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Reseach Article

Recording and Measuring of Jaw Movements using a Computer Vision System

by Mahmoud Sedky Adly, Aliaa A.a. Youssif, Ahmed Sharaf Eldin
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 18
Year of Publication: 2013
Authors: Mahmoud Sedky Adly, Aliaa A.a. Youssif, Ahmed Sharaf Eldin
10.5120/14226-2466

Mahmoud Sedky Adly, Aliaa A.a. Youssif, Ahmed Sharaf Eldin . Recording and Measuring of Jaw Movements using a Computer Vision System. International Journal of Computer Applications. 81, 18 ( November 2013), 38-43. DOI=10.5120/14226-2466

@article{ 10.5120/14226-2466,
author = { Mahmoud Sedky Adly, Aliaa A.a. Youssif, Ahmed Sharaf Eldin },
title = { Recording and Measuring of Jaw Movements using a Computer Vision System },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 18 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 38-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number18/14226-2466/ },
doi = { 10.5120/14226-2466 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:25.587136+05:30
%A Mahmoud Sedky Adly
%A Aliaa A.a. Youssif
%A Ahmed Sharaf Eldin
%T Recording and Measuring of Jaw Movements using a Computer Vision System
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 18
%P 38-43
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Human motion detection and analysis are important in many medical and dental clinics. Mandibular movements are very complex and difficult to detect by naked eyes. Detecting mandibular movements will aid in proper diagnosis, treatment planning and follow up. Many methods are utilized for measuring mandibular movements. However, most of these methods share the features of being very expensive and difficult to use in the clinic. Using computer vision systems to track such movements may be considered one of the fundamental problems of human motion analysis that may remain unsolved due to its inherent difficulty. However, using markers may greatly simplify the process as long as they are simple, cheap and easy to use. Unlike other tracking systems, this system needs a simple digital video camera, and very simple markers that are created using black-white images that can be stick using any cheap double-sided bonding tape. The proposed system is considered reliable and having a reasonable accuracy. The main advantages in this system are being simple and low cost when compared with any other method having the same accuracy.

References
  1. Okeson JP. Management of temporomandibular disorders and occlusion. 6th ed. St Louis: Mosby Elsevier; 2007.
  2. Stuart CE. Diagnosis and treatment of occlusal relations of the teeth. Texas Dent J 1957; 75: 430-5.
  3. Walker WE. Movements of the mandibular condyles and dental articulation. Dent Cosmos 1896; 38: 573-83.
  4. Naeije M. Measurement of condylar motion: a plea for the use of the condylar kinematic centre. J Oral Rehabil. 2003;30:225-30.
  5. Wood WW. Medial pterygoid muscle activity during chewing and clenching. J Prosthet Dent. 1986;55:615-21.
  6. Mannini A, Sabatini A. Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers. Sensors 2010; 10: 1154-1175.
  7. Minami I, Oogai K, Nemoto T. Measurement of jerk-cost using a triaxial piezoelectric accelerometer for the evaluation of jaw movement smoothness. J of Oral Rehabilitation 2010; 37: 590–595.
  8. Holden JP, Selbie WS, Stanhope SJ. A proposed test to support the clinical movement analysis laboratory accreditation process. Gait Posture. 2003;17:205-13.
  9. Chen C, Lin C. A method for measuring three-dimensional mandibular kinematics in vivo using single-plane fluoroscopy. British Ins of Rad 2013; 42: 1259-1264.
  10. Yang Y, Yatabe M, Soneda K. The relation of canine guidance with laterotrusive movements at the incisal point and the working side condyle. J Oral Rehabil. 2000;27:911-7.
  11. Zharkova N, Hewlett N, Hardcastle W. Coarticulation as an Indicator of Speech Motor Control Development in Children: An Ultrasound Study. Human Kinetics, Inc. 2011; 15: 118-140.
  12. Hueber T, Benaroya E, Chollet G. Visuo-Phonetic Decoding using Multi-Stream and Context-Dependent Models for an Ultrasound-based Silent Speech Interface. Interspeech, Brighton 2009; 45: 640-643.
  13. Travers KH, Buschang PH, Hayasaki H, Throckmorton GS. Associations between incisor and mandibular condylar movements during maximum mouth opening in humans. Arch Oral Biol. 2000;45: 267-75.
  14. J. Clarke, S. Carlsson, and A. Zisserman. Detecting and tracking linear features efficiently. In Proc. British Machine Vision Conf. , 1996.
  15. M. A. Fischler and R. C. Bolles. Random sample concerns us: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. ACM, 24(6):381 395, 1981.
  16. Schiffman E, Anderson G, Fricton J. Diagnostic criteria for intraarticular T. M. disorders . Community Dent Oral Epidemiol 1989 ; 17: 252 – 257.
Index Terms

Computer Science
Information Sciences

Keywords

Motion analysis image processing mandibular motion computer vision