Literature DB >> 22503388

Kinematic assessment of stereotypy in spontaneous movements in infants.

Dominik Karch1, Keun-Sun Kang, Katarzyna Wochner, Heike Philippi, Mijna Hadders-Algra, Joachim Pietz, Hartmut Dickhaus.   

Abstract

Movement variation constitutes a crucial feature of infant motor development. Reduced variation of spontaneous infant movements, i.e. stereotyped movements, may indicate severe neurological deficit at an early stage. Hitherto evaluation of movement variation has been mainly restricted to subjective assessment based on observation. This article introduces a method for quantitative assessment yielding an objective definition of stereotyped movements which may be used for the prognosis of neurological deficits such as cerebral palsy (CP). Movements of 3-month-old infants were recorded with an electromagnetic tracking system facilitating the analysis of joint angles of the upper and lower limb. A stereotypy score based on dynamic time warping has been developed describing movements which are self-similar in multiple degrees of freedom. For clinical evaluation, this measure was calculated in a group of infants at risk for neurological disorders (n=54) and a control group of typically developing children (n=21) on the basis of spontaneous movements at the age of 3 months. The stereotypy score was related to outcome at the age of 24 months in terms of CP (n=10) or no-CP (n=53). Using the stereotypy score of upper limb movements CP cases could be identified with a sensitivity of 90% and a specificity of 96%. The corresponding score of the leg movements did not allow for valid discrimination of the groups. The presented stereotypy feature is a promising candidate for a marker that may be used as a simple and noninvasive quantitative measure in the prediction of CP. The method can be adopted for the assessment of infant movement variation in research and clinical applications.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22503388     DOI: 10.1016/j.gaitpost.2012.03.017

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  11 in total

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Review 3.  [Developmental neurology - networked medicine and new perspectives].

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Review 5.  Movement recognition technology as a method of assessing spontaneous general movements in high risk infants.

Authors:  Claire Marcroft; Aftab Khan; Nicholas D Embleton; Michael Trenell; Thomas Plötz
Journal:  Front Neurol       Date:  2015-01-09       Impact factor: 4.003

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Review 7.  A Review of Wearable Sensor Systems for Monitoring Body Movements of Neonates.

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Review 8.  Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

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Journal:  Front Neurol       Date:  2017-12-21       Impact factor: 4.003

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Review 10.  AI Approaches Towards Prechtl's Assessment of General Movements: A Systematic Literature Review.

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Journal:  Sensors (Basel)       Date:  2020-09-17       Impact factor: 3.576

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