A chairside multimodal platform for temporomandibular joint biomechanical data acquisition: Technical evaluation and illustrative analysis
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Published on: September 13, 2024
Shuchun Sun1, Brooke Damon2, Jichao Zhao2
1Clemson-MUSC Joint Bioengineering Program, Department of Bioengineering, Clemson University, Clemson, SC 29634, United States of America; Department of Oral Health Sciences, Medical University of South Carolina, Charleston, SC 29425, United States of America.
Background:
Temporomandibular joint (TMJ) biomechanics can be characterized by mandibular motion, masticatory muscle activity, and bite force generation. These measurements can provide functional inputs for subject-specific computational analyses of internal joint mechanics. However, existing tools typically measure these signals using separate hardware and software platforms, complicating their combined acquisition at chairside.
Methods:
We developed and technically evaluated a multimodal platform for chairside acquisition of TMJ biomechanical data. The platform integrates motion, bite force, muscle activity, acoustic, and event-timing measurements with software for real-time preview, protocol guidance, and synchronized export. Technical evaluation included rigid-bar tracking tests, spectacle-frame stability testing during jaw tasks, and static force-sensor linearity testing. We analyzed pre- and postoperative data from an orthognathic surgery patient using offline kinematic, force-control, and computational modeling workflows.
Findings:
Rigid-bar tracking tests yielded mean length deviations of 0.03 mm under static conditions and mean RMSE of 0.16 mm during movement. Spectacle-to-maxillary RMS translational and rotational differences were 0.28 ± 0.04 mm and 0.06° (SD < 0.01°) during maximum mouth opening-closing, and 0.30 ± 0.09 mm and 0.13 ± 0.03° during dynamic biting. Linear regression of force-sensor measurements against applied loads of 0-50 N yielded R2 = 0.998. In the illustrative case, platform setup took approximately 15 min, followed by approximately 15 min of chairside data acquisition. Offline analysis yielded pre- and postoperative mandibular kinematic measurements, bite-force tracking deviations, and model-estimated TMJ disc stresses.
Interpretation:
The platform enabled chairside acquisition of multimodal biomechanical data for subsequent offline analysis. This platform could support subject-specific biomechanical analysis and future clinical studies of TMJ function.
