2020
Subject Transfer Framework Based on Source Selection and Semi-Supervised Style Transfer Mapping for Semg Pattern Recognition
ICASSP 2020accepted
To construct subject-specific feature extractors and classifiers for a new subject using pooled datasets, overcoming intersubject variabilities is required. In this study, we investigate the efficiency of the proposed subject transfer framework, which applies a discriminability-based source selectio…