Evidence map›Paper›PMID 26832134›Full record

ArticleEuropean journal of applied physiology2016

The relationships between heart rate deceleration capacity and spectral indices of heart rate variability during different breathing frequencies.

Yong-Ping Wang, Terry B J Kuo, Jia-Yi Li, Chun-Ting Lai, Cheryl C H Yang

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Article in European journal of applied physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
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  5. Article
  6. Effects of intranasal kinetic oscillation stimulation on heart rate variability.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2018
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5 · Who and what money

Authors and funding

5 authors.

Yong-Ping WangDepartment of Anesthesiology, National Taiwan University Hospital, Taipei, Taiwan.
Terry B J KuoInstitute of Brain Science, National Yang-Ming University, No. 155, Sec. 2, Li-Nong Street, Taipei, 11221, Taiwan.
Jia-Yi LiInstitute of Brain Science, National Yang-Ming University, No. 155, Sec. 2, Li-Nong Street, Taipei, 11221, Taiwan.
Chun-Ting LaiInstitute of Brain Science, National Yang-Ming University, No. 155, Sec. 2, Li-Nong Street, Taipei, 11221, Taiwan.
Cheryl C H YangInstitute of Brain Science, National Yang-Ming University, No. 155, Sec. 2, Li-Nong Street, Taipei, 11221, Taiwan. cchyang@ym.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe frequency of breathing influences the spectral powers of heart rate variability (HRV) as well as the magnitudes of heart rate deceleration capacity (DC) and acceleration capacity (AC). We compared the strength of their relationships under different breathing frequencies.

methodsWe studied 14 healthy young adults who breathed spontaneously and controlled their breathing rates to 0.1, 0.2, 0.3 and 0.4 Hz in a supine position. A 5-min R-R interval time series without movement artefacts or ectopic beats was obtained for each study period. Spectral indices were defined as the square roots of spectral powers in the very low frequency (0.01-0.04 Hz), low frequency (0.04-0.15 Hz), high frequency (0.15-0.4 Hz) and respiratory frequency bands. We also combined these frequency bands into LHF (0.04-0.4 Hz) and VLHF (0.01-0.4 Hz). DC and AC were obtained using phase rectified signal averaging.

resultsDC and AC were significantly correlated with all indices of HRV. The within-subject correlation coefficients for the LHF index had the greatest absolute values (0.953 and -0.919, respectively). DC and AC had different strength of relationships with the LHF index, but became comparable (0.954 vs. -0.943) when the data obtained under 0.1-Hz breathing were excluded.

conclusionDC is strongly correlated with the spectral index of the LHF band, indicating that they are controlled by similar influences under the conditions used in this study. AC is less related to the LHF index due to the fact that its magnitude deceases during 0.1-Hz breathing.

Indexed as

AlgorithmsModels, CardiovascularAdultComputer SimulationFemaleHeart RateHeart Rate DeterminationHumansMaleReproducibility of ResultsRespiratory RateRespiratory Sinus ArrhythmiaSensitivity and SpecificityAccelerationDecelerationHeart rateRespirationSpectral analysis

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.