[2E1-GS-10] AI application

[2E1-GS-10-02] Phase Estimation Method by Pulse Waveform of Blood Pressure Using Beat-by-Beat Features

〇Yuki Sasaki¹, Shihori Uchida¹, Hirotaka Wada¹, Masayuki Koizumi¹, Yukiko Yanagawa¹, Hiroshi Nakajima¹ (1. OMRON Corporation)

Keywords:DeepLearning, Biosignal, MachineLearning, LSTM

The standard blood pressure monitor measures systolic blood pressure (SBP) and diastolic blood pressure (DBP) by using oscillometric method. The method measures blood pressure (BP) precisely by the variabilities in waveforms amplitude but sometimes vulnerable to noise. Recently, the novel method has been developed by employing the neural network based on the features of beat-by-beat waveforms. It classifies each beat into the one of the three different phases, presystolic, between systolic and diastolic, and after diastolic. It could use more information amount than the oscillometric method but still requires some improvements on its performance. In the study, we improved the novel method based on the phase estimation by employing the new features and the new architecture of the neural network. The experiments were conducted to investigate the performance of the developed method. According to the experimental results, the method improves the standard deviation of errors on both SBP and DBP.