Passive coordination of hind limb joints through multi-joint muscles
Bibliographic record
Abstract
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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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".