Paul-Otto Müller

Temporomandibular disorders substantially affect and impair jaw functions and thus the quality of life. Yet, powered assistance for jaw rehabilitation remains widely unexplored despite advances in exoskeletons for other extremities. To the best of our knowledge, this work presents the first comprehensive computational framework for hybrid rigid-soft jaw exoskeletons, integrating a biomechanically validated 24-muscle jaw model with deformable finite element soft-body dynamics in MuJoCo. The proposed four-tendon system combines a rigid chin cup for force transmission with a compliant facial mask for user comfort. Simulation-based evaluation under six configurations (TPU/Silicone materials, muscles-only/tendons-only/combined actuation) demonstrates effective trajectory tracking with mean errors of 4.60-6.42 mm while maintaining safe interface pressures and material stresses. Critical findings reveal fundamental performance-comfort trade-offs: TPU enables efficient force transmission with lower mean strain (11.49 % vs 14.06 %) but higher mean pressure (12.02 kPa vs 9.89 kPa) than silicone. Mean tendon forces of 24.63-35.46 N in tendons-only mode achieve effective assistance, yet combined actuation paradoxically increases biological muscle loading by 6-10 % despite improved tracking, guiding future control strategies toward biomechanical- and metabolically-aware algorithms. This validated open-source computational framework establishes essential safety constraints and design prerequisites for physical prototyping, providing a systematic path toward safe, wearable robot-assisted therapy for temporomandibular disorders.

Precise tracking of the jaw kinematics is crucial for diagnosing various musculoskeletal and neuromuscular diseases affecting the masticatory system and for advancing rehabilitative devices such as jaw exoskeletons, a hardly explored research field, to treat these disorders. We introduce an open-source, low-cost, precise, non-invasive, and biocompatible jaw tracking system based on optical motion capture technology to address the need for accessible and adaptable research tools. The system encompasses a complete pipeline from data acquisition, processing, and kinematic analysis to filtering, visualization, and data storage. We evaluated its performance and feasibility in experiments with four participants executing various jaw movements. The system demonstrated reliable kinematic tracking with an estimated precision of (182 ± 47) μm and (0.126 ± 0.034) °. Therefore, the open-source nature of the system and its utility comparable to commercial systems make it suitable for many research and development contexts, especially for applications such as the integration and design of jaw exoskeletons and customized diagnostic protocols. The complete system is available at GitHub with the aim of promoting innovation in temporomandibular disorders research and jaw assistive technology.

Despite the many technological advancements in exoskeletons for the rehabilitation of lower or upper limbs, there has been limited exploration of their application in treating temporomandibular disorders, a set of musculoskeletal and neuromuscular conditions affecting the masticatory system. By collecting data, implementing assisting and resisting training routines, and encouraging active patient engagement, exoskeletons could provide controlled and individualized exercise with flexibility in time and location to aid in the recovery or improvement of jaw mobility and function. Thus, they might offer a valuable alternative or complement to conservative physiotherapy. In this context, the review aims to draw attention to rehabilitating temporomandibular disorders with the help of exoskeletons by looking at the advantages and opportunities these devices potentially provide. After stating the requirements and resulting scientific challenges in various fields and discussing the state of the art, existing research gaps and deficiencies will be discussed, highlighting areas where further research and development is needed.