A new approach for automatic assessment of a neurological condition employing hand gesture classification

Issue title: Multimedia/Multimodal Human-Computer Interaction in Knowledge-based Environments

Guest editors: Maria Virvou and George A. Tsihrintzis

Article type: Research Article

Authors: Kaszuba, Katarzyna^{; *} | Kostek, Bozena

Affiliations: Multimedia Systems Department (MSD), Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology (GUT), Gdansk, Poland | University of Piraeus, Greece

Correspondence: [*] Corresponding author. Tel.: +48 58 347 11 14; E-mail: katkasz@sound.eti.pg.gda.pl

Abstract: The paper presents a new approach to hand gesture classification which may be useful in testing and monitoring patients with neurological conditions. Since applying gesture recognition based on static image processing may easily fail when it comes to work with patients with neurological disorders, it is crucial to convert static masks into dynamic 3-dimensional geometrical model. The system being developed is meant to be used by patients with Parkinson Disease (PD). Three tests based on UPDRS (Unified Parkinson's Disease Rating Scale) are envisioned to be performed by a patient with the use of the system, i.e.: finger tapping (test No. 23), hand movements (test No. 24) and rapid alternating hand movements (test No. 25). In this concept presentation the movement interpolation curves based on various parameters are to be used as an input to the fuzzy logic classifier. In conclusion the aim of this research is presented and the approach advantages and disadvantages are shown and discussed.

Keywords: Virtual touchpad, fuzzy logic, interpolation curves, hand gesture recognition, Parkinson Disease, UPDRS tests

DOI: 10.3233/IDT-2012-0133

Journal: Intelligent Decision Technologies, vol. 6, no. 2, pp. 171-176, 2012