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Video-based Tracking and Quantified Assessment of Spontaneous Limb Movements in Neonates

Long Xu ; Irene Y.H. Gu (Institutionen för signaler och system, Signalbehandling) ; Anders Flisberg ; Magnus Thordstein
17th IEEE Int'l conf. on E-Health, Networking, Application & Services (HealthCom'15), 2015 p. 517-522. (2015)
[Konferensbidrag, refereegranskat]

Central nervous system dysfunction in infants may be manifested through inconsistent, rigid and abnormal limb movements. Detection and quantification of these movements in infants from videos are hence desirable for providing useful information to clinicians. This could lead to computer-aided diagnosis of dysfunctions where early treatment may improve infant development. In this paper, we propose a scheme for detecting and quantifying qualitative aspects of limb movement through multiple tracking and state space motion modeling on videos. The main novelties of the paper include: (a) An enhanced detection method for effectively detection small weak marker points from video; (b) Bayesian estimation and nearest neighbor searching for selecting new observation in individual tracker and for tracking marker trajectories on limbs; (c) A criterion for anomaly detection based on the frequency and duration of abrupt changes in limb movement, using window averaged prominent residual powers. The proposed method has been tested on videos of neonates, results show that the proposed method is promising for tracking and quantifying the movement of neonate limbs for helping medical diagnostics.

Nyckelord: Limb movement analysis, enhanced marker detection method, multiple trajectories, computer-aided diagnosis, neurological diseases in infants.


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Denna post skapades 2015-10-30. Senast ändrad 2016-08-23.
CPL Pubid: 225098


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