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Record W2060898018 · doi:10.2746/042516400776563572

Frequency domain analysis of heart rate variability in horses at rest and during exercise

2000· article· en· W2060898018 on OpenAlexaff
Peter W. Physick‐Sheard, D. J. MARLIN, Rebecca E. Thornhill, R. C. Schroter

Bibliographic record

VenueEquine Veterinary Journal · 2000
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHeart rate variabilityHeart rateBeat (acoustics)Autonomic nervous systemTreadmillCardiologyInternal medicineHorseMedicineAnimal sciencePhysical therapyBlood pressurePhysicsBiologyAcoustics

Abstract

fetched live from OpenAlex

The pattern of variation in heart rate on a beat-to-beat basis contains information concerning sympathetic (SNS) and parasympathetic (PNS) contributions to autonomic nervous system (ANS) modulation of heart rate (HR). In the present study, heart period (RR interval) time series data were collected at rest and during 3 different treadmill exercise protocols from 6 Thoroughbred horses. Frequency and spectral power were determined in 3 frequency bands: very low (VLF) 0-< or = 0.01, low (LO) >0.01-< or = 0.07 and high (HI) >0.07-< or = 0.5 cycles/beat. Indicators of sympathetic (SNSI = LO/HI) and parasympathetic (PNSI = HI/TOTAL) activity were calculated. Power in all bands fell progressively with increasing exercise intensity from rest to trot. At the gallop VLF and LO power continued to fall but HI power rose. SNSI rose from rest to walk, then fell with increasing effort and was lowest at the gallop. PNSI fell from rest to walk, then rose and was highest at the gallop. Normalised HI power exceeded combined VLF and LO power at all gaits, with the ratio HI to LO power being lowest at the walk and highest at the gallop. ANS indicators showed considerable inter-horse variation, and varied less consistently than raw power with increasing physical effort. In the horses studied, the relationship between power and HR changed at exercise intensities associated with heart rates above approximately 120-130 beats/min. At this level, humoral and other non-neural mechanisms may become more important than autonomic modulation in influencing heart rate and heart rate variability (HRV). HRV at intense effort may be influenced by respiratory-gait entrainment, energetics of locomotion and work of breathing. HRV analysis in the frequency domain would appear to be of potential value as a noninvasive means of assessing autonomic modulation of heart rate at low exercise intensities, only. The technique may be a sensitive method for assessing exercise response to experimental manipulations and disease states.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.362
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations97
Published2000
Admission routes1
Has abstractyes

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