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3D Limb Movement Tracking and Analysis for Neurological Dysfunctions of Neonates Using Multi-Camera Videos

Irene Y.H. Gu (Institutionen för signaler och system, Signalbehandling) ; Grzegorz Sowulewski (Institutionen för signaler och system) ; Yixiao Yun (Institutionen för signaler och system, Signalbehandling) ; Anders Flisberg ; Magnus Thordstein
38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, United States, 16-20 August 2016 (1557-170X). p. 2395-2398. (2016)
[Konferensbidrag, refereegranskat]

Central nervous system dysfunction in infants may be manifested through inconsistent, rigid and abnormal limb movements. Detection of limb movement anomalies associated with such neurological dysfunctions in infants is the first step towards early treatment for improving infant development. This paper addresses the issue of detecting and quantifying limb movement anomalies in infants through non-invasive 3D image analysis methods using videos from multiple camera views. We propose a novel scheme for tracking 3D time trajectories of markers on infant’s limbs by video analysis techniques. The proposed scheme employ videos captured from three camera views. This enables us to detect a set of enhanced 3D markers through cross-view matching and to effectively handle marker self-occlusions by other body parts. We track a set of 3D trajectories of limb movements by a set of particle filters in parallel, enabling more robust 3D tracking of markers, and use the 3D model errors for quantifying abrupt limb movements. The proposed work makes a significant advancement to the previous work in [1] through employing tracking in 3D space, and hence overcome several main barriers that hinder real applications by using single camera-based techniques. To the best of our knowledge, applying such a multi-view video analysis approach for assessing neurological dysfunctions of infants through 3D time trajectories of markers on limbs is novel, and could lead to computer-aided tools for diagnosis of dysfunctions where early treatment may improve infant development. Experiments were conducted on multi-view neonate videos recorded in a clinical setting and results have provided further support to the proposed method.

Nyckelord: 3D trajectory tracking, multi-camera video, neurological dysfunction quantification, Neonates

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Denna post skapades 2016-08-10. Senast ändrad 2017-07-07.
CPL Pubid: 240110


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Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling (1900-2017)
Institutionen för signaler och system (1900-2017)
Institutionen för kliniska vetenskaper, sektionen för kvinnors och barns hälsa (GU)
Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap och rehabilitering (2006-2016)


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