{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T18:28:57Z","timestamp":1780943337373,"version":"3.54.1"},"reference-count":34,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,7,27]],"date-time":"2021-07-27T00:00:00Z","timestamp":1627344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF 2019S1A5A2A03037891, 2020M3A9E410438511"],"award-info":[{"award-number":["NRF 2019S1A5A2A03037891, 2020M3A9E410438511"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Driver drowsiness is a major cause of fatal accidents throughout the world. Recently, some studies have investigated steering wheel grip force-based alternative methods for detecting driver drowsiness. In this study, a driver drowsiness detection system was developed by investigating the electromyography (EMG) signal of the muscles involved in steering wheel grip during driving. The EMG signal was measured from the forearm position of the driver during a one-hour interactive driving task. Additionally, the participant\u2019s drowsiness level was also measured to investigate the relationship between muscle activity and driver\u2019s drowsiness level. Frequency domain analysis was performed using the short-time Fourier transform (STFT) and spectrogram to assess the frequency response of the resultant signal. An EMG signal magnitude-based driver drowsiness detection and alertness algorithm is also proposed. The algorithm detects weak muscle activity by detecting the fall in EMG signal magnitude due to an increase in driver drowsiness. The previously presented microneedle electrode (MNE) was used to acquire the EMG signal and compared with the signal obtained using silver-silver chloride (Ag\/AgCl) wet electrodes. The results indicated that during the driving task, participants\u2019 drowsiness level increased while the activity of the muscles involved in steering wheel grip decreased concurrently over time. Frequency domain analysis showed that the frequency components shifted from the high to low-frequency spectrum during the one-hour driving task. The proposed algorithm showed good performance for the detection of low muscle activity in real time. MNE showed highly comparable results with dry Ag\/AgCl electrodes, which confirm its use for EMG signal monitoring. The overall results indicate that the presented method has good potential to be used as a driver\u2019s drowsiness detection and alertness system.<\/jats:p>","DOI":"10.3390\/s21155091","type":"journal-article","created":{"date-parts":[[2021,7,27]],"date-time":"2021-07-27T22:35:02Z","timestamp":1627425302000},"page":"5091","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Microneedle Array Electrode-Based Wearable EMG System for Detection of Driver Drowsiness through Steering Wheel Grip"],"prefix":"10.3390","volume":"21","author":[{"given":"Afraiz Tariq","family":"Satti","sequence":"first","affiliation":[{"name":"Department of Electronics Engineering, Gachon University, Seongnam 13210, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiyoun","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Exercise Rehabilitation & Welfare, Gachon University, Incheon 21936, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eunsurk","family":"Yi","sequence":"additional","affiliation":[{"name":"Department of Exercise Rehabilitation & Welfare, Gachon University, Incheon 21936, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0465-9665","authenticated-orcid":false,"given":"Hwi-young","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy, Gachon University, Incheon 21936, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3839-6410","authenticated-orcid":false,"given":"Sungbo","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Electronics Engineering, Gachon University, Seongnam 13210, Korea"},{"name":"Department of Health Science and Technology, GAIHST, Gachon University, Incheon 21999, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1093\/sleep\/12.5.458","article-title":"The Detection of Sleep Onset: Behavioral, Physiological, and Subjective Convergence","volume":"12","author":"Ogilvie","year":"1989","journal-title":"Sleep"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Soares, S., Monteiro, T., Lobo, A., Couto, A., Cunha, L., and Ferreira, S. 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