Real-Time Robust Heart Rate Estimation Based on Bayesian Framework and Grid Filters

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00197529" target="_blank" >RIV/68407700:21230/12:00197529 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Real-Time Robust Heart Rate Estimation Based on Bayesian Framework and Grid Filters

Popis výsledku v původním jazyce

In this chapter we discuss derivation, implementation and testing of a robust real-time algorithm for the estimation of heart rate (HR) from electrocardiograms recorded on subjects performing vigorous physical activity. We formulate the problem of HR estimation as a problem of inference in a Bayesian network, which utilizes prior information about the probability distribution of HR changes. From this formulation we derive an inference procedure, which can be implemented as a grid filter. The resulting algorithm can then follow even a rapidly changing HR, whilst withstanding a series of missed or false QRS detections. Also, the HR estimate is complete with confidence intervals to allow the identification of the moments, where the precision of HR estimation is lowered. Additionally, the computational complexity of this algorithm is acceptable for battery powered portable devices.

Název v anglickém jazyce

Real-Time Robust Heart Rate Estimation Based on Bayesian Framework and Grid Filters

Popis výsledku anglicky

In this chapter we discuss derivation, implementation and testing of a robust real-time algorithm for the estimation of heart rate (HR) from electrocardiograms recorded on subjects performing vigorous physical activity. We formulate the problem of HR estimation as a problem of inference in a Bayesian network, which utilizes prior information about the probability distribution of HR changes. From this formulation we derive an inference procedure, which can be implemented as a grid filter. The resulting algorithm can then follow even a rapidly changing HR, whilst withstanding a series of missed or false QRS detections. Also, the HR estimate is complete with confidence intervals to allow the identification of the moments, where the precision of HR estimation is lowered. Additionally, the computational complexity of this algorithm is acceptable for battery powered portable devices.

Druh

C - Kapitola v odborné knize

CEP obor

BD - Teorie informace

OECD FORD obor

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Projekt

<a href="/cs/project/GPP102%2F11%2FP109" target="_blank" >GPP102/11/P109: Techniky prostorové filtrace pro elektroencefalografické záznamy s vysokou hustotou elektrod</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Medical Applications of Intelligent Data Analysis

ISBN

978-1-4666-1803-9

Počet stran výsledku

24

Strana od-do

67-90

Počet stran knihy

348

Název nakladatele

IGI Global

Místo vydání

Hershey, Pennsylvania

Kód UT WoS kapitoly

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