{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T14:56:03Z","timestamp":1781621763915,"version":"3.54.5"},"reference-count":59,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T00:00:00Z","timestamp":1675814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Technology and Science Council, Taiwan","award":["MOST 110-2222-E-006-006"],"award-info":[{"award-number":["MOST 110-2222-E-006-006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Neurodegenerative diseases such as Parkinson\u2019s disease affect motor symptoms with abnormally increased or reduced movements. Symptoms such as tremor and hand movement disorders can be subtle and vary daily such that the actual condition of the disease may not fully present in clinical sessions. Health examination and monitoring, if available in the living space, can capture comprehensive and quantitative information about a patient\u2019s motor symptoms, allowing physicians to make a precise diagnosis and devise a more personalized treatment. WiFi-based sensing is a potential solution for passively detecting human motion in a contactless way that collects no personally identifiable information. This study proposed an approach for human micromotion detection using the WiFi channel state information, which can be realized in a regular-sized room for home health monitoring and examination. Three types of motion were tested to evaluate the proposed method in quantifying micromotion using single and multiple WiFi links. The results show that micromotion could be captured at all distributed locations in the experimental environment (4.2 m \u00d7 7.9 m). Our computer algorithm computed the frequency and duration of simulated hand tremors with an average accuracy of 90.9% (single WiFi link)\u201495.7% (multiple WiFi links).<\/jats:p>","DOI":"10.3390\/bioengineering10020228","type":"journal-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T06:00:05Z","timestamp":1675836005000},"page":"228","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["WiFi-Based Detection of Human Subtle Motion for Health Applications"],"prefix":"10.3390","volume":"10","author":[{"given":"Hui-Hsin","family":"Chen","sequence":"first","affiliation":[{"name":"KLA Corporation, Chupei City 302, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1873-6078","authenticated-orcid":false,"given":"Chi-Lun","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, National Cheng Kung University, 1 University Rd., East Dist., Tainan 701, Taiwan"},{"name":"Medical Device Innovation Center, National Cheng Kung University, Tainan 701, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun-Hsiang","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, National Cheng Kung University, 1 University Rd., East Dist., Tainan 701, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Qian, K., Wu, C., Zhang, Y., Zhang, G., Yang, Z., and Liu, Y. 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