ABSTRACT
BACKGROUND: Temporomandibular disorders (TMDs) are pathological conditions affecting the temporomandibular joint and/or masticatory muscles. The current diagnosis of TMDs is complex and multi-factorial, including questionnaires, medical testing and the use of diagnostic methods, such as computed tomography and magnetic resonance imaging. The evaluation, like the mandibular range of motion, needs the experience of the professional in the field and as such, there is a probability of human error when diagnosing TMD. The aim of this study is therefore to develop a method with infrared cameras, using the maximum range of motion of the jaw and four types of classifiers to help professionals to classify the pathologies of the temporomandibular joint (TMJ) and related muscles in a quantitative way, thus helping to diagnose and follow up on TMD. METHODS: Forty individuals were evaluated and diagnosed using the diagnostic criteria for temporomandibular disorders (DC/TMD) scale, and divided into three groups: 20 healthy individuals (control group CG), 10 individuals with myopathies (MG), 10 individuals with arthropathies (AG). A quantitative assessment was carried out by motion capture. The TMJ movement was captured with camera tracking markers mounted on the face and jaw of each individual. Data was exported and analyzed using a custom-made software. The data was used to identify and place each participant into one of three classes using the K-nearest neighbor (KNN), Random Forest, Naïve Bayes and Support Vector Machine algorithms. RESULTS: Significant precision and accuracy (over 90%) was reached by KNN when classifying the three groups. The other methods tested presented lower values of sensitivity and specificity. CONCLUSION: The quantitative TMD classification method proposed herein has significant precision and accuracy over the DC/TMD standards. However, this should not be used as a standalone tool but as an auxiliary method for diagnostic TMDs.
Subject(s)
Face , Mechanical Phenomena , Temporomandibular Joint Disorders/diagnosis , Adolescent , Adult , Bayes Theorem , Biomechanical Phenomena , Female , Humans , Infrared Rays , Male , Middle Aged , Support Vector Machine , Young AdultABSTRACT
Estímulos leves e intermitentes induzem mudanças na dinâmica mandibular e em sua morfologia. O objetivo deste estudo foi quantificar alterações angulares e lineares em indivíduos com sobremordida profunda, tratados com o equilibrador de Planas. Foram escolhidos 30 indivíduos com sobremordida profunda, dos quais foram obtidos telerradiografias iniciais e finais. Os valores lineares e angulares foram submetidos ao teste "t" de Student. Houve aumento significativo nas medidas lineares, na inclinação dos incisivos inferiores e no eixo de crescimento. Não houve diferença entre a base craniana, o plano maxilar e o plano mandibular, no ângulo mandibular e na inclinação dos incisivos superiores. O Equiplan parece ser eficaz no tratamento da sobremordida profunda, induzindo crescimento dentoalveolar dos molares inferiores, sem provocar intrusão dos incisivos ou interferir na divergência dos planos faciais.
Light and intermittent stimuli induces changes on mandibular dynamics and on its morphology. The aim of the present research was to quantify the angular and linear variations of individuals that presented deep overbite and were treated by Plans equilibrator (equiplan). 30 deep-bite subjects up to 4 mm were selected in this research and their teleradiographies were taken after and before treatment. The values obtained were analyzed by Student "t " test. All linear measurements increased, lower incisors tip and 'y" growth axis too. No lower and upper incisors intrusion occured. There were no differences among cranial basis, maxilar e mandibular planes, mandibular angle and upper incisors tip. The equiplan seems to be efficient in deep bites treatments, inducing lower molar dento-alveolar growth, didnt intrude incisors and didnt change facial planes divergences significantly.
