본 발명은 심전도와 근전도를 각각 이미지로 변환하고, 변환된 각 이미지를 멀티 스트림 합성곱 신경망(multi-stream CNN)에 입력하여 사용자를 식별하는 방법에 관한 것이다. 본 발명의 일 실시예에 따른 심전도와 근전도를 이용한 사용자 식별 방법은 사용자에 대한 1차원 심전도 및 근전도 신호를 획득하는 단계, 상기 심전도 및 근전도 신호를 2차원 이미지로 각각 변환하는 단계 및 상기 2차원 이미지를 멀티 스트림 합성곱 신경망에 입력하여 상기 사용자를 식별하는 단계를 포함하는 것을 특징으로 한다.
Provided is a method of identifying a user by converting an electrocardiogram (ECG) and an electromyogram (EMG) into images, respectively, and inputting each converted image to a multi-stream convolutional neural network (multi-stream CNN). According to an embodiment of the present disclosure, the user identification method using the ECG and the EMG includes acquiring one-dimensional ECG and EMG signals for a user, converting the ECG and EMG signals into two-dimensional images, respectively, and identifying a user by inputting the two-dimensional images to a multi-stream convolutional neural network (multi-stream CNN), respectively.
USER IDENTIFICATION METHOD USING ELECTROCARDIOGRAM AND ELECTROMYOGRAM
심전도와 근전도를 이용한 사용자 식별 방법
2023-10-12
Patent
Electronic Resource
Korean
IPC: | G06V / A61B DIAGNOSIS , Diagnostik / B60R Fahrzeuge, Fahrzeugausstattung oder Fahrzeugteile, soweit nicht anderweitig vorgesehen , VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR / G06T Bilddatenverarbeitung oder Bilddatenerzeugung allgemein , IMAGE DATA PROCESSING OR GENERATION, IN GENERAL |
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