Our work on Jaw Movement
Relationship between anterior occlusion, arch dimension, and mandibular movement during speech articulation
to use 3-dimensional intraoral scanning, computer-aided design, electrognathography, and artificial intelligence to investigate the relationships between anterior occlusion and arch parameters with hard and soft tissue displacements during speech production.
Predicting freeway space utilising clinical history, normalised muscle activity, dental occlusion, and mandibular movement analysis
This study aimed to predict dental freeway space by examining the clinical history, habits, occlusal parameters, mandibular hard tissue movement, soft tissue motion, muscle activity, and temporomandibular joint function of 66 participants.
Predicting masticatory muscle activity and deviations in mouth opening
This study investigated the predictive potential of normalised muscle activity during various jaw movements combined with temporomandibular joint (TMJ) vibration analyses to predict expected maximum lateral deviation during mouth opening.
Variables Associated with Jaw Clicking in a South Australian
Population: A Cross-Sectional Study
This study investigated the potential significant associations between specific aspects of patient histories, occlusal therapy, and self-reported or observed jaw clicking in a population from the state of South Australia.
Dental loop signals: Image-to-signal processing for mandibular electromyography
Dental Loop Signals (DLS) offers a unique approach to biomedical signal-processing, employing deep learning to convert archived images of mandibular muscle activity during dynamic functions into signal data. DLS, processed through unsupervised learning, introduces a cluster-centric signal processing method, enhancing data normalisation for broad applicability.
Facial landmark and habitual head tilt tracking
This study compared the accuracy of facial landmark measurements using deep learning-based fiducial marker (FM) and arbitrary width reference (AWR) approaches. It quantitatively analysed mandibular hard and soft tissue lateral excursions and head tilting from consumer camera footage of 37 participants.
Dental loop SnP: Speech and phonetic pattern recognition
Dental Loop SnP represents a pioneering python-based software application tailored to analyse phonetic speech patterns in patients and research. By extracting audio from video recordings that capture patients speaking, the software applies an AI-driven text-to-speech engine to create accurate reference speech samples. These samples are further processed through automated audio segmentation and subjected to statistical and spectral phonetic analysis techniques, resulting in the generation of diverse graphical data. The software's modular design allows for easy expansion by incorporating new phonemes and keywords, rendering it a highly adaptable and customisable tool in the realms of dentistry, speech therapy and craniofacial research.
Dental loop FLT: Facial landmark tracking
Dental Loop FLT was developed to address the issue by incorporating advanced methodologies such as Dlib and FAN together into a useable interface for real-time object detection and landmark analysis. This promising approach provides a feasible means to evaluate and assess the intricate facial landmark measurements associated with soft tissue dynamics, thus enhancing the scope of both retrospective and real-time clinical research endeavours.
Variables influencing the device-dependent approaches in digitally analysing jaw movement—a systematic review
To explore the digitisation of jaw movement trajectories through devices and discuss the physiological factors and device-dependent variables with their subsequent effects on the jaw movement analyses
Clinical machine learning in parafunctional and altered functional occlusion: A systematic review
The purpose of this study was to systematically critique the digital methods and techniques used to deploy automated diagnostic tools in the clinical evaluation of altered functional and parafunctional occlusion.
Hormones and other associated factors that shape jaw movement and growth: A Systematic Review of Clinical and Radiographic Evidence
To investigate the influence of endogenous and exogenous neuroendocrine analogues on the range and motion of jaw movement, mandibular growth, and factors affecting condylar guidance in patients with temporomandibular joint disorders using clinical assessment and radiographic imaging
Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review
The study explored the clinical influence, effectiveness, limitations, and human comparison outcomes of machine learning in diagnosing (1) dental diseases, (2) periodontal diseases, (3) trauma and neuralgias, (4) cysts and tumors, (5) glandular disorders, and (6) bone and temporomandibular joint as possible causes of dental and orofacial pain
