scholarly journals A New Wearable Device for Blood Pressure Estimation Using Photoplethysmogram

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2557 ◽  
Author(s):  
Remo Lazazzera ◽  
Yassir Belhaj ◽  
Guy Carrault
Keyword(s):  
Blood Pressure ◽  
Real Time ◽  
American Association ◽  
Index Finger ◽  
Pulse Transit Time ◽  
Estimation Algorithm ◽  
Wearable Device ◽  
Medical Instrumentation ◽  
Blood Pressure Estimation ◽  
Pulse Oximeters

We present a novel smartwatch, CareUp ® , for estimating the Blood Pressure (BP) in real time. It consists of two pulse oximeters: one placed on the back and one on the front of the device. Placing the index finger on the front oximeter starts the acquisition of two photoplethysmograms (PPG); the signals are then filtered and cross-correlated to obtain a Time Delay between them, called Pulse Transit Time (PTT). The Heart Rate (HR) (estimated from the finger PPG) and the PTT are then input in a linear model to give an estimation of the Systolic and Diastolic BP. The performance of the smartwatch in measuring BP have been validated in the Institut Coeur Paris Centre Turin (ICPC), using a sphygmomanometer, on 44 subjects. During the validation, the measures of the CareUp ® were compared to those of two oscillometry-based devices already available on the market: Thuasne ® and Magnien ® . The results showed an accuracy comparable to the oscillometry-based devices and they almost agreed with the American Association for the Advancement of Medical Instrumentation standard for non-automated sphygmomanometers. The integration of the BP estimation algorithm in the smartwatch makes the CareUp ® an easy-to-use, wearable device for monitoring the BP in real time.

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 ◽  
At Home

scholarly journals Blood Pressure Estimation Using On-body Continuous Wave Radar and Photoplethysmogram in Various Posture and Exercise Conditions

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Malikeh Pour Ebrahim ◽  
Fatemeh Heydari ◽  
Taiyang Wu ◽  
Katherine Walker ◽  
Keith Joe ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Continuous Wave ◽  
Pulse Transit Time ◽  
Medical Monitoring ◽  
Body Contact ◽  
Radar Sensors ◽  
Wave Radar ◽  
Blood Pressure Estimation ◽  
Electrocardiogram Ecg ◽  
Pulse Arrival

Abstract The pulse arrival time (PAT), pre-ejection period (PEP) and pulse transit time (PTT) are calculated using on-body continuous wave radar (CWR), Photoplethysmogram (PPG) and Electrocardiogram (ECG) sensors for wearable continuous systolic blood pressure (SBP) measurements. The CWR and PPG sensors are placed on the sternum and left earlobe respectively. This paper presents a signal processing method based on wavelet transform and adaptive filtering to remove noise from CWR signals. Experimental data are collected from 43 subjects in various static postures and 26 subjects doing 6 different exercise tasks. Two mathematical models are used to calculate SBPs from PTTs/PATs. For 38 subjects participating in posture tasks, the best cumulative error percentage (CEP) is 92.28% and for 21 subjects participating in exercise tasks, the best CEP is 82.61%. The results show the proposed method is promising in estimating SBP using PTT. Additionally, removing PEP from PAT leads to improving results by around 9%. The CWR sensors present a low-power, continuous and potentially wearable system with minimal body contact to monitor aortic valve mechanical activities directly. Results of this study, of wearable radar sensors, demonstrate the potential superiority of CWR-based PEP extraction for various medical monitoring applications, including BP measurement.

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