A Measure to Detect Sleep Onset Using Statistical Analysis of Spike Rhythmicity

Preprocessing

The polysomnography datasets from which Electroencephalogram is extracted is acquired from the sleep laboratory of M S Ramaiah Hospitals. As the EEG changes during onset of sleep occur first in the occipital lobe of the brain, channels O1 and O2 are considered for the data acquisition process. The sampling frequency of the acquired data is 256 Hz used for feature extraction. The system that is used for the analysis of the data is Sandman analysis system, the portion of which utilizes Primo Burner Technology © 2003-2006 Primo software. For the proposed study, three subjects’ recordings are considered for analysis. EEG being a non-stationary signal is segmented into 1 second patterns by applying different windowing as discussed below.

• 1.

  Assuming that the given time series is divided into 1sec, there is no overlap between any two consecutive 1 second EEG patterns(SR1)

• 2.

  Retaining the first segmented 1 second pattern, a 50% overlap is introduced in such a manner that the second EEG pattern comprise of 0.5 sec i.e. half of first EEG pattern and first half of second EEG pattern of SR1(SR2).

• 3.

  The third and fourth windowing is based on 60% (SR3) and 75%(SR4) of the overlap. The procedure is same as discussed in (ii).