research-article

Smart phone based blood pressure indicator

Authors:

Aishwarya Visvanathan,

Rohan Banerjee,

Anirban Dutta Choudhury,

Aniruddha Sinha, and

Shaswati KunduAuthors Info & Claims

MobileHealth '14: Proceedings of the 4th ACM MobiHoc workshop on Pervasive wireless healthcare

August 2014

Pages 19 - 24

https://doi.org/10.1145/2633651.2633657

Published: 11 August 2014 Publication History

Abstract

In this paper, we propose a methodology to estimate the range of human blood pressure (BP) using Photoplethysmography (PPG). 12 time domain features and 7 frequency domain features are pointed out and extracted from the PPG signal. A feature selection algorithm based on Maximal Information Coefficient (MIC) is presented to reduce the dimensionality of the feature set to effective ones, thereby cutting down resource requirements. Support Vector Machine (SVM) is used to classify the BP values into separate bins. The proposed methodology is validated and tested on a standard benchmark clean dataset as well as phone captured noisy dataset to justify its robustness and efficiency. Apart from a commending performance improvement, BP estimation is achieved with minimal features and processing, making the algorithm light weight for porting on smart phones.

References

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Cited By

Liu SHuang ZZhu JLiu BZhou P(2024)Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction modelBiomedical Signal Processing and Control10.1016/j.bspc.2023.10535488(105354)Online publication date: Feb-2024
https://doi.org/10.1016/j.bspc.2023.105354
Sun WChang W(2023)Blood Pressure Monitoring Based on Flexible Encapsulated SensorsApplied Sciences10.3390/app1313747313:13(7473)Online publication date: 25-Jun-2023
https://doi.org/10.3390/app13137473
Fan FGu YShen JDong FChen Y(2023)FewShotBPProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36109187:3(1-39)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610918
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Smart phone based blood pressure indicator

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cover image ACM Conferences

MobileHealth '14: Proceedings of the 4th ACM MobiHoc workshop on Pervasive wireless healthcare

August 2014

62 pages

ISBN:9781450329835

DOI:10.1145/2633651

General Chairs:
Emmanuel Baccelli
INRIA, Paris, France
,
Roozbeh Jafari
University of Texas at Dallas, USA
,
Rahul Mangharam
University of Pennsylvania, USA
,
Rong Zheng
McMaster University, Canada

Copyright © 2014 ACM.

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 ACM 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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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 11 August 2014

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MobiHoc'14

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SIGMOBILE

MobiHoc'14: The Fifteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing

August 11, 2014

Pennsylvania, Philadelphia, USA

Acceptance Rates

MobileHealth '14 Paper Acceptance Rate 6 of 9 submissions, 67%;

Overall Acceptance Rate 15 of 25 submissions, 60%

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Cited By

Liu SHuang ZZhu JLiu BZhou P(2024)Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction modelBiomedical Signal Processing and Control10.1016/j.bspc.2023.10535488(105354)Online publication date: Feb-2024
https://doi.org/10.1016/j.bspc.2023.105354
Sun WChang W(2023)Blood Pressure Monitoring Based on Flexible Encapsulated SensorsApplied Sciences10.3390/app1313747313:13(7473)Online publication date: 25-Jun-2023
https://doi.org/10.3390/app13137473
Fan FGu YShen JDong FChen Y(2023)FewShotBPProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36109187:3(1-39)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610918
Man PCheung KSangsiri NShek WWong KChin JChan TSo R(2022)Blood Pressure Measurement: From Cuff-Based to Contactless MonitoringHealthcare10.3390/healthcare1010211310:10(2113)Online publication date: 21-Oct-2022
https://doi.org/10.3390/healthcare10102113
Cano JFácila LGracia-Baena JZangróniz RAlcaraz RRieta J(2022)The Relevance of Calibration in Machine Learning-Based Hypertension Risk Assessment Combining Photoplethysmography and ElectrocardiographyBiosensors10.3390/bios1205028912:5(289)Online publication date: 1-May-2022
https://doi.org/10.3390/bios12050289
Ihm SPark JKim JKim JKim KLee ELee HPark SShin JKim C(2022)Home blood pressure monitoring: a position statement from the Korean Society of Hypertension Home Blood Pressure ForumClinical Hypertension10.1186/s40885-022-00218-128:1Online publication date: 1-Oct-2022
https://doi.org/10.1186/s40885-022-00218-1
Liu WCheng JWu ZLi JShi WYang WJin NMu YWeng BWu JHao DLiu CWang ZLi GDong L(2022)A Wearable and Flexible Photoplethysmogram Sensor Patch for Cuffless Blood Pressure Estimation With High AccuracyIEEE Sensors Journal10.1109/JSEN.2022.320280322:20(19818-19825)Online publication date: 15-Oct-2022
https://doi.org/10.1109/JSEN.2022.3202803
Ranjan PKumar AKumar RSameer MGupta B(2022)Automated Detection of Blood Pressure using CNN2022 IEEE Delhi Section Conference (DELCON)10.1109/DELCON54057.2022.9753601(1-5)Online publication date: 11-Feb-2022
https://doi.org/10.1109/DELCON54057.2022.9753601
Frey LMenon CElgendi M(2022)Blood pressure measurement using only a smartphonenpj Digital Medicine10.1038/s41746-022-00629-25:1Online publication date: 6-Jul-2022
https://doi.org/10.1038/s41746-022-00629-2
Qin KHuang WZhang TTang S(2022)Machine learning and deep learning for blood pressure prediction: a methodological review from multiple perspectivesArtificial Intelligence Review10.1007/s10462-022-10353-856:8(8095-8196)Online publication date: 26-Dec-2022
https://doi.org/10.1007/s10462-022-10353-8
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