In this section
@article{Vujaklija:2017:10.3389/fnbot.2017.00007,
author = {Vujaklija, I and Roche, AD and Hasenoehrl, T and Sturma, A and Amsuess, S and Farina, D and Aszmann, O},
doi = {10.3389/fnbot.2017.00007},
journal = {Frontiers in Neurorobotics},
title = {Translating research on myoelectric control into clinics – are the performance assessment methods adequate?},
url = {http://dx.doi.org/10.3389/fnbot.2017.00007},
volume = {11},
year = {2017}
}
TY - JOUR
AB - Missing an upper limb dramatically impairs daily-life activities. Efforts in overcoming the issues arising from this disability have been made in both academia and industry, although their clinical outcome is still limited. Translation of prosthetic research into clinics has been challenging because of the difficulties in meeting the necessary requirements of the market. In this perspective article, we suggest that one relevant factor determining the relatively small clinical impact of myocontrol algorithms for upper limb prostheses is the limit of commonly used laboratory performance metrics. The laboratory conditions, in which the majority of the solutions are being evaluated, fail to sufficiently replicate real-life challenges. We qualitatively support this argument with representative data from seven transradial amputees. Their ability to control a myoelectric prosthesis was tested by measuring the accuracy of offline EMG signal classification, as a typical laboratory performance metrics, as well as by clinical scores when performing standard tests of daily living. Despite all subjects reaching relatively high classification accuracy offline, their clinical scores varied greatly and were not strongly predicted by classification accuracy. We therefore support the suggestion to test myocontrol systems using clinical tests on amputees, fully fitted with sockets and prostheses highly resembling the systems they would use in daily living, as evaluation benchmark. Agreement on this level of testing for systems developed in research laboratories would facilitate clinically relevant progresses in this field.
AU - Vujaklija,I
AU - Roche,AD
AU - Hasenoehrl,T
AU - Sturma,A
AU - Amsuess,S
AU - Farina,D
AU - Aszmann,O
DO - 10.3389/fnbot.2017.00007
PY - 2017///
SN - 1662-5218
TI - Translating research on myoelectric control into clinics – are the performance assessment methods adequate?
T2 - Frontiers in Neurorobotics
UR - http://dx.doi.org/10.3389/fnbot.2017.00007
UR - http://hdl.handle.net/10044/1/44799
VL - 11
ER -