{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:24:15Z","timestamp":1760232255010,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T00:00:00Z","timestamp":1666137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education","award":["NRF-2018R1A6A1A03025109"],"award-info":[{"award-number":["NRF-2018R1A6A1A03025109"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The activities of daily living (ADL) ability level of an elderly patient is an important indicator in determining the patient\u2019s degree of degenerative brain disease and is mainly evaluated through face-to-face interviews with doctors and patients in hospitals. It is impossible to determine the exact ADL ability of a patient through such a temporary interview, and the pursuit of accurate ADL ability evaluation technology is a very important research task worldwide. In this paper, in order to overcome the limitations of the existing ADL evaluation method mentioned above, first of all, a self-organized IoT architecture in which IoT devices autonomously and non-invasively measure a patient\u2019s ADL ability within the context of the patient\u2019s daily living place was designed and implemented. Second, a remote rehabilitation treatment concept for enhancing the patient\u2019s ADL ability we call an \u201ce-coaching framework\u201d, in which a doctor remotely gives an instruction in a specific ADL scenario, and the patient\u2019s ability to understand and perform the instruction can be measured on-line and in real time, was additionally developed on top of the self-organized IoT architecture. In order to verify the possibility of remote rehabilitation treatment through the proposed architecture, various remotely directed ADL scenarios were performed and the accuracy of the measurements was verified.<\/jats:p>","DOI":"10.3390\/s22207957","type":"journal-article","created":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T22:19:53Z","timestamp":1666217993000},"page":"7957","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients"],"prefix":"10.3390","volume":"22","author":[{"given":"Hyo-Jung","family":"Kim","sequence":"first","affiliation":[{"name":"School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea"}]},{"given":"Seol-Young","family":"Jeong","sequence":"additional","affiliation":[{"name":"Software Education Institute, Kyungpook National University, Daegu 41566, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8171-195X","authenticated-orcid":false,"given":"Soon-Ju","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,19]]},"reference":[{"key":"ref_1","unstructured":"Edemekong, P.F., Bomgaars, D.L., Sukumaran, S., and Levy, S.B. 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