Backed by a century of research and development, Hill-type models of skeletal muscle, often including a muscle-tendon complex and neuromechanical interface, are widely used for countless applications. Lacking recent comprehensive reviews, the field of Hill-type modeling is, however, dense and hard-to-explore, with detrimental consequences on innovation. Here we present the first systematic review of Hill-type muscle modeling. It aims to clarify the literature by detailing its contents and critically discussing the state-of-the-art by identifying the latest advances, current gaps, and potential future directions in Hill-type modeling. For this purpose, fifty-eight criteria-abiding Hill-type models were assessed according to a completeness evaluation, which identified the modelled muscle properties, and a modeling evaluation, which considered the level of validation and reusability of the models, as well as their modeling strategy and calibration. It is concluded that most models (1) do not significantly advance beyond historical foundational standards, (2) neglect the importance of parameter identification, (3) lack robust validation, and (4) are not reusable in other studies. Besides providing a convenient tool supported by extensive supplementary materials for navigating the literature, the results of this review highlight the need for global recommendations in Hill-type modeling to optimize inter-study consistency, knowledge transfer, and model reusability.
Caillet et al. (2025) studied this question.