2003
DOI: 10.1053/jvet.2003.50058
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An in vivo equine forelimb model for short‐term recording of peak isometric force in the superficial and deep digital flexor muscles

Abstract: Studies using this model will improve knowledge of SDF and DDF muscle mechanics with insight to functional implications of the complex architecture of these muscles. Knowledge of the dynamic performance of the SDF and DDF muscles would also be useful for the development of new treatment strategies for flexor deformities and tendon injuries in horses.

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Cited by 6 publications
(5 citation statements)
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References 50 publications
(76 reference statements)
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“…Segment inertial properties, 8 muscle force‐generating information 12,27–29 and joint kinematics 8 (in two dimensions) were defined to complete the musculoskeletal model in SIMM ® 26 …”
Section: Discussionmentioning
confidence: 99%
“…Segment inertial properties, 8 muscle force‐generating information 12,27–29 and joint kinematics 8 (in two dimensions) were defined to complete the musculoskeletal model in SIMM ® 26 …”
Section: Discussionmentioning
confidence: 99%
“…Larger muscle forces might have been achieved had different neuro-muscular stimulation settings been used or had the anesthesia time been shorter. However, the stimulation parameters were chosen to provide the largest active muscle forces while minimizing muscle fatigue and avoiding co-contraction of adjacent muscles through direct intermuscular conduction (Zarucco et al, 2003). Although the experimental protocol resulted in prolonged anesthesia, horse temperature, oxygenation, blood gases, and electrolytes were maintained at or close to physiologic levels to optimize muscle stimulations under the circumstances of the study (Driessen et al, 2002).…”
Section: Discussionmentioning
confidence: 99%
“…The limb was prepared for data collection as previously described (Zarucco et al, 2003). Briefly, the median and ulnar nerves were instrumented with cuff electrodes (Micro Probe, Inc., NC452 & NC552) for stimulation to elicit muscle contractions.…”
Section: Methodsmentioning
confidence: 99%
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“…Computational modelling represents a viable alternative to experimentation in the field of biomechanics. In particular, numerical multibody models have proven to be a valuable tool for addressing open issues related to the musculoskeletal system as well as improving the understanding of complex anatomical structures, such as those constituting diarthrodial joints [5][6][7]. By exploiting these models, internal forces that cannot be measured in vivo directly (e.g., intra-articular contact forces) can be estimated to enable the identification of detrimental biomechanical conditions and allow the prediction of injuries [8,9].…”
Section: Introductionmentioning
confidence: 99%