Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation
The last few years have seen significant advances in neuromotor rehabilitation technologies, such as robotics and virtual reality. Rehabilitation robotics primarily focuses on devices, control strategies, scenarios and protocols aimed at recovering sensory, motor and cognitive impairments often expe...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/21/7793 |
| _version_ | 1797548875575197696 |
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| author | Yassine Bouteraa Ismail Ben Abdallah Atef Ibrahim Tariq Ahamed Ahanger |
| author_facet | Yassine Bouteraa Ismail Ben Abdallah Atef Ibrahim Tariq Ahamed Ahanger |
| author_sort | Yassine Bouteraa |
| collection | DOAJ |
| description | The last few years have seen significant advances in neuromotor rehabilitation technologies, such as robotics and virtual reality. Rehabilitation robotics primarily focuses on devices, control strategies, scenarios and protocols aimed at recovering sensory, motor and cognitive impairments often experienced by stroke victims. Remote rehabilitation can be adopted to relieve stress in healthcare facilities by limiting the movement of patients to clinics, mainly in the current COVID-19 pandemic. In this context, we have developed a remote controlled intelligent robot for elbow rehabilitation. The proposed system offers real-time monitoring and ultimately provides an electronic health record (EHR). Rehabilitation is an area of medical practice that treats patients with pain. However, this pain can prevent a person from positively interacting with therapy. To cope with this matter, the proposed solution incorporates a cascading fuzzy decision system to estimate patient pain. Indeed, as a safety measure, when the pain exceeds a certain threshold, the robot must stop the action even if the desired angle has not yet been reached. A fusion of sensors incorporating an electromyography (EMG) signal, feedback from the current sensor and feedback from the position encoder provides the fuzzy controller with the data needed to estimate pain. This measured pain is fed back into the control loop and processed to generate safe robot actions. The main contribution was to integrate vision-based gesture control, a cascade fuzzy logic-based decision system and IoT (Internet of Things) to help therapists remotely take care of patients efficiently and reliably. Tests carried out on three different subjects showed encouraging results. |
| first_indexed | 2024-03-10T15:06:59Z |
| format | Article |
| id | doaj.art-5cda070a521e4be7b760c7f64ffa9b39 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T15:06:59Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-5cda070a521e4be7b760c7f64ffa9b392023-11-20T19:40:09ZengMDPI AGApplied Sciences2076-34172020-11-011021779310.3390/app10217793Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow RehabilitationYassine Bouteraa0Ismail Ben Abdallah1Atef Ibrahim2Tariq Ahamed Ahanger3College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al Kharj 16268, Saudi ArabiaCEM-Lab ENIS & Digital Research Center of Sfax, University of Sfax, Sfax 3038, TunisiaCollege of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al Kharj 16268, Saudi ArabiaCollege of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al Kharj 16268, Saudi ArabiaThe last few years have seen significant advances in neuromotor rehabilitation technologies, such as robotics and virtual reality. Rehabilitation robotics primarily focuses on devices, control strategies, scenarios and protocols aimed at recovering sensory, motor and cognitive impairments often experienced by stroke victims. Remote rehabilitation can be adopted to relieve stress in healthcare facilities by limiting the movement of patients to clinics, mainly in the current COVID-19 pandemic. In this context, we have developed a remote controlled intelligent robot for elbow rehabilitation. The proposed system offers real-time monitoring and ultimately provides an electronic health record (EHR). Rehabilitation is an area of medical practice that treats patients with pain. However, this pain can prevent a person from positively interacting with therapy. To cope with this matter, the proposed solution incorporates a cascading fuzzy decision system to estimate patient pain. Indeed, as a safety measure, when the pain exceeds a certain threshold, the robot must stop the action even if the desired angle has not yet been reached. A fusion of sensors incorporating an electromyography (EMG) signal, feedback from the current sensor and feedback from the position encoder provides the fuzzy controller with the data needed to estimate pain. This measured pain is fed back into the control loop and processed to generate safe robot actions. The main contribution was to integrate vision-based gesture control, a cascade fuzzy logic-based decision system and IoT (Internet of Things) to help therapists remotely take care of patients efficiently and reliably. Tests carried out on three different subjects showed encouraging results.https://www.mdpi.com/2076-3417/10/21/7793rehabilitation roboticshuman–robot interactiongesture controlInternet of Things |
| spellingShingle | Yassine Bouteraa Ismail Ben Abdallah Atef Ibrahim Tariq Ahamed Ahanger Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation Applied Sciences rehabilitation robotics human–robot interaction gesture control Internet of Things |
| title | Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation |
| title_full | Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation |
| title_fullStr | Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation |
| title_full_unstemmed | Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation |
| title_short | Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation |
| title_sort | development of an iot based solution incorporating biofeedback and fuzzy logic control for elbow rehabilitation |
| topic | rehabilitation robotics human–robot interaction gesture control Internet of Things |
| url | https://www.mdpi.com/2076-3417/10/21/7793 |
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