A novel algorithm for HRV estimation from short-term acoustic recordings at neck

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Title: A novel algorithm for HRV estimation from short-term acoustic recordings at neck
Authors: Sharma, P
Rodriguez-Villegas, E
Item Type: Conference Paper
Abstract: Heart rate variability (HRV) is an important non-invasive parameter to monitor the activity of the autonomicnervous system. This paper proposes an algorithm to analyzeHRV by processing the acoustic data, recorded by placing asmall, wearable sensor on the suprasternal notch (at neck) ofan adult subject, primarily intended to record breathing sounds.The method used an empirical data analysis approach of theHilbert-Huang transform (HHT) to construct an instantaneousenergy envelope and segment the cardiac cycle by detectingS1 and S2 sounds using the K-means algorithm. The time-domain HRV analysis for the short-term recordings of 10subjects demonstrated a close agreement with the referenceECG signal. The instantaneous heart rate (IHR) comparisonsyielded an accuracy of 95.78% and 92.35% for S1 and S2sounds respectively. The experimental results showed that theproposed algorithm can provide an accurate HRV analysis forthe cardiac signals recorded at the neck.
Issue Date: 23-Jul-2019
Date of Acceptance: 12-Apr-2019
URI: http://hdl.handle.net/10044/1/69975
Publisher: IEEE
Copyright Statement: This paper is embargoed until publication.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 724334
Conference Name: 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Publication Status: Accepted
Start Date: 2019-07-23
Finish Date: 2019-07-27
Conference Place: Berlin, Germany
Embargo Date: publication subject to indefinite embargo
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering

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