Human–Machine coupled modeling of mandibular musculoskeletal multibody system and its application in the designation of mandibular movement function trainer

Abstract

Many patients suffering from oral and maxillofacial tumors present trismus in the six months following mandibulectomy. Traditional mandibular movement function trainers (MMFT) cannot fulfill patient-specific targeted training, but mandibular musculoskeletal modeling can reveal patient-specific muscle recruitment patterns. This study proposed a digital rehabilitation framework for patients via mandibular musculoskeletal simulations. A flexible MMFT consisting of a soft intraoral airbag and a cable-driven extraoral trainer was designed. A human–machine coupling model was established to estimate the patient-specific muscle activations. Here, the intraoral trainer was modeled as a force vector, and the extraoral trainer was discretized by the flexible cable elements via an arbitrary Lagrangian–Eulerian description. Dynamic optimizations were performed to determine the patient-specific auxiliary forces, and the obtained values were utilized to design a quantitative rehabilitation plan. The effectiveness of the MMFT at increasing the magnitude of mandibular opening was validated with in vitro measurements. Numerical predictions for eight patients demonstrated that the proposed rehabilitation framework could improve the patient's jaw opening magnitude by an average of 3.8 ± 2.0 mm, highlighting the importance of subject-specific musculoskeletal modeling in mandibular rehabilitation.