Detecting Aortic Valve Opening and Closing from Distal Body Vibrations
Andrew D. Wiens, Ann Johnson, Omer T. Inan

TL;DR
This study develops and validates two methods to accurately detect aortic valve opening and closing from distal body vibrations, enabling new non-invasive cardiovascular assessments.
Contribution
It introduces FilterBCG and RidgeBCG methods for measuring AVO and AVC from distal vibrations, with FilterBCG showing superior accuracy and being the first to measure AVC distally.
Findings
FilterBCG accurately detects AVO and AVC from distal vibrations.
Distal vibrations filtered with FilterBCG resemble seismocardiogram signals.
The methods outperform traditional R-J interval and RidgeBCG approaches.
Abstract
Objective: Proximal and whole-body vibrations are well studied in seismocardiography and ballistocardiography, yet distal vibrations are still poorly understood. In this paper we develop two methods to measure aortic valve opening (AVO) and closing (AVC) from distal vibrations. Methods: AVO and AVC were detected for each heartbeat with accelerometers on the upper arm (A), wrist (W), and knee (K) of 22 consenting adults following isometric exercise. Exercise-induced changes were recorded with impedance cardiography, and nine-beat ensemble averaging was applied. Our first method, FilterBCG, detects peaks in distal vibrations after filtering with individually-tuned bandpass filters while RidgeBCG uses ridge regression to estimate AVO and AVC without peaks. Pseudocode is provided. Results: In agreement with recent studies, we did not find peaks at AVO and AVC in distal vibrations, and the…
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Taxonomy
TopicsNon-Invasive Vital Sign Monitoring · Cardiovascular Health and Disease Prevention · Hemodynamic Monitoring and Therapy
