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Blood Pressure Estimation with a Wristband Optical Sensor

Published: 08 October 2018 Publication History

Abstract

UPDATED---August 17, 2018. Blood pressure (BP) is the most commonly performed medical office test. We developed a system that uses exclusively wristband-collected photoplethysmogram (PPG) to estimate BP. A dataset was collected and annotated during daily activities of 22 subjects. Preprocessing was applied to remove the signal noise and artefacts. Signal was segmented into cycles and features were computed. The RReliefF algorithm was used to select a subset of relevant features. The approach was validated with a person-independent leave-one-subject-out (LOSO) experiment. The LOSO experiment was updated with personalization to improve the results. The lowest mean absolute error (MAE) was 6.70 mmHg for systolic and 4.42 for diastolic BP. Ensemble of regression trees achieved the best results, which borderline meet the requirements set by two standards for BP estimation devices.

References

[1]
Y. Kurylyak, F. Lamonaca, and D. Grimaldi. 2013. A Neural Network-based method for continuous blood pressure estimation from a PPG signal. In 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 280--283.
[2]
Q. Li and G. D. Clifford. 2012. Dynamic time warping and machine learning for signal quality assessment of pulsatile signals. Physiological Measurement 33, 9 (2012).
[3]
J. Lázaro, E. Gil, J. M. Vergara, and P. Laguna. 2014. Pulse Rate Variability Analysis for Discrimination of Sleep-Apnea-Related Decreases in the Amplitude Fluctuations of Pulse Photoplethysmographic Signal in Children. IEEE Journal of Biomedical and Health Informatics 18, 1 (2014).
[4]
C. C. Y. Poon and Y. T. Zhang. 2005. Cuff-less and Noninvasive Measurements of Arterial Blood Pressure by Pulse Transit Time. In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. 5877--5880.
[5]
X. F. Teng and Y. T. Zhang. 2003. Continuous and noninvasive estimation of arterial blood pressure using a photoplethysmographic approach. In Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439), Vol. 4. 3153--3156 Vol.4.

Cited By

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  • (2022)Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG SignalsBioMed Research International10.1155/2022/80943512022:1Online publication date: Oct-2022
  • (2020)HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive PopulationArtificial Intelligence in Medicine10.1007/978-3-030-59137-3_29(325-335)Online publication date: 25-Aug-2020
  • (2019)pH Watch - Leveraging Pulse Oximeters in Existing Wearables for Reusable, Real-time Monitoring of pH in SweatProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3326105(262-274)Online publication date: 12-Jun-2019

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cover image ACM Conferences
UbiComp '18: Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
October 2018
1881 pages
ISBN:9781450359665
DOI:10.1145/3267305
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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New York, NY, United States

Publication History

Published: 08 October 2018

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Author Tags

  1. blood pressure
  2. photplethysmogram
  3. regression
  4. signal preprocessing

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  • Short-paper
  • Research
  • Refereed limited

Funding Sources

  • European Union?s Horizon 2020 research and innovation programme

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UbiComp '18
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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

View all
  • (2022)Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG SignalsBioMed Research International10.1155/2022/80943512022:1Online publication date: Oct-2022
  • (2020)HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive PopulationArtificial Intelligence in Medicine10.1007/978-3-030-59137-3_29(325-335)Online publication date: 25-Aug-2020
  • (2019)pH Watch - Leveraging Pulse Oximeters in Existing Wearables for Reusable, Real-time Monitoring of pH in SweatProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3326105(262-274)Online publication date: 12-Jun-2019

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