METHOD FOR DETERMINING SLEEP PHASE IN LONG-TERM EEG RECORDING Russian patent published in 2021 - IPC G16H50/00 A61B5/00 

FIELD: computing technology.

SUBSTANCE: proposed is a computer-implemented method for determining the sleep phase in a long-term EEG recording, containing a preparatory stage whereat: at least one EEG signal from the database preprocessed, at least one channel is filtered, at least one epoch is isolated from at least one EEG signal and channel-by-channel normalisation is performed; the first neural network is trained, at the input whereof at least one epoch of at least one EEG signal is supplied, wherein at least two channels common to all subjects are used, wherein features from at least one epoch of at least one EEG signal are automatically extracted by applying a one-dimensional convolutional layer with a large filter size and applying at least one convolutional block providing a greater abstraction level; the obtained features are combined into input sequences, wherein a sequence consists of the current epoch and at least one previous epoch of the first neural network; each epoch is divided into equal parts by the length of the segment, and for each segment, in each channel the power of the signal in the alpha range is calculated, the obtained features are added to the input sequence; the second neural network is trained, to the input whereof the input sequence obtained at the previous stage is supplied to determine the temporal dynamics of the correlation between the epochs. The method also comprises a working stage, whereat: the first and second neural networks trained at the previous stage are initialised, at least one epoch of at least one EEG signal is supplied to the input of the first neural network, the input sequence obtained from the first neural network and containing features calculated based on the power of the signal in the alpha range is then supplied to the input of the second neural network; classification of at least one epoch of at least one EEG signal is performed to determine the probability of attribution of at least one epoch to at least one sleep phase; the results of the classification are output.

EFFECT: invention provides improved accuracy of classification of an EEG signal according to the sleep phases.

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