Continuous cuffless blood pressure measurement using body sensors

Fatemeh Hevdari; Malikeh P. Ebrahim; Taiyang Wu; Katie Walker; Keith Joe; Jean Michel Redoute; Mehmet R. Yuce

doi:10.1109/ICSENS.2018.8630294

Continuous cuffless blood pressure measurement using body sensors

Fatemeh Hevdari, Malikeh P. Ebrahim, Taiyang Wu, Katie Walker, Keith Joe, Jean Michel Redoute, Mehmet R. Yuce

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

7 Citations (Scopus)

Abstract

Non-invasive cuffless blood pressure (BP) measurement using pulse arrival time (PAT) offers some unique features for healthcare applications including improved wearability and user-friendly BP monitoring. Researchers have mostly been using electrocardiography (ECG) and photoplesthysmography (PPG) signals to measure PAT, which requires at least two separate attachments to the subject's body. In this paper, human cuffless systolic BP (SBP) calculations using the shoulders bioimpedance (BImp) signal were investigated and compared to PPG (left ear sensor) and oscillometric sphygmomanometric SBP (left upper arm). The BImp sensors were placed on subject's shoulder and could be completely hidden under their clothes. In order to calculate different BP trends, two groups of experimental conditions (mainly postures and exercises) were followed. Data was obtained from 43 volunteer participants whilst they were sitting, standing and supine, and 26 subjects then cycled on an exercise bike with light, moderate and heavy resistance settings. Four different mathematical models for calculating SBP were compared for accuracy, using both BImp and PPG signal data. Overall, the results of SBP calculation with BImp based PATs were 2% more accurate than that of PATs extracted from PPG.

Original language	English
Title of host publication	2018 IEEE SENSORS Proceedings
Editors	Rudra Pratap, Ravinder Dahiya
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	180-183
Number of pages	4
ISBN (Electronic)	9781538647073
ISBN (Print)	9781538647080
DOIs	https://doi.org/10.1109/ICSENS.2018.8630294
Publication status	Published - 2018
Event	IEEE Conference on Sensors 2018 - New Delhi, India Duration: 28 Oct 2018 → 31 Oct 2018 Conference number: 17th http://ieee-sensors2018.org/ https://ieeexplore.ieee.org/xpl/conhome/8572682/proceeding (Proceedings)

Conference

Conference	IEEE Conference on Sensors 2018
Abbreviated title	SENSORS 2018
Country/Territory	India
City	New Delhi
Period	28/10/18 → 31/10/18
Internet address	http://ieee-sensors2018.org/ https://ieeexplore.ieee.org/xpl/conhome/8572682/proceeding (Proceedings)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICSENS.2018.8630294

Cite this

@inproceedings{21755c3a7bb045aebcf68ada3c75c344,

title = "Continuous cuffless blood pressure measurement using body sensors",

abstract = "Non-invasive cuffless blood pressure (BP) measurement using pulse arrival time (PAT) offers some unique features for healthcare applications including improved wearability and user-friendly BP monitoring. Researchers have mostly been using electrocardiography (ECG) and photoplesthysmography (PPG) signals to measure PAT, which requires at least two separate attachments to the subject's body. In this paper, human cuffless systolic BP (SBP) calculations using the shoulders bioimpedance (BImp) signal were investigated and compared to PPG (left ear sensor) and oscillometric sphygmomanometric SBP (left upper arm). The BImp sensors were placed on subject's shoulder and could be completely hidden under their clothes. In order to calculate different BP trends, two groups of experimental conditions (mainly postures and exercises) were followed. Data was obtained from 43 volunteer participants whilst they were sitting, standing and supine, and 26 subjects then cycled on an exercise bike with light, moderate and heavy resistance settings. Four different mathematical models for calculating SBP were compared for accuracy, using both BImp and PPG signal data. Overall, the results of SBP calculation with BImp based PATs were 2% more accurate than that of PATs extracted from PPG.",

author = "Fatemeh Hevdari and Ebrahim, {Malikeh P.} and Taiyang Wu and Katie Walker and Keith Joe and Redoute, {Jean Michel} and Yuce, {Mehmet R.}",

year = "2018",

doi = "10.1109/ICSENS.2018.8630294",

language = "English",

isbn = "9781538647080",

pages = "180--183",

editor = "Rudra Pratap and Ravinder Dahiya",

booktitle = "2018 IEEE SENSORS Proceedings",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE Conference on Sensors 2018, SENSORS 2018 ; Conference date: 28-10-2018 Through 31-10-2018",

url = "http://ieee-sensors2018.org/, https://ieeexplore.ieee.org/xpl/conhome/8572682/proceeding",

}

Hevdari, F, Ebrahim, MP, Wu, T, Walker, K , Joe, K, Redoute, JM & Yuce, MR 2018, Continuous cuffless blood pressure measurement using body sensors. in R Pratap & R Dahiya (eds), 2018 IEEE SENSORS Proceedings. IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 180-183, IEEE Conference on Sensors 2018, New Delhi, India, 28/10/18. https://doi.org/10.1109/ICSENS.2018.8630294

Continuous cuffless blood pressure measurement using body sensors. / Hevdari, Fatemeh; Ebrahim, Malikeh P.; Wu, Taiyang et al.
2018 IEEE SENSORS Proceedings. ed. / Rudra Pratap; Ravinder Dahiya. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2018. p. 180-183.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Continuous cuffless blood pressure measurement using body sensors

AU - Hevdari, Fatemeh

AU - Ebrahim, Malikeh P.

AU - Wu, Taiyang

AU - Walker, Katie

AU - Joe, Keith

AU - Redoute, Jean Michel

AU - Yuce, Mehmet R.

N1 - Conference code: 17th

PY - 2018

Y1 - 2018

N2 - Non-invasive cuffless blood pressure (BP) measurement using pulse arrival time (PAT) offers some unique features for healthcare applications including improved wearability and user-friendly BP monitoring. Researchers have mostly been using electrocardiography (ECG) and photoplesthysmography (PPG) signals to measure PAT, which requires at least two separate attachments to the subject's body. In this paper, human cuffless systolic BP (SBP) calculations using the shoulders bioimpedance (BImp) signal were investigated and compared to PPG (left ear sensor) and oscillometric sphygmomanometric SBP (left upper arm). The BImp sensors were placed on subject's shoulder and could be completely hidden under their clothes. In order to calculate different BP trends, two groups of experimental conditions (mainly postures and exercises) were followed. Data was obtained from 43 volunteer participants whilst they were sitting, standing and supine, and 26 subjects then cycled on an exercise bike with light, moderate and heavy resistance settings. Four different mathematical models for calculating SBP were compared for accuracy, using both BImp and PPG signal data. Overall, the results of SBP calculation with BImp based PATs were 2% more accurate than that of PATs extracted from PPG.

AB - Non-invasive cuffless blood pressure (BP) measurement using pulse arrival time (PAT) offers some unique features for healthcare applications including improved wearability and user-friendly BP monitoring. Researchers have mostly been using electrocardiography (ECG) and photoplesthysmography (PPG) signals to measure PAT, which requires at least two separate attachments to the subject's body. In this paper, human cuffless systolic BP (SBP) calculations using the shoulders bioimpedance (BImp) signal were investigated and compared to PPG (left ear sensor) and oscillometric sphygmomanometric SBP (left upper arm). The BImp sensors were placed on subject's shoulder and could be completely hidden under their clothes. In order to calculate different BP trends, two groups of experimental conditions (mainly postures and exercises) were followed. Data was obtained from 43 volunteer participants whilst they were sitting, standing and supine, and 26 subjects then cycled on an exercise bike with light, moderate and heavy resistance settings. Four different mathematical models for calculating SBP were compared for accuracy, using both BImp and PPG signal data. Overall, the results of SBP calculation with BImp based PATs were 2% more accurate than that of PATs extracted from PPG.

UR - http://www.scopus.com/inward/record.url?scp=85061246649&partnerID=8YFLogxK

U2 - 10.1109/ICSENS.2018.8630294

DO - 10.1109/ICSENS.2018.8630294

M3 - Conference Paper

AN - SCOPUS:85061246649

SN - 9781538647080

SP - 180

EP - 183

BT - 2018 IEEE SENSORS Proceedings

A2 - Pratap, Rudra

A2 - Dahiya, Ravinder

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - IEEE Conference on Sensors 2018

Y2 - 28 October 2018 through 31 October 2018

ER -

Continuous cuffless blood pressure measurement using body sensors

Abstract

Conference

UN SDGs

Access to Document

Other files and links

Cite this