1247846
doi
10.5281/zenodo.1247846
oai:zenodo.org:1247846
user-eu
Pattern recognition myoelectric control: Evaluating EMG pattern separability
Franzke, AW; Kristoffersen, MB, Murgia, A; Sluis, CK van der; Bongers, RM,
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
machine learning control
pattern recognition control
emg pattern
myoelectric control
upper limb myoelectric prostheses
<p>Pattern recognition based myoelectric control for upper limb prostheses has gained increasing attention in the last years as it seems to offer more intuitive control than conventional, direct control. However, for such control to be feasible, the prosthesis user needs to have sufficient control of muscle contractions to create EMG patterns suitable for pattern classification. Few studies have investigated the relation between control ability and EMG pattern characteristics and an evaluation tool for quality of EMG patterns is still missing. We proposed such a tool and investigated whether scores from this tool were related to EMG pattern control ability.</p>
<p>This poster was presented during the 2nd international symposium on innovations in amputations surgery and prosthetic technologies in Vienna, May 10-12, 2018.</p>
Zenodo
2018-05-12
info:eu-repo/semantics/conferencePoster
1247845
user-eu
award_title=Intuitive Natural Prosthesis UTilization; award_number=687795; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/687795; funder_id=00k4n6c32; funder_name=European Commission;
1579542083.501734
5430344
md5:3e4accdcaa4efc9da89d99a01200dcd2
https://zenodo.org/records/1247846/files/Poster IASPT.jpg
public
10.5281/zenodo.1247845
isVersionOf
doi