Literature DB >> 23797215

Heart rate turbulence analysis based on photoplethysmography.

Eduardo Gil, Pablo Laguna, Juan Pablo Martínez, Óscar Barquero-Pérez, Arcadi García-Alberola, Leif Sörnmo.   

Abstract

The goal of this paper is to determine whether the photoplethysmography (PPG) can replace the ECG-based detection of heart rate turbulence. Using the PPG, classification of ventricular premature beats (VPBs) is accomplished with a linear classifier. The two conventional parameters turbulence onset and slope are studied together with a recently introduced parameter characterizing turbulence shape. Performance is studied on a dataset with 4131 VPBs, recorded from a total of 27 patients in different clinical contexts (hemodialysis treatment, intensive care monitoring, and electrophysiological study). The sensitivity/specificity of VPB classification was found to be 90.5/99.9%, with an accuracy of 99.3%, suggesting that classification of VPBs can be reliable made from the PPG. The main difference between the two types of turbulence analysis stems from the fact that the pulse transit time varies largely immediately after the VPB. Out of the 22 patients which had a sufficient number of VPBs, the outcome of the ECG- and PPG-based analysis was identical in 21. It is concluded that the PPG may serve as a surrogate technique for the ECG in turbulence analysis.

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Year:  2013        PMID: 23797215     DOI: 10.1109/TBME.2013.2270083

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

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Authors:  Sibylle Fallet; Mathieu Lemay; Philippe Renevey; Célestin Leupi; Etienne Pruvot; Jean-Marc Vesin
Journal:  Med Biol Eng Comput       Date:  2018-09-15       Impact factor: 2.602

2.  Research on recognition and classification of pulse signal features based on EPNCC.

Authors:  Haichu Chen; Chenglong Guo; Zhifeng Wang; Jianxiao Wang
Journal:  Sci Rep       Date:  2022-04-25       Impact factor: 4.996

Review 3.  Arrhythmia detection and classification using ECG and PPG techniques: a review.

Authors:  H K Sardana; R Kanwade; S Tewary
Journal:  Phys Eng Sci Med       Date:  2021-11-02

4.  Increasing accuracy of pulse transit time measurements by automated elimination of distorted photoplethysmography waves.

Authors:  Marit H N van Velzen; Arjo J Loeve; Sjoerd P Niehof; Egbert G Mik
Journal:  Med Biol Eng Comput       Date:  2017-03-30       Impact factor: 2.602

5.  Training Convolutional Neural Networks on Simulated Photoplethysmography Data: Application to Bradycardia and Tachycardia Detection.

Authors:  Andrius Sološenko; Birutė Paliakaitė; Vaidotas Marozas; Leif Sörnmo
Journal:  Front Physiol       Date:  2022-07-18       Impact factor: 4.755

6.  Premature Atrial and Ventricular Contraction Detection using Photoplethysmographic Data from a Smartwatch.

Authors:  Dong Han; Syed Khairul Bashar; Fahimeh Mohagheghian; Eric Ding; Cody Whitcomb; David D McManus; Ki H Chon
Journal:  Sensors (Basel)       Date:  2020-10-05       Impact factor: 3.847

  6 in total

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