HRV Computation as Embedded Software

George Manis

Abstract

The heart rate signal contains useful information about the condition of the human heart which cannot be extracted without the use of an information processing system. Various techniques for the analysis of the heart rate variability (HRV) have been proposed, derived from diverse scientific fields. In this paper we examine theoretically and experimentally the most commonly used algorithms as well as some other interesting approaches for the computation of heart rate variability from the point of view of the embedded software development. The selected algorithms are compared for their efficiency, the complexity, the size of the object code, the memory requirements, the power consumption, the real time response and the simplicity of their interfaces. Figures giving a rough image of the capability of each algorithm to classify the subjects into two distinct groups presenting high and low heart rate variability are also presented, using data acquired from young and elderly subjects.

References

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Paper Citation


in Harvard Style

Manis G. (2005). HRV Computation as Embedded Software . In Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005) ISBN 972-8865-35-X, pages 150-157. DOI: 10.5220/0001195401500157


in Bibtex Style

@conference{bpc05,
author={George Manis},
title={HRV Computation as Embedded Software},
booktitle={Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005)},
year={2005},
pages={150-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001195401500157},
isbn={972-8865-35-X},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005)
TI - HRV Computation as Embedded Software
SN - 972-8865-35-X
AU - Manis G.
PY - 2005
SP - 150
EP - 157
DO - 10.5220/0001195401500157