Noninvasive and Continuous Blood Pressure Monitoring Using Wearable Body Sensor Networks

Hao Lin; Wenyao Xu; Nan Guan; Dong Ji; Yangjie Wei; Wang Yi

doi:10.1109/MIS.2015.72

Noninvasive and Continuous Blood Pressure Monitoring Using Wearable Body Sensor Networks

Hao Lin
, Wenyao Xu
, Nan Guan^*
, Dong Ji
, Yangjie Wei
, Wang Yi

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

63 Scopus citations

Abstract

Hypertension is a major health risk that influences the quality of life for many people. The importance of monitoring hypertension in a continuous and noninvasive manner increases as more people experience raised blood pressure (BP). The authors present a smartphone-centric body sensor network to measure the pulse transit time (PTT) in real time. Their robust method for calculating BP uses PPT information that considers the baroreflex mechanism, which reflects the relationship between BP and the heart rate. To evaluate the performance of their proposed method, they collected 300 groups of data from six subjects before and after exercise. Experimental results show that their proposed method can estimate BP values in real time with good precision.

Original language	English
Article number	7274241
Pages (from-to)	38-48
Number of pages	11
Journal	IEEE Intelligent Systems
Volume	30
Issue number	6
DOIs	https://doi.org/10.1109/MIS.2015.72
State	Published - 1 Nov 2015
Externally published	Yes

Keywords

baroreflex
blood pressure
body sensor networks
intelligent systems
pulse transit time

UN SDGs

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

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10.1109/MIS.2015.72

Cite this

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title = "Noninvasive and Continuous Blood Pressure Monitoring Using Wearable Body Sensor Networks",

abstract = "Hypertension is a major health risk that influences the quality of life for many people. The importance of monitoring hypertension in a continuous and noninvasive manner increases as more people experience raised blood pressure (BP). The authors present a smartphone-centric body sensor network to measure the pulse transit time (PTT) in real time. Their robust method for calculating BP uses PPT information that considers the baroreflex mechanism, which reflects the relationship between BP and the heart rate. To evaluate the performance of their proposed method, they collected 300 groups of data from six subjects before and after exercise. Experimental results show that their proposed method can estimate BP values in real time with good precision.",

keywords = "baroreflex, blood pressure, body sensor networks, intelligent systems, pulse transit time",

author = "Hao Lin and Wenyao Xu and Nan Guan and Dong Ji and Yangjie Wei and Wang Yi",

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T1 - Noninvasive and Continuous Blood Pressure Monitoring Using Wearable Body Sensor Networks

AU - Lin, Hao

AU - Xu, Wenyao

AU - Guan, Nan

AU - Ji, Dong

AU - Wei, Yangjie

AU - Yi, Wang

PY - 2015/11/1

Y1 - 2015/11/1

N2 - Hypertension is a major health risk that influences the quality of life for many people. The importance of monitoring hypertension in a continuous and noninvasive manner increases as more people experience raised blood pressure (BP). The authors present a smartphone-centric body sensor network to measure the pulse transit time (PTT) in real time. Their robust method for calculating BP uses PPT information that considers the baroreflex mechanism, which reflects the relationship between BP and the heart rate. To evaluate the performance of their proposed method, they collected 300 groups of data from six subjects before and after exercise. Experimental results show that their proposed method can estimate BP values in real time with good precision.

AB - Hypertension is a major health risk that influences the quality of life for many people. The importance of monitoring hypertension in a continuous and noninvasive manner increases as more people experience raised blood pressure (BP). The authors present a smartphone-centric body sensor network to measure the pulse transit time (PTT) in real time. Their robust method for calculating BP uses PPT information that considers the baroreflex mechanism, which reflects the relationship between BP and the heart rate. To evaluate the performance of their proposed method, they collected 300 groups of data from six subjects before and after exercise. Experimental results show that their proposed method can estimate BP values in real time with good precision.

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KW - blood pressure

KW - body sensor networks

KW - intelligent systems

KW - pulse transit time

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DO - 10.1109/MIS.2015.72

M3 - 文章

AN - SCOPUS:84962027408

SN - 1541-1672

VL - 30

SP - 38

EP - 48

JO - IEEE Intelligent Systems

JF - IEEE Intelligent Systems

IS - 6

M1 - 7274241

ER -

Noninvasive and Continuous Blood Pressure Monitoring Using Wearable Body Sensor Networks

Abstract

Keywords

UN SDGs

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