Detection of complex movement patterns in multivariate kinematic time series for diagnostics in pediatric neurology View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009

AUTHORS

Ratko Magjarevic , D. Karch , K. Wochner , K. Kim , H. Philippi , J. Pietz , H. Dickhaus

ABSTRACT

Evaluation of spontaneous infant movements is an important tool for the detection of neurological impairments. It is necessary to automatically detect movement phases which exhibit certain complex characteristics in order to quantitatively assess these movements. This article presents a method to extract segments of complex movements from multivariate kinematic tracking data. Expert knowledge is represented in a principal component model. Evaluation shows a good concordance between the segments marked by the experts and the results of the automated approach. It is further shown that normal infant movements can be discriminated from pathologic movement patterns. More... »

PAGES

771-774

Book

TITLE

World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany

ISBN

978-3-642-03881-5
978-3-642-03882-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-03882-2_205

DOI

http://dx.doi.org/10.1007/978-3-642-03882-2_205

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040203572


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