SHMID Aleksandr Viktorovich (RU),ШМИД Александр Викторович (RU),BEREZIN Andrej Aleksandrovich (RU),БЕРЕЗИН Андрей Александрович (RU),NOVOPASHIN Maksim Aleksandrovich (RU),НОВОПАШИН Максим Александрови
申请号：
RU2019127394
公开号：
RU0002728869C1
申请日:
2019.08.30
申请国别(地区):
RU
年份:
2020
代理人:
摘要：
FIELD: medicine.SUBSTANCE: group of inventions relates to medicine, specifically to computerized methods for non-invasive detection of carbohydrate metabolism disorders (CMD) by cardiac electrocardiogram (ECG), population screening for detecting individuals with CMD signs by their ECG, as well as monitoring the level of the patient's CMD by ECG. Heart is considered as an open non-linear self-oscillation system characterized by Fermi-Pasta-Ulam (FPU) self-return, and the ECG is a representation of a FPU automatic return. ECG is removed. Fourier transform of the recorded ECG is performed to obtain an amplitude Fourier spectrum. Fourier amplitude spectrum is discretised to obtain discrete form of initial form of Fourier amplitude spectrum (DECG). DECG is analysed by computer processing to detect the presence/absence of the cardiac CMD by establishing the similarity/difference with the DECG of the patients with the CMD from an annotated sample of ECG and DECG of the healthy patients from the annotated ECG sample. Presence of similarity of analysed DECG with DECG of patients with CMD and absence of similarity with DECG of healthy patients is a sign of CMD. Screening method further includes setting sensitivity targets and specificity for determining the minimum required number of ECG of one person being tested and a threshold value of the number of ECG with signs of an CMD for each age group of observation, exceeding which the presence of an CMD is recognized in the patients of the group. Population is screened by ECG data extraction and processing. Results are statistically analysed by determining from the minimum required ECG number of one analysed ECG count with the CMD feature and comparing it with the preset threshold value. Monitoring method additionally involves accumulation in the database of the sequence of ECG recorded marked with patient identifiers. Degree of difference of the analysed DECG from the DECG of healthy people is calculated and used as an integral
