Validation of a leg-mounted pedometer for the measurement of steps in lactating Holstein cows
Notice bibliographique
Résumé
The aim of this study was to validate the pedometer AfiAct II (AfiMilk) for the measurement of steps in lactating Holstein cows housed in a freestall design by assessing its agreement with visual observation of step counts. A total of 41 primiparous (n = 12) and multiparous (n = 29) cows were enrolled in the study between August and September 2018. Steps were monitored continuously by the pedometer and visually assessed for a 24-h period using video recordings. Visually observed steps were categorized as walking and stationary steps. The total number of steps taken per cow was calculated using the sum of walking and stationary steps. Unprocessed step count data from the study day were retrieved from the AfiMilk system in time-blocks of approximately 15 min. Repeated measures correlation was used to quantify the association between the pedometer measurements and visual observation of step counts. Nonindependence among observations were accounted adjusting for interindividual (cow) variability with an analysis of covariance. Pearson correlation coefficients (r) were categorized from negligible (0.00-0.30) to very high (0.90-1.00). Bland-Altman plots were created to evaluate the bias between the pedometer and visual observations. A total of 2,261 time-blocks were used in this study with an average (mean ± standard deviation) of 55.14 ± 8.1 time-blocks per cow. A high correlation was found for the evaluation between the pedometer and observed walking steps (r = 0.74; 95% confidence interval [CI] = 0.73-0.76), stationary steps (r = 0.71; 95% CI = 0.69-0.63), and total steps (r = 0.88; 95% CI = 0.87-0.89). The results of the Bland-Altman plot suggested limited bias between the pedometer step counts and visual observation of steps, independent of the type of steps. Numerical differences and several time-block differences outside of the 95% interval of agreement suggested an overestimation of step counts by the pedometer, which increased as the number of steps increased. The pedometer measured, on average, 97.6 ± 118.5 (28%), 249.2 ± 126.2 (125%), and 297.2 ± 205.4 (196%) steps/day more than the visual observed total steps, stationary steps, and walking steps, respectively. Our findings indicate that the pedometer counts all movement in which the pedometer leg is lifted off the floor without distinguishing if there was body movement of the animal.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».