PHOTOPLETHYSMOGRAPHY-BASED REAL-TIME BLOOD PRESSURE MONITORING SYSTEM USING CONVOLUTIONAL·BIDIRECTIONAL SHORT- AND LONG-TERM MEMORY RECURRENT NEURAL NETWORK, AND REAL-TIME BLOOD PRESSURE MONITORING METHOD USING SAME

摘要

The present invention relates to a photoplethysmography-based real-time blood pressure monitoring system using a convolutional·bidirectional short- and long-term memory recurrent neural network, and a real-time blood pressure monitoring method using same, and according to the present invention, there may be provided the photoplethysmography-based real-time blood pressure monitoring system using a convolutional·bidirectional short- and long-term memory recurrent neural network, the real-time blood pressure monitoring system comprising: a pulse wave measurement module for measuring photoplethysmography; and a blood pressure prediction server for receiving the measured photoplethysmography from the pulse wave measurement module and predicting blood pressure through the recurrent neural network. Also, there may be provided the real-time blood pressure monitoring method using the photoplethysmography-based real-time blood pressure monitoring system using a convolutional·bidirectional short- and long-term memory recurrent neural network, the real-time blood pressure monitoring method comprising: a measurement step for measuring photoplethysmography through the pulse wave measurement module; and a prediction step for predicting, by the blood pressure prediction server, blood pressure through the recurrent neural network by using the photoplethysmography.