Automatic Detection of Facial Tics in Gilles de la Tourette Syndrome Patients

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dc.contributor.advisorVuurpijl, L.G.
dc.contributor.advisorDesain, P.W.M.
dc.contributor.advisorGriendt, J. van de
dc.contributor.authorRijn, F.W. van
dc.date.issued2014-01-30
dc.description.abstractThis project pursues automatic facial tic detection in video recordings of Gilles de la Tourette syn- drome patients. Current diagnostic methods using a severity measurement scales and tic counts require huge e ort from the therapist and the patient. By automating these diagnostic methods, this would alle- viate these e orts. A study by Chappell et al. shows that manually counting tics in videotape recordings is feasible[9]. Only few studies used arti cial intelligence to automate the process of tic detection. A study by M. Bernabei is the most prominent one and shows that automatic tic detection with triaxial accelerometers is possible[3]. In the current project, distinctive features used by experts have been explored for their use in a system using computer vision and machine learning techniques. An implementation for this system is made and the performance is benchmarked. This project explored whether this approach was feasible and yields recommendations for further improvements. Finally, results and guidelines for the design of a system that uses automated tic detection for psychotherapeutic feedback and exercises are given.en_US
dc.identifier.urihttp://theses.ubn.ru.nl/handle/123456789/145
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationBachelor Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeBacheloren_US
dc.titleAutomatic Detection of Facial Tics in Gilles de la Tourette Syndrome Patientsen_US
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