Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency
Abstract Children born with congenital upper limb absence exhibit consistent and distinguishable levels of biological control over their affected muscles, assessed through surface electromyography (sEMG). This represents a significant advancement in determining how these children might utilize sEMG-...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-82519-z |
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| author | Marcus A. Battraw Justin Fitzgerald Eden J. Winslow Michelle A. James Anita M. Bagley Wilsaan M. Joiner Jonathon S. Schofield |
| author_facet | Marcus A. Battraw Justin Fitzgerald Eden J. Winslow Michelle A. James Anita M. Bagley Wilsaan M. Joiner Jonathon S. Schofield |
| author_sort | Marcus A. Battraw |
| collection | DOAJ |
| description | Abstract Children born with congenital upper limb absence exhibit consistent and distinguishable levels of biological control over their affected muscles, assessed through surface electromyography (sEMG). This represents a significant advancement in determining how these children might utilize sEMG-controlled dexterous prostheses. Despite this potential, the efficacy of employing conventional sEMG classification techniques for children born with upper limb absence is uncertain, as these techniques have been optimized for adults with acquired amputations. Tuning sEMG classification algorithms for this population is crucial for facilitating the successful translation of dexterous prostheses. To support this effort, we collected sEMG data from a cohort of N = 9 children with unilateral congenital below-elbow deficiency as they attempted 11 hand movements, including rest. Five classification algorithms were used to decode motor intent, tuned with features from the time, frequency, and time–frequency domains. We derived the congenital feature set (CFS) from the participant-specific tuned feature sets, which exhibited generalizability across our cohort. The CFS offline classification accuracy across participants was 73.8% ± 13.8% for the 11 hand movements and increased to 96.5% ± 6.6% when focusing on a reduced set of five movements. These results highlight the potential efficacy of individuals born with upper limb absence to control dexterous prostheses through sEMG interfaces. |
| format | Article |
| id | doaj-art-f5dfc44388474382a9bbc05ccdd990b1 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-f5dfc44388474382a9bbc05ccdd990b12025-01-05T12:26:04ZengNature PortfolioScientific Reports2045-23222024-12-0114111810.1038/s41598-024-82519-zSurface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiencyMarcus A. Battraw0Justin Fitzgerald1Eden J. Winslow2Michelle A. James3Anita M. Bagley4Wilsaan M. Joiner5Jonathon S. Schofield6Department of Mechanical and Aerospace Engineering, University of CaliforniaDepartment of Biomedical Engineering, University of CaliforniaDepartment of Biomedical Engineering, University of CaliforniaShriners Children’s – Northern CaliforniaShriners Children’s – Northern CaliforniaDepartment of Neurobiology, Physiology and Behavior, University of CaliforniaDepartment of Mechanical and Aerospace Engineering, University of CaliforniaAbstract Children born with congenital upper limb absence exhibit consistent and distinguishable levels of biological control over their affected muscles, assessed through surface electromyography (sEMG). This represents a significant advancement in determining how these children might utilize sEMG-controlled dexterous prostheses. Despite this potential, the efficacy of employing conventional sEMG classification techniques for children born with upper limb absence is uncertain, as these techniques have been optimized for adults with acquired amputations. Tuning sEMG classification algorithms for this population is crucial for facilitating the successful translation of dexterous prostheses. To support this effort, we collected sEMG data from a cohort of N = 9 children with unilateral congenital below-elbow deficiency as they attempted 11 hand movements, including rest. Five classification algorithms were used to decode motor intent, tuned with features from the time, frequency, and time–frequency domains. We derived the congenital feature set (CFS) from the participant-specific tuned feature sets, which exhibited generalizability across our cohort. The CFS offline classification accuracy across participants was 73.8% ± 13.8% for the 11 hand movements and increased to 96.5% ± 6.6% when focusing on a reduced set of five movements. These results highlight the potential efficacy of individuals born with upper limb absence to control dexterous prostheses through sEMG interfaces.https://doi.org/10.1038/s41598-024-82519-z |
| spellingShingle | Marcus A. Battraw Justin Fitzgerald Eden J. Winslow Michelle A. James Anita M. Bagley Wilsaan M. Joiner Jonathon S. Schofield Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency Scientific Reports |
| title | Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency |
| title_full | Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency |
| title_fullStr | Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency |
| title_full_unstemmed | Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency |
| title_short | Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency |
| title_sort | surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency |
| url | https://doi.org/10.1038/s41598-024-82519-z |
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