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Pulse Wave Characteristics Based on Age and Body Mass Index (BMI) During Sitting Posture
Heydari, F.; Pour Ebrahim, M.; Redouté, Jean-Michel et al.
2019In Body Area Networks Smart IoT and Big Data for Intelligent Health Management
Peer reviewed
 

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Keywords :
Blood; Blood pressure; Elasticity; Parameter estimation; Physiological models; Cardiac activity; Measurement technologies; Photoplethysmography (PPG); Physiological parameters; Pulse wave signal; Pulse waveforms; Reflected waves; Sitting posture; Health
Abstract :
[en] Measurement technologies of arterial parameters are mostly based on processing blood pulse wave which is an important representation of cardiac activity. The pulse wave is structured with forward and reflected waves which are affected by individual physiological parameters such as the blood intensity, the elasticity of the aorta, artery elasticity and the reflection location. The pulse wave is also an important parameter in invasive cuff-less blood pressure measurement methods. However, different physiological circumstances can lead to pulse waveforms with different characteristics including the curve factors, amplitude and time landmarks. In this study, the pulse wave signal is obtained by bio-impedance (BImp) via shoulder and photoplethysmography (PPG) from the left ear. Four age groups, as well as three (body mass index) BMI groups, are considered as physiological circumstances and the effect of them on five characteristics factors of the pulse wave, are compared. Overall, the results displayed a significant effect of the aging and BMI on the pulse wave’s characteristics. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Heydari, F.;  Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia
Pour Ebrahim, M.
Redouté, Jean-Michel  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes microélectroniques intégrés
Yuce, M. R.;  Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia
Language :
English
Title :
Pulse Wave Characteristics Based on Age and Body Mass Index (BMI) During Sitting Posture
Publication date :
2019
Event name :
14th EAI International Conference on Body Area Networks, BodyNets 2019
Event date :
2 October 2019 through 3 October 2019
Audience :
International
Main work title :
Body Area Networks Smart IoT and Big Data for Intelligent Health Management
Pages :
125-132
Peer reviewed :
Peer reviewed
Name of the research project :
ARC: FT130100430
Funders :
ARC - Australian Research Council [AU]
Commentary :
234309 9783030348328
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since 06 June 2020

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