FIELD: computing technology.
SUBSTANCE: invention relates to medicine and computing technology. A method is proposed, which is for automatic detection of focal epileptiform discharges in a long-term EEG recording containing: a) a preparatory stage wherein a computing apparatus is used to pre-process at least one EEG signal to receive input data, wherein at least one segment of the signal with a length of 1 second is isolated in said at least one EEG signal; at least one segment selected at the previous stage is marked in accordance with the existing markup of a specialist from the database; a neural network is trained, wherein at least one pair of segments of the EEG signal with a length of 1 second attributed to symmetrical channels and a tag corresponding to the first of the two symmetrical channels are simultaneously supplied to the input of the neural network; cross-validation is conducted to estimate the classification quality; the cutoff threshold for the predicted focal discharges by probability is selected, and b) a working stage, wherein the computing apparatus is used to pre-process at least one EEG signal, wherein at least one segment of the signal with a length of 1 second is isolated in said at least one EEG signal; the neural network trained in the previous stage is activated, wherein at least one pair of segments of the EEG signal with a length of 1 second attributed to symmetrical channels is supplied to the input of said network; an estimation of the probability of attribution of the first of the two symmetrical segments of the signal to the epileptiform class is obtained at the output; the obtained probabilities are cut according to the predetermined threshold, and a list of predicted focal epileptiform discharges is formed; a search is conducted for the localisation of the discharge source by means of automatic application of the predicted focal points to the map considering the standard location of the electrodes, and interpolation is performed to determine the distribution of focal epileptiform discharges.
EFFECT: provides a reduction in the time of detection of focal epileptiform discharges.
1 cl, 5 dwg, 2 tbl
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Authors
Dates
2021-08-12—Published
2020-06-05—Filed