Signal Processing for Hybrid BCI Signals

EEG signal processing methods for BCI applications

Brain-computer interface (BCI) is a communication system that translates brain activity into commands for a computer or other digital device. The majority of BCI systems work by reading and interpreting cortically-evoked electro-potentials (“brain waves”) via an electroencephalogram (EEG) data. The EEG data is inherently complex. The signals are non-linear, non-stationary and therefore difficul...

Robust Classification of Electrocorticographic Signals for BCI

We examine the problem of classifying electrocorticographic changes during overt movement of two different body parts (tongue and hand) for designing closed-loop BCI control. We overcome the problem of extremely small training data sets via judicious feature selection and the use of powerful sparse classification methods (LPM). Our results show very high accuracy on quarter-second windows of da...

Signals and signal processing for the electrophysiologist: part II: signal processing and artifact.

Saturation Artifact If a 3-mV peak signal is being amplified at a gain of 5000, the final output will be 15 000 mV or 15 V; however, if the system supply voltage is limited to 10 V, the overall signal amplitude would be limited to about 9.5 V (slightly below the supply voltage). The signal would simply be cut off above 9.5 V, although the amplifiers would attempt to drive themselves up to the r...

Signal Processing of Random Physiological Signals

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Signal Processing of Discrete-time Signals