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Heart Beat Detection from Smartphone SCG Signals: Comparison with Previous Study on HR Estimation

  • Szymon SiecińskiEmail author
  • Paweł Kostka
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 925)

Abstract

Seismocardiography (SCG) is a non-invasive method of analyzing and recording cardiovascular activity as vibrations transmitted to the chest wall. Mobile devices offer the possibility to monitor health parameters thanks to embedded sensors. Various applications have been proposed for SCG, including heart rate calculation. Our aim is to detect heart beat on seismocardiograms using improved algorithm and compare its performance with results obtained in previous study.

Algorithm proposed in this study consists of signal preprocessing, RMS envelope calculation and peak finding. Algorithm performance was measured as sensitivity (Se) and positive predictive value (PPV) of beat detection on 4 signals acquired from 4 subjects.

We achieved average \(Se = 0.994\) and \(PPV = 0.966\) and in the best case \(Se = 0.995\) and \(PPV = 0.970\). Results prove major improvement of beat detection from smartphone seismocardiograms since the previous study.

Keywords

Seismocardiography AO detection Heart beat detection Smartphone 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Biosensors and Biomedical Signals ProcessingSilesian University of TechnologyZabrzePoland

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