{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:01:34Z","timestamp":1777705294269,"version":"3.51.4"},"reference-count":32,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,3,2]]},"abstract":"<jats:p>In this paper, a robotic system dedicated to remote wrist rehabilitation is proposed as an Internet of Things (IoT) application. The system offers patients home rehabilitation. Since the physiotherapist and the patient are on different sites, the system guarantees that the physiotherapist controls and supervises the rehabilitation process and that the patient repeats the same gestures made by the physiotherapist. A human-machine interface (HMI) has been developed to allow the physiotherapist to remotely control the robot and supervise the rehabilitation process. Based on a computer vision system, physiotherapist gestures are sent to the robot in the form of control instructions. Wrist range of motion (RoM), EMG signal, sensor current measurement, and streaming from the patient\u2019s environment are returned to the control station. The various acquired data are displayed in the HMI and recorded in its database, which allows later monitoring of the patient\u2019s progress. During the rehabilitation process, the developed system makes it possible to follow the muscle contraction thanks to an extraction of the Electromyography (EMG) signal as well as the patient\u2019s resistance thanks to a feedback from a current sensor. Feature extraction algorithms are implemented to transform the EMG raw signal into a relevant data reflecting the muscle contraction. The solution incorporates a cascade fuzzy-based decision system to indicate the patient\u2019s pain. As measurement safety, when the pain exceeds a certain threshold, the robot should stop the action even if the desired angle is not yet reached. Information on the patient, the evolution of his state of health and the activities followed, are all recorded, which makes it possible to provide an electronic health record. Experiments on 3 different subjects showed the effectiveness of the developed robotic solution.<\/jats:p>","DOI":"10.3233\/jifs-201671","type":"journal-article","created":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T15:26:34Z","timestamp":1610119594000},"page":"4835-4850","source":"Crossref","is-referenced-by-count":6,"title":["Fuzzy logic-based connected robot for home rehabilitation"],"prefix":"10.1177","volume":"40","author":[{"given":"Yassine","family":"Bouteraa","sequence":"first","affiliation":[{"name":"Digital Research Center of Sfax & CEM Lab-ENIS, University of Sfax, Sfax, Tunisia"},{"name":"Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ismail Ben","family":"Abdallah","sequence":"additional","affiliation":[{"name":"Centre de Recherche en Num\u00e9rique de Sfax, Sfax, Tunisie"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Atef","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tariq Ahamed","family":"Ahanger","sequence":"additional","affiliation":[{"name":"Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-201671_ref2","doi-asserted-by":"crossref","first-page":"101739","DOI":"10.1016\/j.bspc.2019.101739","article-title":"Predicting the occurrence of wrist tremor based on electromyography using a hidden markov model and entropy based learning algorithm","volume":"57","author":"Samaee","year":"2020","journal-title":"Biomedical Signal Processing and Control"},{"issue":"2","key":"10.3233\/JIFS-201671_ref5","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1109\/TNSRE.2013.2250521","article-title":"Wrist rehabilitation in chronic stroke patients by means of adaptive, progressive robot-aided therapy","volume":"22","author":"Giannoni","year":"2014","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"10.3233\/JIFS-201671_ref6","doi-asserted-by":"crossref","unstructured":"Abdallah I.B. , Bouteraa Y. and Rekik C. , Web-based robot control for wrist telerehabilitation. 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