Systolic blood pressure estimation using wearable radar and photoplethysmogram signals

Ebrahim, M. P.; Heydari, F.; Walker, K.; Joe, K.; Redouté, Jean-Michel; Yuce, M. R.

doi:10.1109/SMC.2019.8914567

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Systolic blood pressure estimation using wearable radar and photoplethysmogram signals

Ebrahim, M. P.; Heydari, F.; Walker, K. et al.

2019 • In Conference Proceedings. IEEE International Conference on Systems, Man, and Cybernetics, 2019-October, p. 3878-3882

Peer reviewed

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https://hdl.handle.net/2268/248069

DOI
10.1109/SMC.2019.8914567

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Keywords :

Blood; Blood pressure; Continuous wave radar; Electrocardiography; Regression analysis; Wavelet transforms; Cumulative errors; Electrocardiogram (ECG) sensors; Noise components; Photo-plethysmogram; Pulse arrival time; Pulse transit time; Regression method; Systolic blood pressure; Wearable sensors

Abstract :

[en] On-body Continuous Wave Radar (CWR) sensors, along with Photoplethysmogram (PPG) and Electrocardiogram (ECG) sensors, have been introduced to estimate blood pressure(BP) using time parameters as Pulse Arrival Time (PAT), Pre-ejection Period (PEP) and Pulse Transit Time (PTT) during different postures and exercises tasks. The wavelet transform is applied to the signals to remove the noise components. The on-body CWR sensor and PPG sensor are placed on the sternum and left earlobe, respectively. The time parameters of 43 healthy subjects are collected in the different sitting, standing, and supine postures, and also for 26 healthy subjects in six different exercise tasks as handgrip, light, moderate and heavy bike exercise, and two recoveries. Two different regression methods are used to estimate BP from PTT and the results are compared with the estimated BP from PAT. The best Cumulative Error Percentage (<10mmHg) is 98.2% for 38 subjects, participated in posture tasks and 88.89% for 21 subjects, participated in exercise tasks. The results show the proposed method is promising for estimating BP using PTT obtained from radar and PPG signals. © 2019 IEEE.

Disciplines :

Electrical & electronics engineering

Author, co-author :

Ebrahim, M. P.; Monash University, Department of Electrical and Computer Systems Engineering, Melbourne, Australia

Heydari, F.; Monash University, Department of Electrical and Computer Systems Engineering, Melbourne, Australia

Walker, K.; Cabrini Health, Emergency Department, Melbourne, Australia

Joe, K.; Cabrini Health, Emergency Department, Melbourne, Australia

Redouté, Jean-Michel ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes microélectroniques intégrés

Yuce, M. R.; Monash University, Department of Electrical and Computer Systems Engineering, Melbourne, Australia

Language :

English

Title :

Systolic blood pressure estimation using wearable radar and photoplethysmogram signals

Publication date :

2019

Event name :

2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019

Event date :

6 October 2019 through 9 October 2019

Audience :

International

Journal title :

Conference Proceedings. IEEE International Conference on Systems, Man, and Cybernetics

ISSN :

1062-922X

eISSN :

2577-1655

Publisher :

Institute of Electrical and Electronics Engineers Inc.

Volume :

2019-October

Pages :

3878-3882

Peer reviewed :

Peer reviewed

Name of the research project :

ARC: LP160101823

Funders :

ARC - Australian Research Council [AU]

Commentary :

155660 9781728145693

Available on ORBi :

since 06 June 2020

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Bibliography

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