Paul-Otto Müller

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.

Temporomandibular disorders affect a significant portion of the population, often causing pain and restricted jaw movement. Physiotherapy with active jaw exoskeletons seems to be a promising treatment approach. However, there has been limited progress in this area, with only a few studies published. The lack of detailed simulations and biomechanical jaw models in these papers impedes the design and validation of such devices. Thus, this work presents an open-source and extendable jaw model framework to support the development of jaw exoskeletons for TMD rehabilitation. The framework includes three model variants with varying complexity: a rigid body model with point-on-surface constraints, a rigid body model with mesh geometry constraints, and a hybrid model combining rigid dynamics with finite element methods. Model customization is facilitated through JSON configuration files, requiring minimal programming expertise. The framework was evaluated using experimental kinematic data from a single participant, with muscle excitations computed via PID controllers tuned through global optimization. The models successfully reproduced jaw movements without prior individualization, demonstrating their suitability for prototyping and studying exoskeleton behavior. The basic models are ideal for rapid prototyping, while the hybrid model provides insights into the effects of exoskeletons on the masticatory system. This framework establishes a foundation for advancing jaw exoskeleton development, with future work focusing on patient-specific modeling, improved anatomical detail, and tools for exoskeleton control and design. The framework code is publicly available and can be found at https://github.com/paulotto/exosim.