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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.

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Volltext §
DOI: 10.5445/IR/1000060446
DOI: 10.1515/cdbme-2016-0153
Seitenaufrufe: 6
seit 26.09.2018
Downloads: 32
seit 25.10.2016
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2016
Sprache Englisch
Identifikator ISSN: 2364-5504
KITopen-ID: 1000060446
HGF-Programm 47.01.02 (POF III, 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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