Different methods of heart rate variability analysis reveal different correlations of heart rate variability spectrum with average heart rate

Sacha, Jerzy; Pluta, Władysław

doi:10.1016/j.jelectrocard.2004.09.015

Cited by 70 publications

(77 citation statements)

References 9 publications

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“…The lack of adjustments for sleep and wake during monitoring in the Rauchenzauner study may also have an impact. It is well known that physical activity and HR is of importance for instant HRV and that there is an inverse association between HR and HF power, which is somewhat weaker for HFnu (Kuch et al 2001;Sacha and Pluta 2005). One could therefore suspect that diVerences in physical activity could account for the observed group and day diVerences.…”

Section: Discussionmentioning

confidence: 96%

Heart rate variability changes in physicians working on night call

Malmberg

Persson

Flisberg

et al. 2010

Int Arch Occup Environ Health

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The physiological recovery after night duty seemed sufficient in terms of HRV patterns for HFnu, reflecting autonomic balance and did not differ between specialities. However, the less dynamic HRV after daytime work and during night-call duty in the ANEST group may indicate a higher physiological stress level. These results may contribute to the improvement of night-call schedules within the health care sector.

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Section: Discussionmentioning

confidence: 96%

Heart rate variability changes in physicians working on night call

Malmberg

Persson

Flisberg

et al. 2010

Int Arch Occup Environ Health

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“…The HF corresponds to parasympathetic nervous system activity (cardiac vagus nerve activities). The LF/HF ratio corresponds to sympathetic nervous system activity in rhesus macaques due to the correlations among HR, HF, and LF/HF [22,24]. Fig.…”

Section: Discussionmentioning

confidence: 99%

The Evaluation of Autonomic Nervous System Activation during Learning in Rhesus Macaques with the Analysis of the Heart Rate Variability

2007

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ABSTRACT. The aims of this study were to measure the activity of the autonomic nervous system using heart rate variability (HRV) during learning tasks and to clarify the relationship between learning to overcome a difficult situation and the autonomic nervous system in monkeys. Two young male monkeys (Macaca mulatta) were given simple discrimination learning tasks (DL) and delayed matching to samples tasks (DMTS); Holter-type electrocardiography was done, and HRV was measured. We defined the frequency bands of HRV in rhesus macaques; the low frequency (LF) was 0.01-0.15 Hz, and the high frequency (HF) was 0.15-0.50 Hz. Based on these frequency bands, the LF/HF ratios during learning tasks were analyzed, and a significant increase in the ratio was found during the tasks. The variances in the HF differed between the DL and DMTS tasks; during DMTS tasks, HF variances had a tendency to increase. Our results indicate that increased sympathetic activity accompanied learning and suggest that the parasympathetic nervous system plays a key role during learning, particularly when difficult tasks are being learned. KEY WORDS: autonomic nervous system, heart rate variability, holter-type electrocardiography, learning tasks, rhesus macaque (Macaca mulatta).

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“…HRV analysis has been performed by measuring intervals between heartbeats, which are easily observed as RR intervals. Thus, HRV can be determined Polar S810i RR series for HRV analysis www.bjournal.com.br directly from an ECG signal, which is obtained by means of external sensors placed on specific points of the body (9).…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains

Vanderlei

Silva

Pastre

et al. 2008

Braz J Med Biol Res

245

191

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The aim of the present study was to compare heart rate variability (HRV) at rest and during exercise using a temporal series obtained with the Polar S810i monitor and a signal from a LYNX ® signal conditioner (BIO EMG 1000 model) with a channel configured for the acquisition of ECG signals. Fifteen healthy subjects aged 20.9 ± 1.4 years were analyzed. The subjects remained at rest for 20 min and performed exercise for another 20 min with the workload selected to achieve 60% of submaximal heart rate. RR series were obtained for each individual with a Polar S810i instrument and with an ECG analyzed with a biological signal conditioner. The HRV indices (rMSSD, pNN50, LFnu, HFnu, and LF/HF) were calculated after signal processing and analysis. The unpaired Student t-test and intraclass correlation coefficient were used for data analysis. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV at rest and during exercise

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Different methods of heart rate variability analysis reveal different correlations of heart rate variability spectrum with average heart rate

Cited by 70 publications

References 9 publications

Heart rate variability changes in physicians working on night call

Heart rate variability changes in physicians working on night call

The Evaluation of Autonomic Nervous System Activation during Learning in Rhesus Macaques with the Analysis of the Heart Rate Variability

Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains

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