Tenghuan He

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In this paper, we propose a novel interface between drivers and in-vehicle devices by using steady-state visual evoked potential (SSVEP) of brain signals. The SSVEP is detected by a canonical correlation analysis (CCA) classifier and applied to turn on and turn off in-vehicle devices. The proposed interface is built and tested online in a driving simulator(More)
In this paper, we propose a novel driver-vehicle interface by using the event-related desynchronizations (ERD) and event-related synchronization (ERS) potentials induced by motor imagery in conjunction with alpha rhythm to interact with a vehicle. The alpha rhythm, which is recognized by using a linear discriminant analysis (LDA) classifier, is employed to(More)
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