Detection of cortical slow waves in the sleep EEG using a modified matching pursuit method with a restricted dictionary.

In this paper, an innovative knowledge-based methodological framework to detect sleep slow waves (SSW) in the human sleep electroencephalogram (EEG) is proposed. Based on a restricted matching pursuit (RMP) algorithm, automatic pattern recognition of SSW is implemented using a small dictionary of Gabor functions modeling the target waveform morphological characteristics. The method describes EEG signals in terms of SSW properties and provides detection thresholds based on the largest MP coefficients.

Automated detection of sleep EEG slow waves based on matching pursuit using a restricted dictionary.

In this paper, an original method to detect sleep slow waves (SSW) in electroencephalogram (EEG) recordings is proposed. This method takes advantage of a Matching Pursuit algorithm using a dictionary reduced to Gabor functions reproducing the main targeted waveform characteristics. By describing the EEG signals in terms of SSW properties, the corresponding algorithm is able to identify waveforms based on the largest matching coefficients.

On-line automatic detection of driver drowsiness using a single electroencephalographic channel.

In this paper, an on-line drowsiness detection algorithm using a single electroencephalographic (EEG) channel is presented. This algorithm is based on a means comparison test to detect changes of the alpha relative power ([8-12]Hz band). The main advantage of the method proposed is that the detection threshold is completely independent of drivers and does not need to be tuned for each person.