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A Wearable Technology Revisited for Cardio-Respiratory Functional Exploration: Stroke Volume Estimation from Respiratory Inductive Plethysmography

Julie Fontecave-Jallon, Pierre-Yves Guméry, Pascale Calabrese, Raphaël Briot and Pierre Baconnier
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Julie Fontecave-Jallon: University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
Pierre-Yves Guméry: University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
Pascale Calabrese: University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
Raphaël Briot: University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
Pierre Baconnier: University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France

International Journal of E-Health and Medical Communications (IJEHMC), 2013, vol. 4, issue 1, 12-22

Abstract: The objective of the present study is to extract new information from complex signals generated by Respiratory Inductive Plethysmography (RIP). This indirect cardio-respiratory (CR) measure is a well-known wearable solution. The authors applied time-scale analysis to estimate cardiac activity from thoracic volume variations, witnesses of CR interactions. Calibrated RIP signals gathered from 4 healthy volunteers in resting conditions are processed by Ensemble Empirical Mode Decomposition to extract cardiac volume signals and estimate stroke volumes. Averaged values of these stroke volumes (SVRIP) are compared with averaged values of stroke volumes determined simultaneously by electrical impedance cardiography (SVICG). There is a satisfactory correlation between SVRIP and SVICG (r=0.76, p

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jehmc0:v:4:y:2013:i:1:p:12-22

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