ArticleSensors (Basel, Switzerland)2019
Unobtrusive Estimation of Cardiovascular Parameters with Limb Ballistocardiography.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
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Who cites it
9 citing papers in PubMed, 33 citations in OpenAlex.
- Comparative analysis of heart rate variability indices from ballistocardiogram and electrocardiogram: a study on measurement agreement.Heart and vessels · 2025Article
- Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications.Sensors (Basel, Switzerland) · 2023Article
- Wearable Seismocardiography-Based Assessment of Stroke Volume in Congenital Heart Disease.Journal of the American Heart Association · 2022Article
- Digital Optical Ballistocardiographic System for Activity, Heart Rate, and Breath Rate Determination during Sleep.Sensors (Basel, Switzerland) · 2022Article
- Flexible Pressure Sensor Array with Multi-Channel Wireless Readout Chip.Sensors (Basel, Switzerland) · 2022Article
- Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals.Sensors (Basel, Switzerland) · 2022Article
- Article
- Wearable and Nearable Biosensors and Systems for Healthcare.Sensors (Basel, Switzerland) · 2021Article
- Bed-Based Ballistocardiography: Dataset and Ability to Track Cardiovascular Parameters.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 3 countries.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.