No abstract

ECoG promises exact localization of brain sources by providing high spatial resolution and good signal quality, thus makes it the premier choice for future BCI applications. Unfortunately decoding these signals is not as straightforward as one would expect. In this work we applied a time-frequency analysis based on Empirical Mode decomposition (EMD) and Adaptive Filtering (AF) to decode and estimate the finger movement using 10 minutes-long, multi-channel ECoG signals. The dataset was recorded from three epileptic patients at Harborview Hospital in Seattle, Washington for Brain Computer Interface (BCI) Competition IV. Our proposed method showed the average correlation of 0.55 between real and predicted movement across the subjects and across fingers.

Abstract-The spatio-temporal oscillations in EEG waves are indicative of sensory and cognitive processing. We propose a method to find the spatial amplitude patterns of a timelimited waveform across multiple EEG channels. It consists of a single iteration of multichannel matching pursuit where the base waveform is obtained via the Hilbert transform of a time-limited tone. The vector of extracted amplitudes across channels is used for classification, and we analyze the effect of deviation in temporal alignment of the waveform on classification performance. Results for a previously published dataset of 6 subjects show comparable results versus a more complicated criteria-based method.

No abstract

The Electroencephalogram (EEG) is a non-invasive technique used in the medical field to record and analyze brain activity. In particular, Brain Machine Interfaces (BMI) create this bridge between brain signals and the external world through prosthesis, visual interfaces and other physical devices. This paper investigates the relation between particular hand movement directions while using a BMI and the EEG recordings during such movement. The Common Spatial Pattern method (CSP) over the high-γ frequency band is utilized in order to discriminate opposite hand movement directions. The experiment is performed with three subjects and the average classification accuracy is obtained for two different cases.