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Abstract Mandibular movement is complex and individual due to variations in the temporomandibular joint (TMJ). Consequently, patient-centered dentistry should incorporate patients’ specific anatomy and condylar function in treatment planning. Real-time magnetic resonance imaging (rt-MRI) visualizes relevant structures and tracks mandibular movement. However, current assessments rely on qualitative observations or time-consuming manual tracking, lacking reliability. This study developed an automatic tracking algorithm for mandibular movement in rt-MRI using least mean square registration (LMS) and compared it to manual tracking (MT) during mouth opening. Ten participants with skeletal class I underwent rt-MRI (10 frames/s). The same operator tracked the condylar pathway for the two methods, setting 2000 landmarks (2 landmarks x100 frames x10 participants) for MT and 210 landmarks (3 landmarks x7 frames x10 participants) for LMS. Time required, superimposition error, and the distance between tracked condylar pathways were compared between methods. LMS tracking was 76% faster and showed significantly better superimposition (0.0289 ± 0.0058) than MT (0.059 ± 0.0145) (p = 0.002). During one-third of the movement, the pathways tracked by both methods were more than 1 mm and 1° apart. These findings highlight the benefits of automatic condylar movement tracking in rt-MRI, laying the groundwork for more objective and quantitative observation of TMJ function.

Abstract Background Real-time magnetic resonance imaging (rtMRI) is essential for diagnosing and comprehending temporomandibular joint (TMJ) movements. Current methods for tracking and analysis require manual landmark placement on each acquisition frame. Therefore, our study aimed to assess the inter- and intra-rater reliability of placing cephalometric landmarks in frames from a dynamic real-time TMJ MRI. Material and methods Four real-time MRIs of the right TMJ were taken during mandibular movement at ten frames per second. Seven dentists identified ten landmarks on two frames (intercuspal position—ICP—and maximum mouth opening—MMO) twice at a two-week interval, yielding 112 tracings. Six typical cephalometric measurements (angles and distances) were derived from these landmarks. The reliabilities of landmarks and measurements were evaluated using distance-based (dbICC), linear mixed effect model intraclass correlation (lmeICC), and standard ICC. Results The average inter-rater reliability for the landmarks stood at 0.92 (dbICC) and 0.93 (lmeICC). The intra-rater reliability scores were 0.97 and 0.98. Over 80% of the landmarks showed an ICC greater than 0.98 (inter-rater) and over 0.99 (intra-rater). The lowest landmark ICC was observed for the orbitale and the oblique ridge of the mandibular ramus. However, the cephalometric angle and distance measurements derived from these landmarks showed only moderate to good reliability, whereas the reliability in the frames with ICP was better than those with MMO. Measurements performed in the ICP frame were more reliable than measurements in the MMO frame. Conclusion While dentists reliably localize isolated landmarks in real-time MRIs, the cephalometric measurements derived from them remain inconsistent. The better results in ICP than MMO are probably due to a more familiar jaw position. The higher error rate of the TMJ measurements in MMO could be associated with a lack of training in real-time MRI analysis in dentistry.

Semi-autonomous (SA) control of upper-limb prostheses can improve the performance and decrease the cognitive burden of a user. In this approach, a prosthesis is equipped with additional sensors (e.g., computer vision) that provide contextual information and enable the system to accomplish some tasks automatically. Autonomous control is fused with a volitional input of a user to compute the commands that are sent to the prosthesis. Although several promising prototypes demonstrating the potential of this approach have been presented, methods to integrate the two control streams (i.e., autonomous and volitional) have not been systematically investigated. In the present study, we implemented three shared control modalities (i.e., sequential, simultaneous, and continuous) and compared their performance, as well as the cognitive and physical burdens imposed on the user. In the sequential approach, the volitional input disabled the autonomous control. In the simultaneous approach, the volitional input to a specific degree of freedom (DoF) activated autonomous control of other DoFs, whereas in the continuous approach, autonomous control was always active except for the DoFs controlled by the user. The experiment was conducted in ten able-bodied subjects, and these subjects used an SA prosthesis to perform reach-and-grasp tasks while reacting to audio cues (dual tasking). The results demonstrated that, compared to the manual baseline (volitional control only), all three SA modalities accomplished the task in a shorter time and resulted in less volitional control input. The simultaneous SA modality performed worse than the sequential and continuous SA approaches. When systematic errors were introduced in the autonomous controller to generate a mismatch between the goals of the user and controller, the performance of SA modalities substantially decreased, even below the manual baseline. The sequential SA scheme was the least impacted one in terms of errors. The present study demonstrates that a specific approach for integrating volitional and autonomous control is indeed an important factor that significantly affects the performance and physical and cognitive load, and therefore these should be considered when designing SA prostheses.