Can RR intervals editing and selection techniques interfere with the analysis of heart rate variability?

•95% confidence interval identified more doubtful points than other studied methods.•Correction techniques do not influence the final set of RR intervals.•Selection methods may interfere with the quantity–quality of RR intervals.•The 256-point selection appears to be more sensitive to changes in aut...

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Bibliographic Details
Published in:Revista brasileira de fisioterapia (São Carlos (São Paulo, Brazil)) Brazil)), 2018-09, Vol.22 (5), p.383-390
Main Authors: Ribeiro, Gustavo dos Santos, Neves, Victor Ribeiro, Deresz, Luís Fernando, Melo, Rosangela Domingues, Dal Lago, Pedro, Karsten, Marlus
Format: Article
Language:English
Subjects:
Aged
Autonomous nervous system
Cardiovascular system
Electrocardiography - methods
Female
Heart Rate - physiology
Humans
Male
Original Research
Premature ventricular complexes
Test reproducibility
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Summary:•95% confidence interval identified more doubtful points than other studied methods.•Correction techniques do not influence the final set of RR intervals.•Selection methods may interfere with the quantity–quality of RR intervals.•The 256-point selection appears to be more sensitive to changes in autonomic function. Oscillation between successive sinus beats or RR intervals, termed heart rate variability, is an important marker of autonomic function of the heart. However, its analysis may be influenced by the database recorded based on the occurrence of interference. To evaluate if the techniques of identification and editing of artifacts, as well as the selection methods of RR intervals, can interfere with heart rate variability analysis. The RR intervals of 56 subjects (30 aortic stenosis patients, 14 physically active individuals, 12 amateur athletes) were recorded for 10min using a heart rate monitor. Values with differences greater than 20%, higher than three standard deviations or outside of the normal curve (95% confidence interval) were considered artifacts. These points were corrected through data replacement, adjacent, linear and polynomial interpolation, or excluded. Then, the 256 highest stability points and the last 5min of recordings were chosen. The software programs, Kubios HRV and GraphPAD, were used to calculate and to analyze the indices of heart rate variability, respectively. Strong agreement was observed among the identification algorithms; there was no difference between the correction techniques (p=0.95); and the selection methods exhibited different sections (p
ISSN:1413-3555
1809-9246
DOI:10.1016/j.bjpt.2018.03.008