Classification of EEG signals using multiple gait features based on Small-world Neural Network

Abstract

In this paper, a novel classification method among running, walking and standing by combining common spatial patterns (CSP) and the fastICA feature extraction method together and constructing a Small-world Neural Network(SWNN, for short) through the gait feature extracted is proposed. We conducted our experiments on a treadmill at 0km/h, 1.6km/h and 3km/h… (More)
DOI: 10.1109/URAI.2016.7734021

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