Hybrid MI-SSSEP Paradigm for classifying left and right movement toward BCI for exoskeleton control

Authors
Lee, JaehyungCha, KabmunKim, HyungminChoi, JunhyukKim, ChoonghyunLee, Songjoo
Issue Date
2019-02-19
Publisher
IEEE
Citation
7th International Winter Conference on Brain-Computer Interface (BCI), pp.196 - 198
Abstract
The goal of this study was to compare decoding accuracy of left and right movement intention from electroencephalography (EEG) using three different types of paradigms: Motor Imagery (MI), Selective Attention (SA), and Hybrid task (HY)). Specifically, SA and HY are the Steady-State Somatosensory Evoked potential (SSSEP) paradigms which elicit brain responses to tactile stimulation. One subject participated in two sessions (Screening and Study session). In the screening session, resonance-like frequency of the subject was found at each hand while sitting on a chair. In the study session, the subject was asked to imagine either left of right hand open-close movement (MI task), to give selective attention to the vibrotactile stimulation (SA task), and to perform combined MI and SA task (HY) according to a randomly assigned directional cue. The accuracies of 3 paradigms were MI-left 65.8%, MI-right 69.2% (mean: 67.5%), SA-left 76.6%, SA-right 84.0% (mean: 80.3%) and HY-left 93.8%, HY-right 95.9% (mean: 94.9%). The method and results of the current study could be a basis for controlling the left and right movement direction of an exoskeleton robot using EEG.
ISSN
2572-7680
URI
https://pubs.kist.re.kr/handle/201004/114305
DOI
10.1109/IWW-BCI.2019.8737319
Appears in Collections:
KIST Conference Paper > 2019
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