Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89302
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Title: Virtual hand rehabilitation with force guidance adaptable to mental states using brain-computer interface
Authors: Choi, KS 
Issue Date: 2019
Source: The 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 2019), Biomedical Engineering Ranging from Wellness to Intensive Care Medicine, 23-27 July, Berlin, Germany, WePOS-30.28, p. 1 (Poster)
Abstract: This paper presents a virtual hand dexterity training system where force guidance is activated autonomously in real time depending on the mental states of user, which are determined by electroencephalogram (EEG) signals acquired using brain-computer interface (BCI). In the context of handwriting, when EEG signals suggests a certain level of frustration, assistive forces are produced as an aid to completing the desired strokes. The study provides insights toward the development of intelligent rehabilitation system with automated guidance and natural user interface for self-paced practice.
Rights: Posted with permission of the author.
Appears in Collections:Conference Paper

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