In the article the method of automated analysis of polysomnographic (PSG) study is described designed to detect sleep event named "sleep spindle". PSG study by its origin is rather long (8-12 hours) and because of that automation of its analysis is an actual problem. In the text the process of processing and analysis of PSG study is described stage by stage. The algorithm can be divided in to the following stages: selection of the window size and offset value for FFT, detection of dominant frequency for each interval, building the distribution of dominant frequencies (histogram), selecting the frequency value from all frequency range that probably will match the sleep spindles frequency. Following this from the preliminary selected intervals with the known values of dominant frequencies the ones are chosen which are correspond to the value of sleep spindles frequency. The last stage is the control of the condition of event duration. The description of the algorithm is illustrated with the real recording illustrations for each step.
Keywords: polysomnography, PSG, sleep spindles, sleep, sleep events, EEG
Method of an automatic recognition of sleep events is described. The method is based on analysis of amplitude histograms that are built on each of registered channels. The method is designed for sleep events, distinctive feature of which is expressed amplitude change that appears simultaneously on several channels. For example, "General body movement" and "Limbs movement" events. But this is not limited; method can be applied to other events, for example "Snore". Algorithm can be divided into three stages: histograms building and analysis, vertical analysis, results processing.
Keywords: PSG, sleep events, histogram, detection algorithm