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Experimental investigation of muscle-tendon unit geometry and kinematics in lower-limb muscles during gait: Current Applications and Future Directions - A Scoping Review

Lecharte, T.; Leboeuf, F.; Gross, R.; Nordez, A.; Le Sant, G.; Dussault-Picard, C.

2025-09-18 rehabilitation medicine and physical therapy
10.1101/2025.09.16.25335871 medRxiv
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PurposeMusculoskeletal (MSK) modeling and ultrasound imaging (USI) are complementary techniques that, when combined with three-dimensional gait analysis (3DGA), provide insights into muscle and/or muscle-tendon unit (MTU) characteristics during gait. Despite their potential, a synthesis of their current use during 3DGA in populations with neuromotor impairments has not been conducted. This scoping review aimed to examine how MSK modeling and USI are used alongside 3DGA to assess muscle and MTU characteristics in populations with neuromotor impairments and evaluate the potential clinical implications of these approaches on clinical assessment and decision-making. ResultsThree databases were searched up to February 2025, yielding 50 studies (42 studies used MSK modeling, 5 used USI, and 3 employed both), including 4 pathological populations (cerebral palsy, stroke, hereditary spastic paraparesis, and idiopathic toe walking), and analyzing 11 lower-limb muscles. Both MSK modeling and USI have enabled the assessment of muscle or MTU length during gait, and detection of abnormal MTU. Only MSK modeling was used to assess MTU lengthening velocity, interventions effects, and predictors of surgical outcomes. MSK modeling appears limited by modeling assumptions and lack of real-time data, whereas USI faces constraints related to data acquisition complexity and processing challenges. ConclusionsThis review enhances understanding of neuromuscular impairments and current uses of MSK modeling and USI in clinical populations. It highlights their complementary potential with 3DGA to support personalized clinical decision-making. Future work should include broader neuromotor conditions and explore automated data analysis (e.g., deep learning for USI) to improve clinical applicability.

Published in Gait & Posture · not in our set (fewer than 10 published preprints to learn from) · training set

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