Hybrid MI-SSSEP Paradigm for classifying left and right movement toward BCI for exoskeleton control
Jaehyung Lee, Kab-Mun Cha, Hyungmin Kim, Junhyuk Choi, Kim Choong-Hyun, Song-Joo Lee
- 发表年份
- 2019
- 引用次数
- 8
摘要
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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002