| Autor: |
Ann M. Simon, Keira Newkirk, Laura A. Miller, Kristi L. Turner, Kevin Brenner, Michael Stephens, Levi J. Hargrove |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Frontiers in Rehabilitation Sciences, Vol 5 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2673-6861 |
| DOI: |
10.3389/fresc.2024.1345364 |
| Popis: |
IntroductionMyoelectric pattern recognition systems have shown promising control of upper limb powered prostheses and are now commercially available. These pattern recognition systems typically record from up to 8 muscle sites, whereas other control systems use two-site control. While previous offline studies have shown 8 or fewer sites to be optimal, real-time control was not evaluated.MethodsSix individuals with no limb absence and four individuals with a transradial amputation controlled a virtual upper limb prosthesis using pattern recognition control with 8 and 16 channels of EMG. Additionally, two of the individuals with a transradial amputation performed the Assessment for Capacity of Myoelectric Control (ACMC) with a multi-articulating hand and wrist prosthesis with the same channel count conditions.ResultsUsers had significant improvements in control when using 16 compared to 8 EMG channels including decreased classification error (p = 0.006), decreased completion time (p = 0.019), and increased path efficiency (p = 0.013) when controlling a virtual prosthesis. ACMC scores increased by more than three times the minimal detectable change from the 8 to the 16-channel condition.DiscussionThe results of this study indicate that increasing EMG channel count beyond the clinical standard of 8 channels can benefit myoelectric pattern recognition users. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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