Reliability of Impact Forces, Hip Angles and Velocities during Simulated Forward Falls Using a Novel Propelled Upper Limb Fall ARrest Impact System (PULARIS)
Notice bibliographique
Résumé
Previous forward fall simulation methods have provided good kinematic and kinetic data, but are limited in that they have started the falls from a stationary position and have primarily simulated uni-directional motion. Therefore, a novel Propelled Upper Limb fall ARest Impact System (PULARIS) was designed to address these issues during assessments of a variety of fall scenarios. The purpose of this study was to present PULARIS and evaluate its ability to impact the upper extremities of participants with repeatable velocities, hand forces and hip angles in postures and with vertical and horizontal motion consistent with forward fall arrest. PULARIS consists of four steel tubing crossbars in a scissor-like arrangement that ride on metal trolleys within c-channel tracks in the ceiling. Participants are suspended beneath PULARIS by the legs and torso in a prone position and propelled horizontally via a motor and chain drive until they are quick released, and then impact floor-mounted force platforms with both hands. PULARIS velocity, hip angles and velocities and impact hand forces of ten participants (five male, five female) were collected during three fall types (straight-arm, self-selected and bent-arm) and two fall heights (0.05 m and 0.10 m) to assess the reliability of the impact conditions provided by the system. PULARIS and participant hip velocities were found to be quite repeatable (mean ICC = 0.81) with small between trial errors (mean = 0.03 m/s). The ratio of horizontal to vertical hip velocity components (~0.75) agreed well with previously reported data (0.70-0.80). Peak vertical hand impact forces were also found to be relatively consistent between trials with a mean ICC of 0.73 and mean between trial error of 13.4 N. Up to 83% of the horizontal hand impact forces displayed good to excellent reliability (ICC > 0.6) with small between trial differences. Finally, the ICCs for between trial hip angles were all classified as good to excellent. Overall, PULARIS is a reliable method and is appropriate for studying the response of the distal upper extremity to impact loading during non-stationary, multi-directional movements indicative of a forward fall. This system performed well at different fall heights, and allows for a variety of upper and lower extremity, and hip postures to be tested successfully in different landing scenarios consistent with elderly and sport-related falls.
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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 | 0,002 | 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».