DocumentCode :
3728446
Title :
Game-Based BCI Training: Interactive Design for Individuals with Cerebral Palsy
Author :
Reinhold Scherer;Andreas Schwarz; M?ller-Putz;Viktoria Pammer-Schindler;Mariano Lloria Garcia
Author_Institution :
Inst. of Knowledge Discovery, Graz Univ. of Technol., Graz, Austria
fYear :
2015
Firstpage :
3175
Lastpage :
3180
Abstract :
Mutual brain-machine co-adaptation is the most common approach used to gain control over spontaneous electroencephalogram (EEG) based brain-computer interfaces (BCIs). Co-adaptation means the concurrent or alternating use of machine learning and the brain´s reinforcement learning mechanisms. Results from the literature, however, suggest that current implementations of this approach does not lead to desired results ("BCI inefficiency"). In this paper, we propose an alternative strategy that implements some recommendations from educational psychology and instructional design. We present a jigsaw puzzle game for Android devices developed to train the BCI skill in individuals with cerebral palsy (CP). Preliminary results of a supporting study in four CP users suggest high user acceptance. Three out of the four users achieved better than chance accuracy in arranging pieces to form the puzzle.
Keywords :
"Training","Electroencephalography","Brain modeling","Predictive models","Switches","Calibration","Timing"
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/SMC.2015.551
Filename :
7379683
Link To Document :
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