Passive coordination of hind limb joints through multi-joint muscles
Notice bibliographique
Résumé
PASSIVE COORDINATION OF HIND LIMB JOINTS THROUGH MULTI-JOINT MUSCLES Violet Campbell, Andrew Sawatsky, Walter Herzog Human Performance Lab, University of Calgary, Kinesiology Program, University of Calgary vcampbell@kin.ucalgary.ca INTRODUCTION Studies in cats measuring muscle lengths using joint angles show a clear correlation between the movements at the hip, knee, and ankle joints [2]. This correlation could be explained to 70% by a covariance plane between the hip, knee, and ankle joint angles [1]. It has been suggested that the multi-joint muscles may be the origin of the passive limb mechanics [1,4]. EMG recordings show that during cat locomotion, activation of the muscles extending the knee occurs 30-70msec after the knee extension begins; thus the onset of knee extension seems to be controlled passively by the extensor muscles [3]. Furthermore, it has been said that muscles directly change joint angles [4]. The purpose of this study was to examine the effects of multi-joint muscles on the passive joint alignment in the rabbit hind limb. We hypothesize that the hip, knee, and ankle joint angles in the rabbit hind limb are coordinated by passive forces and the passive joint alignment is controlled primarily by the multi-joint muscles. METHODS Five New Zealand white rabbit cadavers were used. The joints were marked with bone pins, and the condyles of the femur were held and the hip joint was passively moved through its range of motion while associated changes in knee and ankle joint angles were measured. Hind limb joint movements were recorded using high speed video. Individual video frames were then extracted and digitized manually to obtain the hip, knee and ankle joint angles. Variance was approximately ±5o for each of the joint angles in repeat trials of the same animal. The multi-joint muscles including the biceps femoris, rectus femoris, semitendinosus, plantaris, medial and lateral gastrocnemius, extensor digitorum longus and tensor fascia latae were selectively cut in three hind-limbs, and in a different order for each leg, to identify the contribution of each muscle to the passive coordination of the hind-limb joints. RESULTS Before any muscles were cut 80-99% of the variability of the knee and ankle joint angles was explained by variations in the hip angle. As multi-joint muscles were cut sequentially the correlation between hip, knee, and ankle joint angles decreased, and was eventually completely lost (Figure 1). Figure 1. Passive ankle angles (degrees) as a function of hip angles throughout the entire flexion movement and analyzed every 5˚. The data are from three trials of one rabbit’s hind limb. Blue points (± 1SE) represent the intact leg, orange represents the medial and lateral gastrocnemius removed, and the pink points represent the plantaris was removed in addition to the two heads of the gastrocnemius. DISCUSSION AND CONCLUSIONS Removal of selected two joint muscles changed the relationship between passive hip and knee and between passive hip and ankle angles. For example, when removing the gastrocnemius and plantaris muscles, hip motion did not result in any change in the ankle angle, illustrating that all passive force transmission between the two joints hinges crucially on the two-joint triceps surae muscles (Figure 1). In order to identify the precise contribution of each two-joint muscle to passive force transmission across the rabbit hind limb, multiple experiments with different order of cutting the muscles would have to be implemented. Such an extensive experiment was not possible within the framework of this summer. REFERENCES Bosco, et al. J Neurophysiol. 76 :715-726, 1996. Goslow et al. J Morphol . 141 :1-42, 1973. Miller et al. Brain Res. 91 :217-237, 1975. Shen & Poppele J Neurophysiol. 74 :2266-2280, 1995.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 ».