Vision-based motion detection, analysis and recognition of epileptic seizures-A systematic review

Authors:
Matthew Pediaditis;Manolis Tsiknakis;Norbert Leitgeb
Affiliations:
Foundation for Research and Technology - Hellas, Biomedical Informatics Laboratory, 100 Nikolaou Plastira str., Vassilika Vouton, Heraklion, Crete GR 700 13, Greece;Foundation for Research and Technology - Hellas, Biomedical Informatics Laboratory, 100 Nikolaou Plastira str., Vassilika Vouton, Heraklion, Crete GR 700 13, Greece;Graz University of Technology, Institute of Health Care Engineering, Kopernikusgasse 24, 8010, Graz, Austria
Venue:
Computer Methods and Programs in Biomedicine
Year:
2012

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Abstract

The analysis of human motion from video has been the object of interest for many application areas, these including surveillance, control, biomedical analysis, video annotation etc. This paper addresses the advances within this topic in relation to epilepsy, a domain where human motion is with no doubt one of the most important elements of a patient's clinical image. It describes recent achievements in vision-based detection, analysis and recognition of human motion in epilepsy for marker-based and marker-free systems. An overview of motion-characterizing features extracted so far is presented separately. The objective is to gain existing knowledge in this field and set the route marks for the future development of an integrated decision support system for epilepsy diagnosis and disease management based on automated video analysis. This review revealed that the quantification of motion patterns of selected epileptic seizures has been studied thoroughly while the recognition of seizures is currently in its beginnings, but however feasible. Moreover, only a limited set of seizure types have been analyzed so far, indicating that a holistic approach addressing all epileptic syndromes is still missing.