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EEG-BCIs have been well studied in the past decades and implemented intoseveral famous applications, like P300 speller and wheelchair controller.However, these interfaces are indirect due to low spatial resolution of EEG.Recently, direct ECoG-BCIs attract intensive attention because ECoG provides ahigher spatial resolution and signal quality. This makes possible localizationof the source of neural signals with respect to certain brain functions. Inthis article, we present a realization of ECoG-BCIs for finger flexionprediction provided by BCI competition IV. Methods for finger flexionprediction including feature extraction and selection are provided in thisarticle. Results show that the predicted finger movement is highly correlatedwith the true movement when we use band-specific amplitude modulation.

Decoding Finger Flexion using amplitude modulation from band-specific ECoG