Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke
Stroke is a leading cause of long-term disability in the United States. Recent studies have shown that high doses of repeated task-specific practice can be effective at improving upper-limb function at the chronic stage. Providing at-home telerehabilitation services with therapist supervision may al...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/5/1806 |
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| author | Octavio Marin-Pardo Coralie Phanord Miranda Rennie Donnelly Christopher M. Laine Sook-Lei Liew |
| author_facet | Octavio Marin-Pardo Coralie Phanord Miranda Rennie Donnelly Christopher M. Laine Sook-Lei Liew |
| author_sort | Octavio Marin-Pardo |
| collection | DOAJ |
| description | Stroke is a leading cause of long-term disability in the United States. Recent studies have shown that high doses of repeated task-specific practice can be effective at improving upper-limb function at the chronic stage. Providing at-home telerehabilitation services with therapist supervision may allow higher dose interventions targeted to this population. Additionally, muscle biofeedback to train patients to avoid unwanted simultaneous activation of antagonist muscles (co-contractions) may be incorporated into telerehabilitation technologies to improve motor control. Here, we present the development and feasibility of a low-cost, portable, telerehabilitation biofeedback system called Tele-REINVENT. We describe our modular electromyography acquisition, processing, and feedback algorithms to train differentiated muscle control during at-home therapist-guided sessions. Additionally, we evaluated the performance of low-cost sensors for our training task with two healthy individuals. Finally, we present the results of a case study with a stroke survivor who used the system for 40 sessions over 10 weeks of training. In line with our previous research, our results suggest that using low-cost sensors provides similar results to those using research-grade sensors for low forces during an isometric task. Our preliminary case study data with one patient with stroke also suggest that our system is feasible, safe, and enjoyable to use during 10 weeks of biofeedback training, and that improvements in differentiated muscle activity during volitional movement attempt may be induced during a 10-week period. Our data provide support for using low-cost technology for individuated muscle training to reduce unintended coactivation during supervised and unsupervised home-based telerehabilitation for clinical populations, and suggest this approach is safe and feasible. Future work with larger study populations may expand on the development of meaningful and personalized chronic stroke rehabilitation. |
| first_indexed | 2024-03-09T05:22:05Z |
| format | Article |
| id | doaj.art-5369d7326e3841ad96524ab5c58b0c0a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T05:22:05Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5369d7326e3841ad96524ab5c58b0c0a2023-12-03T12:39:22ZengMDPI AGSensors1424-82202021-03-01215180610.3390/s21051806Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic StrokeOctavio Marin-Pardo0Coralie Phanord1Miranda Rennie Donnelly2Christopher M. Laine3Sook-Lei Liew4Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 900089, USAChan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 900089, USAChan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 900089, USAChan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 900089, USADepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 900089, USAStroke is a leading cause of long-term disability in the United States. Recent studies have shown that high doses of repeated task-specific practice can be effective at improving upper-limb function at the chronic stage. Providing at-home telerehabilitation services with therapist supervision may allow higher dose interventions targeted to this population. Additionally, muscle biofeedback to train patients to avoid unwanted simultaneous activation of antagonist muscles (co-contractions) may be incorporated into telerehabilitation technologies to improve motor control. Here, we present the development and feasibility of a low-cost, portable, telerehabilitation biofeedback system called Tele-REINVENT. We describe our modular electromyography acquisition, processing, and feedback algorithms to train differentiated muscle control during at-home therapist-guided sessions. Additionally, we evaluated the performance of low-cost sensors for our training task with two healthy individuals. Finally, we present the results of a case study with a stroke survivor who used the system for 40 sessions over 10 weeks of training. In line with our previous research, our results suggest that using low-cost sensors provides similar results to those using research-grade sensors for low forces during an isometric task. Our preliminary case study data with one patient with stroke also suggest that our system is feasible, safe, and enjoyable to use during 10 weeks of biofeedback training, and that improvements in differentiated muscle activity during volitional movement attempt may be induced during a 10-week period. Our data provide support for using low-cost technology for individuated muscle training to reduce unintended coactivation during supervised and unsupervised home-based telerehabilitation for clinical populations, and suggest this approach is safe and feasible. Future work with larger study populations may expand on the development of meaningful and personalized chronic stroke rehabilitation.https://www.mdpi.com/1424-8220/21/5/1806biofeedbackstroketelerehabilitationelectromyographyhuman-computer interface |
| spellingShingle | Octavio Marin-Pardo Coralie Phanord Miranda Rennie Donnelly Christopher M. Laine Sook-Lei Liew Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke Sensors biofeedback stroke telerehabilitation electromyography human-computer interface |
| title | Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke |
| title_full | Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke |
| title_fullStr | Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke |
| title_full_unstemmed | Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke |
| title_short | Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke |
| title_sort | development of a low cost modular muscle computer interface for at home telerehabilitation for chronic stroke |
| topic | biofeedback stroke telerehabilitation electromyography human-computer interface |
| url | https://www.mdpi.com/1424-8220/21/5/1806 |
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