VALIDITY OF ASSESSMENT OF DAILY ENERGY EXPENDITURE IN A RESPIRATION CHAMBER BY ACCELEROMETRY LOCATED ON THE WAIST VS THE WRIST OR IN COMBINATION
Bibliographic record
Abstract
PURPOSE: We have reported that the energy expenditure (EE) estimated by uniaxial accelerometry in the vertical plane (Lifecorder, Suzuken Co.; LC) located on the waist was highly correlated with EE measured in a respiration chamber (MSSE.33:s251,2001). On the other hand, slight movements of the limbs (i.e. fidgeting) also seem to play an important role in daily EE. The purpose of this study was to investigate the validity of accelerometry as a predictor of daily EE when two accelerometers are used separately, one on the wrist and the other one on the waist levels, or in combination. METHODS: In 55 healthy Japanese (37+/− 12 y of age, BMI = 21.7+/− 3.3 kg/m2) we measured 24-h EE in a respiration chamber. The subjects were prescribed two 30 min walking exercises on the treadmill (3.9, 5.1km/h, flat) and the sleeping duration was controlled (for 8-h). The subjects wore two LCs, one on the belt (LCbeit) and the other one on the wrist of the dominant arm (LCwrist). Linear regressions were calculated between measured EE normalized for body weight (kcal/kg*h) and LC activity levels assessed by acceleration (11 levels; 0, 0.5 and 1 to 9), and LCbeit vs LCwrist after these values were averaged over 15-min periods for a total of 16-h. RESULTS: There were highly significant relationships between EE and both accelerometric measures. The degree of correlation between LCbeit and EE was higher than that between LCwrist and EE: r = 0.817 p < 0.001, SEE = 0.41 vs r = 0.694 p < 0.001, SEE = 0.51, respectively. If treadmill walking periods are not considered, both correlations were found to be lower: r = 0.557 p < 0.001, SEE = 0.38 vs r = 0.476 p < 0.001, SEE = 0.40, respectively. When multiple regression analysis was used to explore the effect of the addition of LCwrist to LCbeit, the variance improved only by 0.8% including treadmill periods and 2.5% excluding treadmill periods. There were significant relationships between the activity levels measured by the 2 accelerations locations: r = 0.782 p < 0.001 with treadmill periods, r = 0.629 p < 0.001 without treadmill periods. CONCLUSION: Adding LCwrist to LCbeit did not substantially improve the degree of prediction of daily energy expenditure. As a result, single accelerometer located on the waist level has sufficient validity for the estimation of the daily energy expenditure in confined conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".