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Sökning: onr:"swepub:oai:research.chalmers.se:187de495-06d1-4d0b-b340-4a55a2c7c7c6" > 3D Limb Movement Tr...

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

Gu, Irene Yu-Hua, 1953 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Sowulewski, Grzegorz, 1990 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Yun, Yixiao, 1987 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
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Flisberg, Anders, 1958 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för pediatrik,Institute of Clinical Sciences, Department of Pediatrics
Thordstein, Magnus (författare)
Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap och rehabilitering,Institute of Neuroscience and Physiology, Department of Clinical Neuroscience and Rehabilitation
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 (creator_code:org_t)
ISBN 9781457702204
2016
2016
Engelska.
Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702204 ; 2016-October, s. 2395-2398
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
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  • 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.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Neurologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Neurology (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Nyckelord

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

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