Using electromechanical signals recorded from the body for respiratory phase detection and respiratory time estimation: A comparative study

Nasim Alamdari, Kouhyar Tavakolian*, Vahid Zakeri, Reza Fazel-Rezai, Mikko Paukkunen, Raimo Sepponen, Alireza Akhbardeh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

6 Citations (Scopus)

Abstract

Electrocardiogram derived respiratory (EDR) is a non-invasive technique to estimate respiratory signal. As an alternative, recent studies suggest using Seismocardiogram to estimate respiratory signal, so called accelerometer derived respiration (ADR). In this study we compared the performance of ADR and EDR in precise detection of respiration phases (inhale and exhale timing). We also compared time lag between breath cycles extracted by use of ADR and EDR, and ground truth (respiratory signal recorded using chest band strain gauge). For this comparative analysis, Seismocardiogram, Single lead electrocardiogram (Lead II), and respiratory signal (using a chest band strain gauge) were recorded from 19 healthy subjects. Principal component analysis (PCA) and envelope detection methods are used to compute EDR and ADR. Initial results show that ADR in z-direction (back to front) seems promising approach in addition to the EDR with accuracy of above 85% in identifying respiration phases (inhale and exhale). 87% of breath cycles extracted from ADR had acceptable time lag compared to ground truth (respiratory signal recorded using a chest band strain gauge). ADR was able to correctly classify heartbeats to inhale and exhale classes with classification accuracy of around 76%.

Original languageEnglish
Title of host publicationComputing in cardiology, CinC 2015
EditorsAlan Murray
PublisherIEEE Computer Society
Pages65-68
Number of pages4
Volume42
ISBN (Print)9781509006854
DOIs
Publication statusPublished - 16 Feb 2016
MoE publication typeA4 Article in a conference publication
EventComputing in Cardiology Conference - Nice, France
Duration: 6 Sep 20159 Sep 2015
Conference number: 42
http://www.cinc.org/

Publication series

NameComputing in cardiology
Volume42
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

ConferenceComputing in Cardiology Conference
Abbreviated titleCinC
CountryFrance
CityNice
Period06/09/201509/09/2015
Internet address

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