Enhancing Classification Accuracy of Transhumeral Prosthesis: A Hybrid sEMG and fNIRS Approach

Limited non-invasive transhumeral prosthesis control exists due to the absence of signal sources on amputee residual muscles. This paper introduces a hybrid brain-machine interface (hBMI) that integrates surface electromyography (sEMG) and functional near-infrared spectroscopy (fNIRS) signals to ove...

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Bibliografiska uppgifter

Huvudupphov:	Neelum Yousaf Sattar, Zareena Kausar, Syed Ali Usama, Noman Naseer, Umer Farooq, Ahmed Abdullah, Syed Zahid Hussain, Umar Shahbaz Khan, Haroon Khan, Peyman Mirtaheri
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	IEEE 2021-01-01
Serie:	IEEE Access
Ämnen:	Classification accuracy fNIRS hybrid brain-machine interface sEMG transhumeral prosthesis
Länkar:	https://ieeexplore.ieee.org/document/9495771/
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