Unobtrusive Estimation of Cardiovascular Parameters with Limb Ballistocardiography

Sensors

Yang Yao¹  Lisheng Xu¹  Ramakrishna Mukkamala²  Sungtae Shin³  Azin Mousavi³  Jin-Oh Hahn³  Chang-Sei Kim⁴ 

[1] College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China;Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA;Department of Mechanical Engineering, University of Maryland, College Park, College Park, MD 20742, USA;School of Mechanical Engineering, Chonnam National University, Gwangju 61186, Korea;

关键词: ballistocardiography;    ballistocardiogram;    blood pressure;    stroke volume;    cardiac output;    total peripheral resistance;    photoplethysmography;    photoplethysmogram;   

DOI  :  10.3390/s19132922

来源: DOAJ

【 摘 要 】

This study investigates the potential of the limb ballistocardiogram (BCG) for unobtrusive estimation of cardiovascular (CV) parameters. In conjunction with the reference CV parameters (including diastolic, pulse, and systolic pressures, stroke volume, cardiac output, and total peripheral resistance), an upper-limb BCG based on an accelerometer embedded in a wearable armband and a lower-limb BCG based on a strain gauge embedded in a weighing scale were instrumented simultaneously with a finger photoplethysmogram (PPG). To standardize the analysis, the more convenient yet unconventional armband BCG was transformed into the more conventional weighing scale BCG (called the synthetic weighing scale BCG) using a signal processing procedure. The characteristic features were extracted from these BCG and PPG waveforms in the form of wave-to-wave time intervals, wave amplitudes, and wave-to-wave amplitudes. Then, the relationship between the characteristic features associated with (i) the weighing scale BCG-PPG pair and (ii) the synthetic weighing scale BCG-PPG pair versus the CV parameters, was analyzed using the multivariate linear regression analysis. The results indicated that each of the CV parameters of interest may be accurately estimated by a combination of as few as two characteristic features in the upper-limb or lower-limb BCG, and also that the characteristic features recruited for the CV parameters were to a large extent relevant according to the physiological mechanism underlying the BCG.

【 授权许可】

Unknown