Comput Methods Programs Biomed - Influence of QRS complex detection errors on entropy algorithms. Application to heart rate variability discrimination.

Tópicos

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Resumo

Signal entropy measures such as approximate entropy (ApEn) and sample entropy (SampEn) are widely used in heart rate variability (HRV) analysis and biomedical research. In this article, we analyze the influence of QRS detection errors on HRV results based on signal entropy measures. Specifically, we study the influence that QRS detection errors have on the discrimination power of ApEn and SampEn using the cardiac arrhythmia suppression trial (CAST) database. The experiments assessed the discrimination capability of ApEn and SampEn under different levels of QRS detection errors. The results demonstrate that these measures are sensitive to the presence of ectopic peaks: from a successful classification rate of 100%, down to a 75% when spikes are present. The discriminating capability of the metrics degraded as the number of misdetections increased. For an error rate of 2% the segmentation failed in a 12.5% of the experiments, whereas for a 5% rate, it failed in a 25%.

Resumo Limpo

signal entropi measur approxim entropi apen sampl entropi sampen wide use heart rate variabl hrv analysi biomed research articl analyz influenc qrs detect error hrv result base signal entropi measur specif studi influenc qrs detect error discrimin power apen sampen use cardiac arrhythmia suppress trial cast databas experi assess discrimin capabl apen sampen differ level qrs detect error result demonstr measur sensit presenc ectop peak success classif rate spike present discrimin capabl metric degrad number misdetect increas error rate segment fail experi wherea rate fail

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