Deep learning-based atrial fibrillation determination system using ppg signal detection ring

Abstract

A deep-learning-based atrial fibrillation determination system using a photoplethysmography (PPG) signal detection ring is provided. The system may include a server, the server may include a signal quality classification component configured to classify the quality of a PPG signal as good or bad by using a first deep learning model, and an atrial fibrillation determination component configured to determine, by using a second deep learning model, from the PPG signal, whether atrial fibrillation has occurred, wherein the PPG signal detection ring includes a plurality of sensors configured to simultaneously measure a plurality of PPG signals at different locations, each of the plurality of sensors includes a light source and a photoelectric conversion device, the PPG signal is measured using the PPG signal detection ring, the server receives the PPG signal from the PPG signal detection ring through a terminal, and the terminal includes a sensor selection component configured to select, from among the plurality of sensors, as a sensor for measuring the PPG signal, a sensor that has measured a test PPG signal having a highest signal quality among a plurality of test PPG signals.

Dependencies are inferred from the claim text.