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Control scheme selection in human-machine-interfaces by analysis of activity signals

Doneit, Wolfgang; Mikut, Ralf; Liebetanz, David; Rupp, Rüdiger; Reischl, Markus

Abstract (englisch): Human-Machine Interfaces in rehabilitation engineering often use activity signals. Examples are electrical wheelchairs or prostheses controlled by means of muscle contractions. Activity signals are user-dependent and often reflect neurological weaknesses. Thus, not all users are able to operate the same control scheme in a robust manner. To avoid under- and overstraining, the interface ideally uses a control scheme which reflects the user’s control ability best. Therefore, we explored typical phenomena of activation signals. We derive criteria to quantify the user’s performance and abilities and present a routine which automatically selects and adapts one of three control schemes being best suited.

Zugehörige Institution(en) am KIT Institut für Angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2016
Sprache Englisch
Identifikator DOI: 10.1515/cdbme-2016-0153
ISSN: 2364-5504
URN: urn:nbn:de:swb:90-604467
KITopen ID: 1000060446
HGF-Programm 47.01.02; LK 01
Erschienen in Current directions in biomedical engineering
Band 2
Heft 1
Seiten 707-710
Schlagworte calibration, data quality, human-machine interfaces, rehabilitation engineering
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