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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書誌詳細

出版年:	IEEE Access
主要な著者:	Neelum Yousaf Sattar, Zareena Kausar, Syed Ali Usama, Noman Naseer, Umer Farooq, Ahmed Abdullah, Syed Zahid Hussain, Umar Shahbaz Khan, Haroon Khan, Peyman Mirtaheri
フォーマット:	論文
言語:	英語
出版事項:	IEEE 2021-01-01
主題:	Classification accuracy fNIRS hybrid brain-machine interface sEMG transhumeral prosthesis
オンライン･アクセス:	https://ieeexplore.ieee.org/document/9495771/