Deep learning-based continuous arterial blood pressure monitoring system and method based on photoplethysmography and non-invasive blood pressure measurements

A deep learning-based continuous arterial blood pressure monitoring system using a photoplethysmography and a non-invasive blood pressure measurement value, the continuous arterial blood pressure monitoring system comprising:

• a data receiving unit configured to receive a photoplethysmography (PPG) measurement value and a non-invasive blood pressure measurement value of a patient whose blood pressure state is to be analyzed;
• a photoplethysmography analysis unit configured to acquire a primary arterial blood pressure waveform from the photoplethysmography measurement value using a first learning model;
• a derived variable extraction unit configured to extract a derived variable using the received non-invasive blood pressure measurement value;
• a non-invasive blood pressure analysis unit configured to input the extracted derived variable and the non-invasive blood pressure measurement value to a second learning model and extracts a second feature value;
• a blood pressure waveform prediction unit configured to input the primary arterial blood pressure waveform and the second feature values to a third learning model, and predict the continuous arterial blood pressure waveform;
• and
• a blood pressure state prediction unit configured to predict the blood pressure state of the patient using the predicted continuous arterial blood pressure waveform.