Listening to muscles: a machine learning approach to low-cost sarcopenia detection for older adults.

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Bibliographic Details
Title: Listening to muscles: a machine learning approach to low-cost sarcopenia detection for older adults.
Authors: Huang CH; Department of Family Medicine and Community Medicine, E-Da Hospital, I-Shou University, Kaohsiung City, Taiwan; School of Medicine for International Students, College of Medicine, I-Shou University, Kaohsiung City, Taiwan; College of Nursing, Kaohsiung Medical University, Kaohsiung City, Taiwan., Huang TH; Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, Penghu, Taiwan., Ouyang CS; Department of Information Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; Department of Pediatrics, School of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan., Huang HC; Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan., Chen YJ; Department of Information Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan; Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan. Electronic address: yjjchen@nkust.edu.tw., Ho WH; Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Precision Sports Medicine and Health Promotion Center, Kaohsiung Medical University, Kaohsiung, Taiwan; College of Professional Studies, National Pingtung University of Science and Technology, Pingtung, Taiwan. Electronic address: whho@kmu.edu.tw.
Source: Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology [J Electromyogr Kinesiol] 2026 Jul 04; Vol. 90, pp. 103184. Date of Electronic Publication: 2026 Jul 04.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: England NLM ID: 9109125 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-5711 (Electronic) Linking ISSN: 10506411 NLM ISO Abbreviation: J Electromyogr Kinesiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1873-5711
DOI:10.1016/j.jelekin.2026.103184