Patent ID: 11877852
Assignee: INDUSTRY ACADEMIC COOPERATION FOUNDATION CHOSUN UNIVERSITY
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC A  G

Claim 4:
5. A computer-implemented method comprising:
measuring, by at least one computer processor, one or more instances of an electrocardiogram (ECG) signal categorized in sequentially input datasets, wherein each ECG signal is in either:
a first state in which the ECG signal is idle; or
a second state in which noise is generated;

extracting, by the at least one computer processor, one or more feature points of each measured ECG signal in the first state and in the second state, wherein extracted feature points comprise an R-peak value and an S-peak value of a respective ECG signal;
performing, by the at least one computer processor, K-means clustering on one or more instances the ECG signal in the first state or the second states based on extracted feature points and generating clustered ECG signals based on performed K-means clustering; and
classifying, by the at least one computer processor, stress experienced by a subject in the first state or the second state based on an R-peak value and an S-peak value calculated based on clustered ECG signals and training a long-short term memory (LTSM), a type of recurrent neural network (RNN), to recognize patterns in clustered ECG signals even when a distance between sequentially input datasets is relatively long.