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

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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Bibliographic Details
Main Authors: Neelum Yousaf Sattar, Zareena Kausar, Syed Ali Usama, Noman Naseer, Umer Farooq, Ahmed Abdullah, Syed Zahid Hussain, Umar Shahbaz Khan, Haroon Khan, Peyman Mirtaheri
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Classification accuracy
fNIRS
hybrid brain-machine interface
sEMG
transhumeral prosthesis
Online Access:https://ieeexplore.ieee.org/document/9495771/

Internet

https://ieeexplore.ieee.org/document/9495771/

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