Study of continuous blood pressure estimation based on pulse transit time, heart rate and photoplethysmography-derived hemodynamic covariates

2018 ◽  
Vol 41 (2) ◽  
pp. 403-413 ◽  
Author(s):  
Jingjie Feng ◽  
Zhongyi Huang ◽  
Congcong Zhou ◽  
Xuesong Ye
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Transit Time ◽  
Pulse Transit Time ◽  
Pressure Estimation ◽  
Blood Pressure Estimation ◽  
Continuous Blood Pressure

scholarly journals Combined Deep CNN–LSTM Network-based Multitasking Learning Architecture for Noninvasive Continuous Blood Pressure Estimation using Difference in ECG-PPG Features

2021 ◽  
Author(s):  
Da Un Jeong ◽  
Ki Moo Lim
Keyword(s):  
Blood Pressure ◽  
Pulse Transit Time ◽  
Patient Specific ◽  
Peak Time ◽  
Simultaneous Prediction ◽  
Deep Cnn ◽  
Pressure Estimation ◽  
The Difference ◽  
Blood Pressure Estimation ◽  
Continuous Blood Pressure

Abstract The pulse transit time (PTT), which is the difference between the R-peak time of the electrocardiogram (ECG) signal and the systolic peak of the photoplethysmography (PPG) signal, is an indicator that enables noninvasive and continuous blood pressure estimation. However, it is difficult to accurately measure the PTT from the ECG and PPG signals because they have inconsistent shapes owing to patient-specific physical characteristics, pathological conditions, and movements. Accordingly, complex preprocessing is required to estimate blood pressure based on PTT. In this paper, as an alternative solution, we propose a noninvasive continuous algorithm using the difference between the ECG and PPG as a new feature that can include PTT information. The proposed algorithm is a deep CNN–LSTM-based multitasking machine learning model that outputs simultaneous prediction results of systolic (SBP) and diastolic blood pressures (DBP). The prediction accuracies of SBP and DBP using the proposed model were 0.017±1.624 mmHg and 0.164±1.297 mmHg, respectively. This result corresponded to Grade A according to the BHS and AAMI standards, which are the validation standards for blood pressure measuring devices.

Wearable Cuff-less Blood Pressure Estimation at Home via Pulse Transit Time

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Venu Gopal Ganti ◽  
Andrew Carek ◽  
Brandi Nicole Nevius ◽  
James Heller ◽  
Mozziyar Etemadi ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Transit Time ◽  
Pulse Transit Time ◽  
Pressure Estimation ◽  
Blood Pressure Estimation ◽  
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