Video-based Tracking and Quantified Assessment of Spontaneous Limb Movements in Neonates
Paper in proceedings, 2015

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.

computer-aided diagnosis

Limb movement analysis

enhanced marker detection method

neurological diseases in infants.

multiple trajectories


Long Xu

Irene Yu-Hua Gu

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Anders Flisberg

Magnus Thordstein

17th IEEE Int'l conf. on E-Health, Networking, Application & Services (HealthCom'15), 2015


Areas of Advance

Information and Communication Technology

Life Science Engineering (2010-2018)

Subject Categories

Medical Engineering

Signal Processing


Computer Vision and Robotics (Autonomous Systems)



More information