An idle state-detecting method based on transient visual evoked potentials for an asynchronous ERP-based BCI.

Journal of Neuroscience Methods
Minghong GongFang Lin

Abstract

An asynchronous brain-computer interface (BCI) allows subject to freely switch between the working state and the idle state, improving the subject's comfort. However, using only the event-related potential (ERP) to detect these two states is difficult because of the small amplitude of the ERP. Our previous study finds that an odd-ball paradigm could evoke transient visual evoked potentials (TSVEPs) simultaneously with ERPs. This study adopts the TSVEP and the ERP to detect the idle state in the design of an asynchronous TSVEP-ERP-based BCI (T-E BCI). The T-E BCI extracts time and frequency features from brain signals and uses a novel probability-based fisher linear discriminant analysis (P-FLDA) to combine the classification results of the ERP and the TSVEP. Ten subjects perform visual speller and video watching experiments, and their brain signals are measured under the working and idle states. The main results show that the T-E BCI achieves a higher accuracy than the ERP-based BCI when judging the subject's intentions and the two states. The P-FLDA performs better than the FLDA in combining the classification results. The study demonstrates that adding the TSVEP can substantially reduce the number of wrongly detected trials. ...Continue Reading

References

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Dec 4, 2019·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Jing JinAndrzej Cichocki

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