Literature DB >> 24844774

Computer-based analysis of general movements reveals stereotypies predicting cerebral palsy.

Heike Philippi1, Dominik Karch, Keun-Sun Kang, Katarzyna Wochner, Joachim Pietz, Hartmut Dickhaus, Mijna Hadders-Algra.   

Abstract

AIM: To evaluate a kinematic paradigm of automatic general movements analysis in comparison to clinical assessment in 3-month-old infants and its prediction for neurodevelopmental outcome.
METHOD: Preterm infants at high risk (n=49; 26 males, 23 females) and term infants at low risk (n=18; eight males, 10 females) of developmental impairment were recruited from hospitals around Heidelberg, Germany. Kinematic analysis of general movements by magnet tracking and clinical video-based assessment of general movements were performed at 3 months of age. Neurodevelopmental outcome was evaluated at 2 years. By comparing the general movements of small samples of children with and without cerebral palsy (CP), we developed a kinematic paradigm typical for infants at risk of developing CP. We tested the validity of this paradigm as a tool to predict CP and neurodevelopmental impairment.
RESULTS: Clinical assessment correctly identified almost all infants with neurodevelopmental impairment including CP, but did not predict if the infant would be affected by CP or not. The kinematic analysis, in particular the stereotypy score of arm movements, was an excellent predictor of CP, whereas stereotyped repetitive movements of the legs predicted any neurodevelopmental impairment.
INTERPRETATION: The automatic assessment of the stereotypy score by magnet tracking in 3-month-old spontaneously moving infants at high risk of developmental abnormalities allowed a valid detection of infants affected and unaffected by CP.
© 2014 Mac Keith Press.

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Year:  2014        PMID: 24844774     DOI: 10.1111/dmcn.12477

Source DB:  PubMed          Journal:  Dev Med Child Neurol        ISSN: 0012-1622            Impact factor:   5.449


  15 in total

1.  Computer-based video analysis identifies infants with absence of fidgety movements.

Authors:  Ragnhild Støen; Nils Thomas Songstad; Inger Elisabeth Silberg; Toril Fjørtoft; Alexander Refsum Jensenius; Lars Adde
Journal:  Pediatr Res       Date:  2017-07-26       Impact factor: 3.756

Review 2.  Current behavioral assessments of movement disorders in children.

Authors:  Tetsuya Asakawa; Kenji Sugiyama; Takao Nozaki; Tetsuro Sameshima; Susumu Kobayashi; Liang Wang; Zhen Hong; Shu-Jiao Chen; Can-Dong Li; Ding Ding; Hiroki Namba
Journal:  CNS Neurosci Ther       Date:  2018-07-24       Impact factor: 5.243

3.  Posture and movement in very preterm infants at term age in and outside the nest.

Authors:  M Zahed; J Berbis; V Brevaut-Malaty; M Busuttil; B Tosello; C Gire
Journal:  Childs Nerv Syst       Date:  2015-10-05       Impact factor: 1.475

4.  Computer Vision to Automatically Assess Infant Neuromotor Risk.

Authors:  Claire Chambers; Nidhi Seethapathi; Rachit Saluja; Helen Loeb; Samuel R Pierce; Daniel K Bogen; Laura Prosser; Michelle J Johnson; Konrad P Kording
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2020-11-06       Impact factor: 3.802

5.  Early motor signs of autism spectrum disorder in spontaneous position and movement of the head.

Authors:  Hirotaka Gima; Hideki Kihara; Hama Watanabe; Hisako Nakano; Junji Nakano; Yukuo Konishi; Tomohiko Nakamura; Gentaro Taga
Journal:  Exp Brain Res       Date:  2018-02-15       Impact factor: 1.972

Review 6.  [Developmental neurology - networked medicine and new perspectives].

Authors:  U Tacke; H Weigand-Brunnhölzl; A Hilgendorff; R M Giese; A W Flemmer; H König; B Warken-Madelung; M Arens; N Hesse; A S Schroeder
Journal:  Nervenarzt       Date:  2017-12       Impact factor: 1.214

7.  Novel AI driven approach to classify infant motor functions.

Authors:  Simon Reich; Dajie Zhang; Tomas Kulvicius; Sven Bölte; Karin Nielsen-Saines; Florian B Pokorny; Robert Peharz; Luise Poustka; Florentin Wörgötter; Christa Einspieler; Peter B Marschik
Journal:  Sci Rep       Date:  2021-05-10       Impact factor: 4.379

Review 8.  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

9.  Developmental Trajectories of Hand Movements in Typical Infants and Those at Risk of Developmental Disorders: An Observational Study of Kinematics during the First Year of Life.

Authors:  Lisa Ouss; Marie-Thérèse Le Normand; Kevin Bailly; Marluce Leitgel Gille; Christelle Gosme; Roberta Simas; Julia Wenke; Xavier Jeudon; Stéphanie Thepot; Telma Da Silva; Xavier Clady; Edith Thoueille; Mohammad Afshar; Bernard Golse; Mariana Guergova-Kuras
Journal:  Front Psychol       Date:  2018-02-19

Review 10.  Precision Medicine in Neonates: A Tailored Approach to Neonatal Brain Injury.

Authors:  Maria Luisa Tataranno; Daniel C Vijlbrief; Jeroen Dudink; Manon J N L Benders
Journal:  Front Pediatr       Date:  2021-05-19       Impact factor: 3.418

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