## 1 Introduction  
Musculoskeletal (MSK) models allow the evaluation of quantities otherwise not directly measurable in vivo, such as muscle and joint internal forces, during gait and other daily tasks. Additionally, they bring the advantages of predictions into the process of designing and personalizing interventions and medical devices. Trusted by the recognized need for personalized medicine [1], the number of studies involving MSK models has increased exponentially in the last twenty years [2]. Despite their potential impact, MSK models are not yet employed on a wide scale in healthcare [3; 4] and a well-established framework to accurately predict neuromuscular-loskeletal dynamics of healthy and pathologic individuals is still lacking [5]. This is also associated to the lack of gold standards, which makes it difficult to quantify the advantages or disadvantages of available approaches [2]. In the attempt to mitigate this problem, several authors have proposed guidelines for the definition and validation of MSK model [2; 3; 6]. Indications on the choice of joint models or, more generally, of the resulting kinematic chain (KC) remain however generic. In [3], the authors suggest choosing \"anatomically based models of musculoskeletal geometry that represent physiological joint kinematics if you are interested in studying internal joint loads\". While reasonable, this indication leaves room for interpretation, and indeed many different joint models and KCs have been used in the literature [7; 8]. Articulations have been modeled as simple ideal spherical, revolute, or universal joints. Alternatively, more advanced joint models have been proposed, such as parallel mechanisms or coupling equations between the joint degrees of freedom (dof). Combining these elements, different KC can be obtained, with a significant effect on the MSK model output [9], due to different accuracy and model sensitivity to parameter variation [10; 11]. The uncertainty related to the KC personalization may further affect MSK model output [12]. In general, no consensus exists on how the joints and KC should be modeled to accurately represent articular anatomy, and how to choose joint models and kinematic chains for a given research question. A possible approach to compare joint models is to evaluate how well they adhere to the hypotheses underlying their definition. A common assumption behind MSK models is that joints behave as ideal, i.e., they are workless joint producing no resistance and deformation over the allowed motions [3]. This reasonable hypothesis, supported by common experience, highly simplifies the computational problem, as it makes the moment equilibrium about the joint axis depending only on the contribution of muscle and external forces and not on the joint constraints. However, for this hypothesis to hold, joint motion should satisfy specific conditions: (i) minimum ligament elongation or cartilage deformation should take place (to not produce deformation work); (ii) ligament and contact resultant forces make no work against joint motion [13; 14]. To be consistent with the articular physiology and MSK hypotheses, any joint model should fulfil this condition. If this does not apply, the model would show an inherent inconsistency which could make estimation of muscle and contact forces unreliable. In practice, the anatomical consistency of a joint model can be quantified computing the ligament elongation and the cartilage co-penetration over the relative motion im-posed by the chosen joint model. The smaller the deformation work, the more consistent the joint model will be with the patient's anatomy and with the MSK hypotheses. The aim of this paper is to show how anatomical consistency can be used to discriminate among different joint models. The method is specifically applied to three ankle joint models with different levels of personalization. We hypothesize that the higher the personalization, the lower the joint work and the higher the anatomical consistency of the model.