Identification of forearm skin zones with similar muscle activation patterns during activities of daily living
Impacte
Scholar |
Altres documents de l'autoria: Jarque-Bou, Néstor J; Vergara, Margarita; Sancho-Bru, Joaquin L.; Roda-Sales, Alba; Gracia-Ibáñez, Verónica
Metadades
Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7035
comunitat-uji-handle3:10234/8617
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INVESTIGACIONMetadades
Títol
Identification of forearm skin zones with similar muscle activation patterns during activities of daily livingAutoria
Data de publicació
2018-10Editor
BMCCita bibliogràfica
JARQUE-BOU, Néstor J., et al. Identification of forearm skin zones with similar muscle activation patterns during activities of daily living. Journal of neuroengineering and rehabilitation, 2018, 15.1: 91.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-018-0437-0Versió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
Background
A deeper knowledge of the activity of the forearm muscles during activities of daily living (ADL) could help to better understand the role of those muscles and allow clinicians to treat motor dysfunctions ... [+]
Background
A deeper knowledge of the activity of the forearm muscles during activities of daily living (ADL) could help to better understand the role of those muscles and allow clinicians to treat motor dysfunctions more effectively and thus improve patients’ ability to perform activities of daily living.
Methods
In this work, we recorded sEMG activity from 30 spots distributed over the skin of the whole forearm of six subjects during the performance of 21 representative simulated ADL from the Sollerman Hand Function Test. Functional principal component analysis and hierarchical cluster analysis (HCA) were used to identify forearm spots with similar muscle activation patterns.
Results
The best classification of spots with similar activity in simulated ADL consisted in seven muscular-anatomically coherent groups: (1) wrist flexion and ulnar deviation; (2) wrist flexion and radial deviation; (3) digit flexion; (4) thumb extension and abduction/adduction; (5) finger extension; (6) wrist extension and ulnar deviation; and (7) wrist extension and radial deviation.
Conclusion
The number of sEMG sensors could be reduced from 30 to 7 without losing any relevant information, using them as representative spots of the muscular activity of the forearm in simulated ADL. This may help to assess muscle function in rehabilitation while also simplifying the complexity of prosthesis control. [-]
Proyecto de investigación
Spanish MINECO (project DPI2014-52095-P) ; European Union (FEDER funds) (FPI grant BES-2015-072480)Drets d'accés
© The Author(s). 2018
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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