Imperial College London
Alternate

DrDeren YusufBarsakcioglu

Faculty of Engineering, Department of Bioengineering

Research Associate
 
 
 
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Contact

 

deren.barsakcioglu10

 
 
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Location

 

U421Sir Michael Uren HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Barsakcioglu:2018:10.1109/BIOCAS.2018.8584659,
author = {Barsakcioglu, DY and Farina, D},
doi = {10.1109/BIOCAS.2018.8584659},
publisher = {IEEE},
title = {A real-time surface EMG decomposition system for non-invasive human-machine interfaces},
url = {http://dx.doi.org/10.1109/BIOCAS.2018.8584659},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Real-time surface EMG decomposition, to extract neural activity of spinal motor neurons, provides a non-invasive solution for establishing direct interfaces with the central nervous system. In this paper, we present a real-time EMG decomposition system, validate it through both synthetic and experimental high-density surface EMG (HD-sEMG) data, and demonstrate the system in an upper-limb prosthetic control scenario. The proposed system achieves (in real-time) median decomposition accuracy comparable to offline methods (within 0.5 %) with minimal utilisation of computational resources (x20 faster compared to the literature).
AU  - Barsakcioglu,DY
AU  - Farina,D
DO  - 10.1109/BIOCAS.2018.8584659
PB  - IEEE
PY  - 2018///
SN  - 2163-4025
TI  - A real-time surface EMG decomposition system for non-invasive human-machine interfaces
UR  - http://dx.doi.org/10.1109/BIOCAS.2018.8584659
UR  - http://hdl.handle.net/10044/1/70045
ER  -
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