The analysis of hu
man
motion fro
m video has been the object of interest for
many application areas, these including surveillance, control, bio
medical analysis, video annotation etc. This paper addresses the advances within this topic in relation to epilepsy, a do
main where hu
man
motion is with no doubt one of the
most i
mportant ele
ments of a patient's clinical i
mage. It describes recent achieve
ments in vision-based detection, analysis and recognition of hu
man
motion in epilepsy for
marker-based and
marker-free syste
ms. 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 develop
ment of an integrated decision support syste
m for epilepsy diagnosis and disease
manage
ment based on auto
mated 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.