WITHDRAWN: Detection of Temporomandibular Joint Disorder Using Surface Electromyography by Supervised Classification Models

Autor:	Roopa B. Kakkeri, D. S. Bormane
Rok vydání:	2021
Předmět:	Orthodontics education.field_of_study TMJ disorders medicine.diagnostic_test business.industry Population Signs and symptoms General Medicine Electromyography medicine.disease Masticatory force medicine Temporomandibular Joint Disorder AdaBoost education Set (psychology) business
Zdroj:	Materials Today: Proceedings.
ISSN:	2214-7853
DOI:	10.1016/j.matpr.2021.07.375
Popis:	Temporomandibular joint disorder (TMD) is a complex disorder with multiple signs and symptoms. It mainly involve set of musculoskeletal disorders which may affect the neck, shoulder and masticatory system. It is estimated that around 60 to70% of population has at least one of the symptoms. This disorder is highly prevalent in general population but females are affected more with a ratio of 4:1. By using Surface electromyography (SEMG) recording technique, the data were collected and results were assessed. Performance parameters of different machine learning models were tested for Optimized features. After the analysis with various machine learning models, the results shows that the Adaboost machine learning model for the detection of TMJ disorder using SEMG of masticatory muscles gives the best results compared to all other algorithms. Result shows a classification accuracy percent of 98.5 per 10 optimized features.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e1ac14c0f664e3421450c63f2ac0baf4 https://doi.org/10.1016/j.matpr.2021.07.375 Zobrazit plný text záznamu Full Text from ScienceDirect