Online detection of REM sleep based on the comprehensive evaluation of short adjacent EEG segments by artificial neural networks
M Groezinger, C Wolf, T Uhl, C Schäffner… - Progress in Neuro …, 1997 - Elsevier
1. For scientific and clinical requirements the present objective is a robust automatic online
algorithm to detect rapid eye movement (REM) steep from single channel sleep EEG data
without using EMG or EOG information. 2. 2. For data preprocessing 20 seconds time
periods of the continuous EEG activity are digitally filtered in 7 frequency bands. Then the
RMS values of these filtered signals are calculated along segments of 2.5 seconds. The
resulting matrix of RMS values is representing information on the power of the signal …
algorithm to detect rapid eye movement (REM) steep from single channel sleep EEG data
without using EMG or EOG information. 2. 2. For data preprocessing 20 seconds time
periods of the continuous EEG activity are digitally filtered in 7 frequency bands. Then the
RMS values of these filtered signals are calculated along segments of 2.5 seconds. The
resulting matrix of RMS values is representing information on the power of the signal …
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