title: Markerless video analysis for movement quantification in pediatric epilepsy monitoring.
abstract: This paper proposes a markerless video analytic system for quantifying body part movements in pediatric epilepsy monitoring. The system utilizes colored pajamas worn by a patient in bed to extract body part movement trajectories, from which various features can be obtained for seizure detection and analysis. Hence, it is non-intrusive and it requires no sensor/marker to be attached to the patient's body. It takes raw video sequences as input and a simple user-initialization indicates the body parts to be examined. In background/foreground modeling, Gaussian mixture models are employed in conjunction with HSV-based modeling. Body part detection follows a coarse-to-fine paradigm with graph-cut-based segmentation. Finally, body part parameters are estimated with domain knowledge guidance. Experimental studies are reported on sequences captured in an Epilepsy Monitoring Unit at a local hospital. The results demonstrate the feasibility of the proposed system in pediatric epilepsy monitoring and seizure detection.
authors.affiliation: Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore. fhlu@i2r.a-star.edu.sg
authors.forename: Haiping
authors.initials: H
authors.lastname: Lu
authors.forename: How-Lung
authors.initials: HL
authors.lastname: Eng
authors.forename: Bappaditya
authors.initials: B
authors.lastname: Mandal
authors.forename: Derrick W S
authors.initials: DW
authors.lastname: Chan
authors.forename: Yen-Ling
authors.initials: YL
authors.lastname: Ng
mesh_terms: D000465:Algorithms; D002648:Child; D003116:Color; D004827:Epilepsy / Q000175:diagnosis*; D006801:Humans; D008991:Monitoring, Physiologic / Q000379:methods*; D009068:Movement / Q000502:physiology*; D014743:Videotape Recording / Q000379:methods*