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Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals
2016
PLoS ONE
Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS) for developing Brain-Computer Interface (BCI) by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multichannel fNIRS signals using support-vector machines (SVM), so as to determine its feasibility as an online neurofeedback system. Towards
doi:10.1371/journal.pone.0159959
pmid:27467528
pmcid:PMC4965045
fatcat:j3mkik4ejngoroaw47jlg5dheu