ABSTRACT
OBJECTIVE: We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. APPROACH: One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. MAIN RESULTS: Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. SIGNIFICANCE: Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.