Monitoring Gait Complexity as an Indicator for Running-Related Injury Risk in Collegiate Cross-Country Runners: A Proof-of-Concept Study
Notice bibliographique
Résumé
Dynamical systems theory suggests that studying the complexity of biological signals could lead to a single gait metric that reliably predicts risk of running-related injury (RRI). The purposes of this pilot study were to examine center of mass (COM) acceleration complexity at baseline, prior to RRI, and the change between timepoints between collegiate runners who developed RRI during a competitive season and those who remained uninjured, and to determine if complexity at these timepoints was associated with increased odds of RRI. Twenty-two collegiate runners from the same cross-country team wore a waist-mounted triaxial accelerometer (100 Hz) during easy-intensity runs throughout the competitive season. RRIs requiring medical attention were reported via an online survey. Control entropy was used to estimate the complexity of the resultant COM acceleration recorded during each run. Associations between complexity and RRI were assessed using a frequency-matching strategy where uninjured participants were paired with injured participants using complexity from the most time-proximal run prior to RRI. Seven runners sustained an RRI. No significant differences were observed between injured and uninjured groups for baseline complexity ( p = 0.364, d = 0.405), pre-injury complexity ( p = 0.258, d = 0.581), or change from baseline to pre-injury ( p = 0.101, d = 0.963). There were no statistically significant associations found between complexity and RRI risk. Although no significant associations were found, the median effect from the models indicated that an increase in baseline complexity, pre-injury complexity, and change in complexity from baseline each corresponded to an increased odds of sustaining an RRI [baseline: odds ratio (OR) = 1.560, 95% CI = 0.587–4.143, p = 0.372; pre-injury: OR = 1.926, 95% CI: 0.689–5.382, p = 0.211; change from baseline: OR = 1.119; 95% CI: 0.839–1.491, p = 0.445). Despite non-significance and wide confidence intervals that included both positive and negative associations, the point estimates for >98% of the 10,000 frequency-case–control-matched model fits indicated that matching strategy did not influence the directionality of the association estimates between complexity and RRI risk (i.e., odds ratio >1.0). This pilot study demonstrates initial feasibility that additional research may support COM acceleration complexity as a useful single-metric monitoring system for RRI risk during real-world training. Follow-up work should assess longitudinal associations between gait complexity and running-related injury in larger cohorts.
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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) | 0,001 | 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 ».