., Zhu, L., Ji, D., et al. (2019) · Advanced Materials Technologies · doi:10.1002/admt.201800658 · Cited by 172 · see citing works
Characterizing EMG data using machine-learning tools
Yousefi, J., & Hamilton-Wright, A. (2014) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2014.04.018 · Cited by 159 · see citing works
Gorgels, A. P. M., Vos, M. A., Mulleneers, R. G. A., de Zwaan, C., Bär, F. W. H. M., & Wellens, H. J. J. (1993) · The American Journal of Cardiology · doi:10.1016/0002-9149(93)90852-4 · Cited by 151 · see citing works
Kim, N., Lim, T., Song, K., Yang, S. H., & Lee, J. (2016) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.6b05025 · Cited by 69 · see citing works
Calibration of an EMG-Based Body Model with six Muscles to control a Leg Exoskeleton
Fleischer, C., & Hommel, G. (2007) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2007.363843 · Cited by 46 · see citing works
Roland, T., Wimberger, K., Amsuess, S., Russold, M., & Baumgärtner, W. (2019) · Sensors · doi:10.3390/s19040961 · Cited by 45 · see citing works
Electromyogram (EMG) driven system based virtual reality for prosthetic and rehabilitation devices
Al-Jumaily, A. A., & Olivares, R. A. (2009) · International Conference on Information Integration and Web-based Applications & Services (iiWAS) · doi:10.1145/1806338.1806448 · Cited by 35 · see citing works
Drowsiness detection system based on eye-closure using a low-cost EMG and ESP8266
Artanto, D., Sulistyanto, M. P., Pranowo, I. D., & Pramesta, E. E. (2017) · International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) · doi:10.1109/icitisee.2017.8285502 · Cited by 32 · see citing works
Mobility assistance robot for disabled persons using electromyography(EMG) sensor
Ahmed, S. F., Ali, A., Joyo, M. K., Rehan, M., Siddiqui, F. A., Bhatti, J. A., Liaquat, A., & Dezfouli, M. M. S. (2018) · IEEE International Conference on Innovative Research and Development (ICIRD) · doi:10.1109/icird.2018.8376304 · Cited by 25 · see citing works
Small‐Scale Biological and Artificial Multidimensional Sensors for 3D Sensing
Agarwal, K., Hwang, S., Bartnik, A., Buchele, N., Mishra, A., & Cho, J. (2018) · Small · doi:10.1002/smll.201801145 · Cited by 22 · see citing works
Vibration Induced Proprioceptive Modulation in Surface-EMG Based Control of a Robotic Arm
Rangwani, R., & Park, H. (2019) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2019.8717117 · Cited by 12 · see citing works
Ultra-Sensitive Flexible Tactile Sensor Based on Graphene Film
Lü, X., Qi, L., Hu, H., Li, X., Bai, G., Chen, J., & Bao, W. (2019) · Micromachines · doi:10.3390/mi10110730 · Cited by 12 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
End-to-end design of wearable sensors
Ates, H. C., Nguyen, P. Q., Gonzalez-Macia, L., Morales-Narváez, E., Güder, F., Collins, J. J., & Dincer, C. (2022) · Nature Reviews Materials · doi:10.1038/s41578-022-00460-x · Cited by 1,306 · see citing works
Review of Wearable Devices and Data Collection Considerations for Connected Health
Vijayan, V., Connolly, J. P., Condell, J., McKelvey, N., & Gardiner, P. (2021) · Sensors · doi:10.3390/s21165589 · Cited by 435 · see citing works
Zhu, M., He, T., & Lee, C. (2020) · Applied Physics Reviews · doi:10.1063/5.0016485 · Cited by 289 · see citing works
IoT‐Based Smart Alert System for Drowsy Driver Detection
Biswal, A. K., Singh, D., Pattanayak, B. K., Samanta, D., & Yang, M. (2021) · Wireless Communications and Mobile Computing · doi:10.1155/2021/6627217 · Cited by 176 · see citing works
Sensors for Context-Aware Smart Healthcare: A Security Perspective
Batista, E., Moncusi, M. A., López-Aguilar, P., Martínez-Ballesté, A., & Solanas, A. (2021) · Sensors · doi:10.3390/s21206886 · Cited by 88 · see citing works
Ali, A., Khan, S. J., Azim, F., Shakeel, C. S., Hussain, A., & Niazi, I. K. (2022) · Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · doi:10.1177/09544119221074770 · Cited by 51 · see citing works
Robotics Perception and Control: Key Technologies and Applications
Luo, J., Zhou, X., Zeng, C., Jiang, Y., Qi, W., Xiang, K., Pang, M., & Tang, B. (2024) · Micromachines · doi:10.3390/mi15040531 · Cited by 45 · see citing works
Advances in Wearable Sensors for Health Management: From Advanced Materials to Intelligent Systems
Song, S., Zhang, M., Gong, X., Shi, S., Fang, J. H., & Wang, X. (2025) · Advanced Functional Materials · doi:10.1002/adfm.202518767 · Cited by 39 · see citing works
A temporal Convolutional Network for EMG compressed sensing reconstruction
Zhang, L., Chen, J., Liu, W., Liu, X., Ma, C., & Xu, L. (2023) · Measurement · doi:10.1016/j.measurement.2023.113944 · Cited by 29 · see citing works
Measuring Biosignals with Single Circuit Boards
Ehrmann, G., Błachowicz, T., Homburg, S. V., & Ehrmann, A. (2022) · Bioengineering · doi:10.3390/bioengineering9020084 · Cited by 27 · see citing works
Wireless Wearable Devices and Recent Applications in Health Monitoring and Clinical Diagnosis
Su, M., Hua, J., Sun, X., Liu, Z., Shi, Y., & Pan, L. (2023) · Biomedical Materials & Devices · doi:10.1007/s44174-023-00141-5 · Cited by 22 · see citing works
Campbell, E., Eddy, E., Bateman, S., Côté‐Allard, U., & Scheme, E. (2024) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-024-01355-4 · Cited by 20 · see citing works
A Wearable Dual-Channel Bioimpedance Spectrometer for Real-Time Muscle Contraction Detection
Kusche, R., Oltmann, A., & Rostalski, P. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3359284 · Cited by 16 · see citing works
Wearable Regionally Trained AI-Enabled Bruxism-Detection System
Ishtiaq, A., Gul, J. Z., Din, Z. M. U., Imran, A., & Hindi, K. M. E. (2025) · IEEE Access · doi:10.1109/access.2025.3532360 · Cited by 14 · see citing works
Internet of Things, a vision of digital twins and case studies
Murthy, A. S., Irshad, M., Noman, S. M., Tang, X., Hu, B., Song, C., & Khader, G. W. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-821051-2.00010-6 · Cited by 13 · see citing works
Wearable Sensors for Motion and Electrophysiological Signal Tracking in XR
Qiu, Y., He, X., Li, Z., Peng, Z., Huang, Y., & Yu, X. (2024) · Korean Journal of Chemical Engineering · doi:10.1007/s11814-024-00227-w · Cited by 14 · see citing works
Multifaceted Free-Space Tissue Sensing up to 100 GHz
Prokscha, A., Batra, A., Santhakumaran, S., Fabricius, J., Kirchner, E. A., & Kaiser, T. (2024) · IEEE Access · doi:10.1109/access.2024.3439605 · Cited by 12 · see citing works
Assembly‐Type Wireless Communication Patch for Miniaturized Flexible Wearable Sensors
Song, M., Kang, S., Kim, J., & Kim, J. (2021) · Advanced Materials Technologies · doi:10.1002/admt.202100034 · Cited by 11 · see citing works
Self-citationBaijot, M., Puers, R., & Kraft, M. D. (2021) · Sensors · doi:10.3390/s21196362 · Cited by 11 · see citing works
Varela, D. T., Ferrer-Varela, J. A., Cruz-Morales, R. D., & Padilla-García, E. A. (2022) · Micromachines · doi:10.3390/mi13101681 · Cited by 11 · see citing works
Bionic Sensors for Biometric Acquisition and Monitoring: Challenges and Opportunities
Yu, H., Ma, M., Zhang, B., Wang, A., Zhong, G., Zhou, Z., Liu, C., Li, C., Fang, J., He, Y., et al. (2025) · Sensors · doi:10.3390/s25133981 · Cited by 9 · see citing works
Khan, M. A., Bayram, B. M., Das, R., & Puthusserypady, S. K. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9630245 · Cited by 9 · see citing works
An sEMG Signal-based Robotic Arm for Rehabilitation applying Fuzzy Logic
Nguyen, N.-K., Dao, T.-M.-P., Nguyen, T.-D., Nguyen, D.-T., Nguyen, H.-T., & Nguyen, V.-L. (2024) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.7146 · Cited by 8 · see citing works
Cui, Z., Fu, X., Wan, X., Li, J., Chen, W., Zhu, S., & Li, Y. (2021) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/bci51272.2021.9385371 · Cited by 7 · see citing works
Bioelectronic Sensors for Neuromuscular Perception in Human‐Machine Interfaces
Li, J., Niu, B., Wu, K., Xiao, J., Liu, X., & Wang, Y. (2025) · Advanced Robotics Research · doi:10.1002/adrr.202500047 · Cited by 6 · see citing works
Non-invasive wearable electrochemical biosensors for personalized applications in health management
Kang, X., Luo, A., Khan, N. A., Zhang, T., Ma, X., Zhao, Z., Tang, Y., Wang, W., Dai, K., Liang, A., et al. (2026) · Sensors International · doi:10.1016/j.sintl.2026.100381 · Cited by 4 · see citing works
Joel, J. P. A., Raj, R. J. S., Durai, C. A. D., & Vedaiyan, R. (2020) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-020-02405-0 · Cited by 4 · see citing works
RetractedA Miniaturized Flexible Surface Electromyography Sensor With an Integrated Localization Concept
Balbach, S., Kolpak, J., Dorn, C., Brückner, S., Schlechtweg, N., Gambietz, M., Koelewijn, A. D., Vossiek, M., & Hagelauer, A. (2025) · IEEE Microwave Magazine · doi:10.1109/mmm.2024.3494717 · Cited by 3 · see citing works
Li, M. (2025) · Thermal Science and Engineering Progress · doi:10.1016/j.tsep.2025.103222 · Cited by 2 · see citing works
RetractedNguyen, N., Dao, T.-M.-P., Nguyen, V., Pham, V., Pham, V.-M., & Pham, V. (2024) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2024.0150348 · Cited by 2 · see citing works
Design and Implementation of an IoT Drowsiness Detection System for DriversPreprint
Kallel, F. (2023) · Research Square · doi:10.21203/rs.3.rs-3268242/v1 · Cited by 2 · see citing works
Novel Graphene Electrode for Electromyography Using Wearables Based on Smart Textiles
Argiró, M. H. H., Quaresma, C., & Silva, H. (2022) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-07520-9_19
IoT based smart transportation system for driver safety using Raspberry Pi
Sridhar, B. T. N., & Lahari, S. (2023) · AIP conference proceedings · doi:10.1063/5.0113336
Towards Skin and Muscle Sensing from GHz to sub-THz SpectrumPreprint
Batra, A., Prokscha, A., Santhakumaran, S., Fabricius, J., Kirchner, E. A., & Kaiser, T. (2023) · doi:10.36227/techrxiv.23199794
Optimal Design of Robust Wireless Power Transfer Links for Human-machine Interface *
Wu, Y., Fang, Y., Guo, W., & Sheng, X. (2023) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio58561.2023.10354827
An Everyday Hat for Detection of Eye Blinks and Forehead Clenching
Rahman, S. M. M., Mattila, H., Shaikh, A., Raumonen, P., & Virkki, J. (2024) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-61625-9_8
STEBAM: Expanding STEAM Education with Biomedical Engineering
Sousa, L. C. D., Ferreira, A. F., & Silva, H. (2025) · International Conference of the Portuguese Society for Engineering Education (CISPEE) · doi:10.1109/cispee64787.2025.11123922
An Affordable and Fully Functional Bionic Claw Using Myoelectric Signals for Physically ChallengedPreprint
Shankar, N., Bhagavath, B. P., Avinash, N., Raju, N. K. K., & Subashini, M. M. (2022) · Research Square · doi:10.21203/rs.3.rs-2138754/v1
Smart wearable sensing systems mediating the digital monitoring of loneliness – A review
Mexia, N., Molteni, E., Ratcliffe, J., Probst, F., Matcham, F., Rees, J., Sebastien Ourselin, A., Antonelli, M., Tinker, A., Liu, W., et al. (2026) · Materials Today Electronics · doi:10.1016/j.mtelec.2026.100202
A Shallow Deep Learning Model for Stress Monitoring from Photoplethysmography Signals
Ali, M. S., Motin, M. A., Mim, M. R., & Kabir, S. (2025) · IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON) · doi:10.1109/spicscon69221.2025.11504104
Masonry workers risk assessment with different trowels using ARIMA model forecasting
Ramya, P., Venkatachalam, S., Yogesh, V., Varun, S., & Karthik, J. R. (2026) · AIP conference proceedings · doi:10.1063/5.0328782
Santhakumaran, S., & Kirchner, E. A. (2026) · International Workshop on Mobile Terahertz Systems (IWMTS) · doi:10.1109/icmmts68132.2026.11733039
- Authors
- Song, M.-S., Kang, S.-G., Lee, K.-T., & Kim, J.
- Affiliations
- Kwangwoon University (KR)
- Inha University (KR)
- Corresponding author
- Lee, Kyu-Tae
- Kim, Jeonghyun
- Venue
- Micromachines
- Publisher
- MDPI AG
- Published
- 2019-12-14
- Volume
- 10
- Issue
- 12
- Pages
- 879
- ISSN
- 2072-666X (ISSN-L)
- PMC
- PMC6952934
- OpenAlex
- W2994896693
- Cited by
- 42
- References
- 27
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 8 · 2023: 6 · 2022: 7 · 2021: 7 · 2020: 2
- FWCI
- 1.41
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Micromachines (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Research Foundation of Korea (NRF-2018R1C1B5045524)
- Korea Institute for Advancement of Technology (No. P0002397)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Keywords
- electromyography sensors, wireless sensors, human-machine interaction, wearable devices, flexible electronics, EMG signal processing, physiological signals
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
