Spectral analysis of heart rate variability with the autoregressive method: What model order to choose?

Dantas, Eduardo Miranda; Sant'Anna, Marcela Lima; Andreão, Rodrigo Varejão; Gonçalves, Cristine; Morra, Elis Aguiar; Baldo, Marcelo Perim; Rodrigues, Sérgio Lamêgo; Mill, José Geraldo

doi:10.1016/j.compbiomed.2011.11.004

Cited by 68 publications

(33 citation statements)

References 23 publications

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“…The WinCardio software (version 4.4a, Micromed, Brazil) was used to generate the R-R interval series from a selected lead (usually Lead II) associated with higher R-wave amplitude. The artifact detection and spectral analytic techniques were the same as used by Dantas et al (24), in which the R-R series were automatically preprocessed to remove ectopic beats and artifacts, and linear interpolation was employed to replace any removed beats.…”

Section: Methodsmentioning

confidence: 99%

Relationship between heart rate variability and subclinical thyroid disorders of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Miranda

Hoshi

Bittencourt

et al. 2018

Braz J Med Biol Res

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The association between subclinical thyroid dysfunctions and autonomic modulation changes has been described by many studies with conflicting results. We aimed to analyze the association between subclinical hyperthyroidism (SCHyper), subclinical hypothyroidism (SCHypo), and heart rate variability (HRV) using the baseline from ELSA-Brasil. SCHyper and SCHypo were classified by use of medication to treat thyroid disorders, thyrotropin levels respectively above and under the reference range, and normal free thyroxine levels. For HRV, the participants underwent 10 min in supine position and the R-R intervals of the final 5 min were selected for analysis. We first used linear regression models to report crude data and then, multivariate adjustment for sociodemographic (age, sex, and race) and cardiovascular risk factors (hypertension, dyslipidemia, diabetes, smoking, body mass index, use of alcohol, and leisure physical activity) using the euthyroid group as reference. From 9270 subjects (median age, 50; interquartile range: 44–56), 8623 (93.0%) were classified as euthyroid, 136 (1.5%) as SCHyper, and 511 (5.5%) as SCHypo. Compared to euthyroid subjects, SCHyper participants presented significantly higher heart rate (68.8 vs 66.5 for euthyroidism, P=0.007) and shorter R-R intervals (871.4 vs 901.6, P=0.007). Although SCHyper was associated with lower standard deviation of NN interval (SDNN) (β: –0.070; 95% confidence interval (95%CI): –0.014 to –0.009) and low-frequency (LF) (β: –0.242, 95%CI: –0.426 to –0.058) compared to the euthyroid group, these differences lost significance after multivariate adjustment for confounders. No significant differences were found for HRV in SCHypo. No association was found between HRV and SCHyper or SCHypo compared to euthyroid subjects in this sample of apparently healthy subjects.

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Section: Methodsmentioning

confidence: 99%

Relationship between heart rate variability and subclinical thyroid disorders of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Miranda

Hoshi

Bittencourt

et al. 2018

Braz J Med Biol Res

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“…The power spectral analysis was performed through autoregressive modeling, using the Yule-Walker method with a Levison-Durbin recursive algorithm. The model order was adjusted to 16 in all analyses, consistent with Dantas et al (2012) [22]. The oscillatory components present in the time series were classified based on very low (VLF: 0–0.04 Hz), low (LF: 0.04–0,15 Hz), and high (0.15–0.40 Hz) frequencies.…”

Section: Methodsmentioning

confidence: 99%

“…Normalization was achieved by dividing the spectral power of each oscillatory component by the total power of the spectrum minus the VLF power component. The LF/HF ratio was achieved by dividing the LF components by the HF components in normalized units [22].…”

Section: Methodsmentioning

confidence: 99%

Strengthening Exercises Improve Symptoms and Quality of Life but Do Not Change Autonomic Modulation in Fibromyalgia: A Randomized Clinical Trial

et al. 2014

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ObjectiveAutonomic dysfunction is an important mechanism that could explain many symptoms observed in fibromyalgia (FM). Exercise is an effective treatment, with benefits potentially mediated through changes in autonomic modulation. Strengthening is one of the less studied exercises in FM, and the acute and chronic effects of strengthening on the autonomic system remain unknown. The objective of this study was to assess the chronic effects of strengthening exercises (STRE) on autonomic modulation, pain perception and the quality of life (QOL) of FM patients.MethodsEighty sedentary women with FM (ACR 1990) were randomly selected to participate in STRE or flexibility (FLEX) exercises in a blinded controlled trial. The intensity of STRE was set at 45% of the estimated load of 1 Repetition Maximum (RM) in 12 different exercises. Outcomes were Visual Analog Scale (VAS) for pain, Heart Rate Variability (HRV) analysis, treadmill test, the sit and reach test (Wells and Dillon’s Bench), maximal repetitions test and handgrip dynamometry; and quality of life by the Fibromyalgia Impact Questionnaire (FIQ), the Beck and Idate Trait-State Inventory (IDATE), a short-form health survey (SF-36).ResultsThe STRE group was more effective to strength gain for all muscles and pain control after 4 and 16 weeks (p<0.05). The FLEX group showed higher improvements in anxiety (p<0.05). Both groups showed improvements in the QOL, and there was no significant difference observed between the groups. There was no change in the HRV of the STRE and FLEX groups.ConclusionsStrengthening exercises show greater and more rapid improvements in pain and strength than flexibility exercises. Despite the benefits in fitness, pain, depression, anxiety and quality of life, no effect was observed on the autonomic modulation in both groups. This observation suggests that changes in autonomic modulation are not a target tobe clinically achieved in fibromyalgia.Trial RegistrationClinicalTrials.gov NCT02004405

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“…| 3 of 12 linear interpolation. If R-R series were changed by more than 20%, they were excluded from analyses (Dantas et al, 2012(Dantas et al, , 2015. According to this criterion, 3.8% of the ECG records were invalid and excluded from HRV analysis.…”

Section: Ecg Records and Hrv Analysismentioning

confidence: 99%

Reference values for short‐term resting‐state heart rate variability in healthy adults: Results from the Brazilian Longitudinal Study of Adult Health—ELSA‐Brasil study

et al. 2018

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Heart rate variability (HRV) is a psychophysiological phenomenon with broad implications, providing an accessible index of vagal function, underpinning psychological constructs, including the capacity for social engagement and emotion regulation, and may predict future morbidity and mortality. However, the lack of reference values for short-term HRV indices for participants of both sexes across the age spectrum is a limiting factor. This was the objective of the present study. Resting electrocardiographic records were obtained from 13,214 participants (both sexes, 35-74 years), and HRV indices in time and frequency domains (mean ± SD) were determined from 5-min records. Results were based on a subsample of 2,874 nonmedicated, healthy participants stratified by sex across 10-year age groupings. Men showed lower heart rate (HR, 64 ± 8 bpm vs. 68 ± 8 bpm, p < .05) and normalized high frequency (HF; 39.4 ± 18.0 normalized units [n.u.] vs. 50.4 ± 18.5 n.u., p < .05) than women, and higher N-N variance (2,214 ± 1,890 ms vs. 1,883 ± 1,635 ms , p < .05), standard deviation of all N-N intervals (SDNN; 43.7 ± 17.3 ms vs. 40.3 ± 15.8 ms, p < .05) and LF/HF (2.30 ± 2.68 vs. 1.33 ± 1.82, p < .05). HR and HF (n.u.) were also higher in younger than older women. LF/HF was lower in women than men. Percentile curves showed almost all HRV indices decreasing with aging. The availability of short-term, resting-state HRV reference values in a large sample of healthy and nonmedicated participants from 35-74 years will provide a valuable tool for researchers, clinicians, and those in the quantified-self community.

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Spectral analysis of heart rate variability with the autoregressive method: What model order to choose?

Cited by 68 publications

References 23 publications

Relationship between heart rate variability and subclinical thyroid disorders of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Relationship between heart rate variability and subclinical thyroid disorders of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Strengthening Exercises Improve Symptoms and Quality of Life but Do Not Change Autonomic Modulation in Fibromyalgia: A Randomized Clinical Trial

Reference values for short‐term resting‐state heart rate variability in healthy adults: Results from the Brazilian Longitudinal Study of Adult Health—ELSA‐Brasil study

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