Imperial College London
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ProfessorDarioFarina

Faculty of Engineering, Department of Bioengineering

Chair in Neurorehabilitation Engineering
 
 
 
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Contact

 

+44 (0)20 7594 1387d.farina Website

 
 
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Location

 

RSM 4.15Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Hahne:2020:10.3389/fnins.2020.00600,
author = {Hahne, JM and Wilke, MA and Koppe, M and Farina, D and Schilling, AF},
doi = {10.3389/fnins.2020.00600},
journal = {Frontiers in Neuroscience},
pages = {1--8},
title = {Longitudinal case study of regression-based hand prosthesis control in daily life},
url = {http://dx.doi.org/10.3389/fnins.2020.00600},
volume = {14},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Hand prostheses are usually controlled by electromyographic (EMG) signals from the remnant muscles of the residual limb. Most prostheses used today are controlled with very simple techniques using only two EMG electrodes that allow to control a single prosthetic function at a time only. Recently, modern prosthesis controllers based on EMG classification, have become clinically available, which allow to directly access more functions, but still in a sequential manner only. We have recently shown in laboratory tests that a regression-based mapping from EMG signals into prosthetic control commands allows for a simultaneous activation of two functions and an independent control of their velocities with high reliability. Here we aimed to study how such regression-based control performs in daily life in a two-month case study. The performance is evaluated in functional tests and with a questionnaire at the beginning and the end of this phase and compared with the participant’s own prosthesis, controlled with a classical approach. Already 1 day after training of the regression model, the participant with transradial amputation outperformed the performance achieved with his own Michelangelo hand in two out of three functional metrics. No retraining of the model was required during the entire study duration. During the use of the system at home, the performance improved further and outperformed the conventional control in all three metrics. This study demonstrates that the high fidelity of linear regression-based prosthesis control is not restricted to a laboratory environment, but can be transferred to daily use.
AU  - Hahne,JM
AU  - Wilke,MA
AU  - Koppe,M
AU  - Farina,D
AU  - Schilling,AF
DO  - 10.3389/fnins.2020.00600
EP  - 8
PY  - 2020///
SN  - 1662-453X
SP  - 1
TI  - Longitudinal case study of regression-based hand prosthesis control in daily life
T2  - Frontiers in Neuroscience
UR  - http://dx.doi.org/10.3389/fnins.2020.00600
UR  - https://www.frontiersin.org/articles/10.3389/fnins.2020.00600/full
UR  - http://hdl.handle.net/10044/1/82326
VL  - 14
ER  -
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