Clinical validation of the TMD-E tracker for diagnosing temporomandibular disorders: a reliability and accuracy assessment - Ramya Srinivasan; Shilpi Gupta; Naveen Gopi Chander; Anitha Kuttae Viswanathan (Journal of Oral Biology and Craniofacial Research)
Aim: Temporomandibular disorders (TMDs) are musculoskeletal conditions affecting the temporomandibular joint (TMJ), often leading to pain, restricted movement, and joint sounds. Traditional diagnostic methods rely on subjective assessments and imaging, which have limitations in terms of accessibility and cost. The TMD-E Tracker is a novel, non-invasive device designed to quantify TMJ vibrations and classify TMD severity in real time. This study aimed to assess the diagnostic accuracy, reliability, and feasibility of the TMD-E Tracker in detecting TMDs and to compare its findings with standard clinical diagnostic methods. Materials and methods: A total of 24 participants (12 TMD patients, 12 healthy individuals) were evaluated using the TMD-E Tracker. The device recorded peak vibrational frequency and timing of peak occurrence, which were statistically compared with standard clinical diagnostic measures. Intra- and inter-examiner reliability were assessed using the Intraclass Correlation Coefficient (ICC). Statistical analysis was performed using independent t-tests with p < 0.05 considered significant. Results: TMD patients exhibited a significantly higher peak frequency (248 ± 28 Hz) and delayed peak occurrence timing (1.65 ± 0.38 s) compared to healthy individuals (108 ± 22 Hz, 0.95 ± 0.21 s, p < 0.05). The device demonstrated excellent intra-examiner reliability (ICC = 0.91) and inter-examiner reliability (ICC = 0.89). The sensitivity (89.5 %) and specificity (92.3 %) further confirmed the high diagnostic accuracy of the TMD-E Tracker. Conclusion: The TMD-E Tracker is a reliable, objective, and clinically feasible diagnostic tool for TMD assessment. Its real-time vibrational analysis offers a promising alternative to conventional diagnostic methods, though further large-scale validation is warranted.