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Record W1970353994 · doi:10.1191/0269215505cr823oa

Measuring energy expenditure using heart rate to assess the effects of wheelchair tyre pressure

2005· article· en· W1970353994 on OpenAlexaff
Bonita Sawatzky, William C. Miller, Ian Denison

Bibliographic record

VenueClinical Rehabilitation · 2005
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsGF Strong Rehabilitation CentreVancouver Coastal HealthUniversity of British Columbia
FundersFundação para a Ciência e a Tecnologia
KeywordsHeart rateEnergy expenditureWheelchairSpinal cord injuryMedicinePhysical therapyBlood pressurePhysical medicine and rehabilitationCardiologyAnesthesiaSpinal cordInternal medicineComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the effects of wheelchair tyre pressure on mechanics and energy and explore the use of heart rate as a measurement of energy expenditure. DESIGN: A single factor repeated measures design was used. Four tyre pressures (100, 75, 50, 25 psi) represented a change of workload. Each subject wheeled at a constant self-selected wheeling velocity for 8 min. A total of four trials were completed with a 10-min rest between trials. Oxygen consumption, heart rate and distance travelled were collected during each trial. SUBJECTS: Three women and 11 men with spinal cord injury. The mean age for the whole group was 34.5 years. The range of lesion level was T4-L1. RESULTS: There was a significant increase is energy expenditure when tyres were deflated to 50 psi from 100 psi. The mean correlation between heart rate and oxygen consumption was 0.74 for all subjects. For the subjects with lesions above T6 and T6 and below the correlations were 0.55 and 0.82, respectively. CONCLUSIONS: Tyre pressures below 50% inflation add an additional 25% increase in energy expenditure during wheeling. This could be detected using oxygen consumption or heart rate, as heart rate was shown to have a good correlation with oxygen consumption in the spinal cord injured with lesions below T5. Heart rate does have its limitations and it should only be used to measure within-subject differences.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.136
GPT teacher head0.464
Teacher spread0.328 · 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 teacher head, not a consensus.

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

Citations31
Published2005
Admission routes1
Has abstractyes

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