FIELD: medicine.
SUBSTANCE: invention relates to medicine, namely, to a method for registering emotional maladaptation based on a cardiorhythmogram. An ECG sensor is used in the implementation of the method. The sensor data is transmitted to a mobile application. Used therein is a pre-trained neural network algorithm for classifying cardiorhythmogram data, namely, classifying a sequence of RR intervals according to the maladaptation level labels based on the data generated when completing a questionnaire while recording an electrocardiogram and extracting a sequence of RR intervals of the heart rate therefrom. The cardiorhythmogram data used to train the algorithm is received from users presented with four groups of verbal characteristics. The characteristics describe emotions in accordance with the modality and activity level in relation to the four basic personal needs, namely safety, independence, achievement, and unity.
EFFECT: by measuring the variability of heart rate and analysing the resulting data using a neural network algorithm, negative human emotions are registered automatically based on cardiorhythmogram data using a pre-trained algorithm for classifying RR intervals according to the maladaptation level labels based on a database of a large amount of unique user records, wherein the emotional maladaptation markers do not need to be calibrated for a specific user.
1 cl, 4 dwg
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Authors
Dates
2022-05-18—Published
2020-12-04—Filed