BCI Competitions III Result
Dataset IVa
Group information:
ZHOU zongtan, HU Dewen, LIU Yang
narcz@163.com
Algorithm description:
Preprocessing:
1) BP filter signals(3~28Hz) for every channel, every subject.
2) Get data of 3.5s length after every cue as trials.
3) compute CSP(Common Spatial Pattern) using training data,
then use it to reduce the dimensions from 118 channels to 12 channels.
Feature extracting:
1) compute continuous wavelet transformation(4~24Hz corresponded) of
every trials to generate a 2D time-frequency array.
2) compute a two samples t-Test statistic on every time-frequency point.
3) construct features using sum of the cwt coefficients weighted by the t-value.
Classifying:
classify using a linear discriminant analysis(LDA).