Affiliations: [a] Digital Research Center of Sfax & CEM Lab-ENIS, University of Sfax, Sfax, Tunisia
| [b] Centre de Recherche en Numérique de Sfax, Sfax, Tunisie
| [c]
Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
Correspondence:
[*]
Corresponding author. Yassine Bouteraa, Prince Sattam Bin Abdulaziz University, KSA & Digital Research Center of Sfax & CEM Lab-ENIS, University of Sfax, Tunisia. E-mail: yassine.bouteraa@isbs.usf.tn.
Abstract: 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’s 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’s 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’s 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’s 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.
Keywords: Gesture control, human robot interaction, internet of things, rehabilitation robotics
