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Surface EMG Statistical and Performance Analysis of Targeted-Muscle-Reinnervated (TMR) Transhumeral Prosthesis Users in Home and Laboratory Settings.
Wang, Bingbin; Hargrove, Levi; Bao, Xinqi; Kamavuako, Ernest N.
Afiliación
  • Wang B; Department of Engineering, King's College London, London WC2R 2LS, UK.
  • Hargrove L; Center for Bionic Medicine, the Shirley Ryan Ability, Chicago, IL 60611, USA.
  • Bao X; Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
  • Kamavuako EN; Department of Engineering, King's College London, London WC2R 2LS, UK.
Sensors (Basel) ; 22(24)2022 Dec 14.
Article en En | MEDLINE | ID: mdl-36560218
A pattern-recognition (PR)-based myoelectric control system is the trend of future prostheses development. Compared with conventional prosthetic control systems, PR-based control systems provide high dexterity, with many studies achieving >95% accuracy in the last two decades. However, most research studies have been conducted in the laboratory. There is limited research investigating how EMG signals are acquired when users operate PR-based systems in their home and community environments. This study compares the statistical properties of surface electromyography (sEMG) signals used to calibrate prostheses and quantifies the quality of calibration sEMG data through separability indices, repeatability indices, and correlation coefficients in home and laboratory settings. The results demonstrate no significant differences in classification performance between home and laboratory environments in within-calibration classification error (home: 6.33 ± 2.13%, laboratory: 7.57 ± 3.44%). However, between-calibration classification errors (home: 40.61 ± 9.19%, laboratory: 44.98 ± 12.15%) were statistically different. Furthermore, the difference in all statistical properties of sEMG signals is significant (p < 0.05). Separability indices reveal that motion classes are more diverse in the home setting. In summary, differences in sEMG signals generated between home and laboratory only affect between-calibration performance.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Miembros Artificiales Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Miembros Artificiales Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article Pais de publicación: Suiza