Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach
In this paper, an autonomous exercise generation system based of fuzzy logic approach is presented. This work attempts to close a gap in the design of a completely autonomous robotic rehabilitation system that can recommend exercises to patients based on their data, such as shoulder range of motion...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/13/6/842 |
| _version_ | 1797484372037730304 |
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| author | Tanjulee Siddique Raouf Fareh Mahmoud Abdallah Zaina Ahmed Mohammad Habibur Rahman |
| author_facet | Tanjulee Siddique Raouf Fareh Mahmoud Abdallah Zaina Ahmed Mohammad Habibur Rahman |
| author_sort | Tanjulee Siddique |
| collection | DOAJ |
| description | In this paper, an autonomous exercise generation system based of fuzzy logic approach is presented. This work attempts to close a gap in the design of a completely autonomous robotic rehabilitation system that can recommend exercises to patients based on their data, such as shoulder range of motion (ROM) and muscle strength, from a pre-set library of exercises. The input parameters are fed into a system that uses Mamdani-style fuzzy logic rules to process them. In medical applications, the rationale behind decision making is a sophisticated process that involves a certain amount of uncertainty and ambiguity. In this instance, a fuzzy-logic-based system emerges as a viable option for dealing with the uncertainty. The system’s rules have been reviewed by a therapist to ensure that it adheres to the relevant healthcare standards. Moreover, the system has been tested with a series of test data and the results obtained ensures the proposed idea’s feasibility. |
| first_indexed | 2024-03-09T23:02:34Z |
| format | Article |
| id | doaj.art-f985d078a6924ad782668759fb2dccff |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-03-09T23:02:34Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-f985d078a6924ad782668759fb2dccff2023-11-23T18:00:15ZengMDPI AGMicromachines2072-666X2022-05-0113684210.3390/mi13060842Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based ApproachTanjulee Siddique0Raouf Fareh1Mahmoud Abdallah2Zaina Ahmed3Mohammad Habibur Rahman4Department of Electrical and Electronics Engineering, University of Sharjah, Sharjah 27272, United Arab EmiratesDepartment of Electrical and Electronics Engineering, University of Sharjah, Sharjah 27272, United Arab EmiratesDepartment of Electrical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, CanadaDepartment of Physiotherapy, University of Sharjah, Sharjah 27272, United Arab EmiratesBiomedical/Mechanical Engineering Department, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USAIn this paper, an autonomous exercise generation system based of fuzzy logic approach is presented. This work attempts to close a gap in the design of a completely autonomous robotic rehabilitation system that can recommend exercises to patients based on their data, such as shoulder range of motion (ROM) and muscle strength, from a pre-set library of exercises. The input parameters are fed into a system that uses Mamdani-style fuzzy logic rules to process them. In medical applications, the rationale behind decision making is a sophisticated process that involves a certain amount of uncertainty and ambiguity. In this instance, a fuzzy-logic-based system emerges as a viable option for dealing with the uncertainty. The system’s rules have been reviewed by a therapist to ensure that it adheres to the relevant healthcare standards. Moreover, the system has been tested with a series of test data and the results obtained ensures the proposed idea’s feasibility.https://www.mdpi.com/2072-666X/13/6/842rehabilitationdecision-making systemfuzzy logicrange of motionstroke |
| spellingShingle | Tanjulee Siddique Raouf Fareh Mahmoud Abdallah Zaina Ahmed Mohammad Habibur Rahman Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach Micromachines rehabilitation decision-making system fuzzy logic range of motion stroke |
| title | Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach |
| title_full | Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach |
| title_fullStr | Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach |
| title_full_unstemmed | Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach |
| title_short | Autonomous Exercise Generator for Upper Extremity Rehabilitation: A Fuzzy-Logic-Based Approach |
| title_sort | autonomous exercise generator for upper extremity rehabilitation a fuzzy logic based approach |
| topic | rehabilitation decision-making system fuzzy logic range of motion stroke |
| url | https://www.mdpi.com/2072-666X/13/6/842 |
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