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Comparison Of Habitual Physical Activity Measured By Heart Rate And By Accelerometry In Cerebral Palsy

2005· article· en· W4239434184 on OpenAlexaff
Désirée B. Maltais, Oded Bar‐Or

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2005
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCerebral palsyHeart ratePercentilePopulationAccelerometerPhysical medicine and rehabilitationGross Motor Function Classification SystemEnergy expenditureMedicineGaitPhysical therapyPreferred walking speedSpastic cerebral palsySpasticInternal medicineMathematicsStatisticsBlood pressurePhysics

Abstract

fetched live from OpenAlex

Physical activity (PA) has physiologic, mechanical and behavioral components. We have previously shown that for children and adolescents with mild spastic cerebral palsy (CP), their habitual PA measured physiologically with monitored heart rate (HR) is related to their physiologic walking economy (oxygen cost of walking). We have also shown for this population that their habitual PA measured mechanically with tri-axial accelerometry is related to their biomechanical walking economy (vertical excursion of the center of mass relative to that expected in normal gait). In both instances, those with the higher levels of PA were the more economical walkers. The relationship between physiologic and mechanical measures of PA in this population, however, is unknown. PURPOSE To determine, in children and adolescents with cerebral palsy (CP), the relationship between; 1) habitual PA as measured by monitored HR and by tri-axial accelerometry and 2) habitual PA and gross motor function related to walking (GMF-W). METHODS Ten subjects (10.6–16.3 yr) with mild spastic CP, simultaneously wore a HR monitor and a tri-axial accelerometer for two weekdays and one weekend day. PAL, the ratio of total energy expenditure to resting energy expenditure, was determined from the monitored HR data, with individual HR-oxygen uptake calibrations and resting measures done in the lab. From the accelerometry data, total vector magnitude movement counts ± d−1 (TMC) and the number of minutes ± d−1 TMC were above the 90th percentile for the group (TMC90) were determined. GMF-W was measured in the lab using the Walking, Running and Jumping Dimension of the Gross Motor Function Measure. Relationships were analyzed using linear regression techniques. Alpha was set at .05. RESULTS PAL (1.33 ± .04) was significantly related (r=.75) to TMC (1.53 ± 105 ± 1.4 ± 104 counts) and (r=.78) to TMC90 (59.8 ± 8.1 minutes). PAL was also significantly related (r=.82) to GMF-W (82.1 ± 5.6%) as were TMC (r=.89) and TMC90 (r=.90). There was no significant relationship for PAL, TMC, TMC90 or GMF-W with age (r=.00001 to .21, P=.60 to 1.0). CONCLUSIONS For older children and adolescents with mild CP, those with higher levels of the physiologic component of PA, may also have higher levels of the mechanical component. Those with higher levels of either component of habitual PA, may also have the better gross motor function related to walking. Further research is needed to determine if, and to what extent, this gross motor function is related to metabolic and mechanical walking economy.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.327
Teacher spread0.300 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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