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Can transcranial direct current stimulation enhance performance of myoelectric control for multifunctional prosthesis? | IEEE Conference Publication | IEEE Xplore

Can transcranial direct current stimulation enhance performance of myoelectric control for multifunctional prosthesis?


Abstract:

Pattern recognition based myoelectric control has been studied by many researchers. However, the classification accuracy was pretty low for amputees towards multifunction...Show More

Abstract:

Pattern recognition based myoelectric control has been studied by many researchers. However, the classification accuracy was pretty low for amputees towards multifunctional prosthesis control in practice. In this work, a novel method of transcranial direct current stimulation (tDCS) which can modulate brain activity was used to enhance performance for myoelectric prosthesis control. The pilot study was conducted on three able-bodied subjects and one transradial amputee. Surface electromyography (EMG) signals were acquired from both arms when performing eleven hand and wrist motions in pre-tDCS and post-tDCS sessions. Time domain (TD) features and linear discriminant analysis (LDA) classifier were adopted to process EMG. For the non-dominant hand of the healthy subjects, active anodal tDCS of the contralateral primary motor cortex was able to significantly improve average classification accuracy by 3.82% (p < 0.05), while sham tDCS could not have such effect (p > 0.05). For amputated (phantom) hand of the amputee, active anodal tDCS was able to significantly improve average classification accuracy by 12.56%, while sham tDCS could not have such effect. For the dominant hand and intact hand, the average classification accuracies were stable and not significantly improved using either active tDCS or sham tDCS. The results show that tDCS is a powerful noninvasive method to modulate brain function and enhance EMG classification performance especially for the amputated hand towards multifunctional prosthesis control. The method proposed has a huge potential to promote EMG pattern recognition based control scheme to clinical application.
Date of Conference: 26-30 August 2014
Date Added to IEEE Xplore: 06 November 2014
Electronic ISBN:978-1-4244-7929-0

ISSN Information:

PubMed ID: 25570761
Conference Location: Chicago, IL, USA

References

References is not available for this document.