Literature DB >> 28745715

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

Ragnhild Støen1, Nils Thomas Songstad2, Inger Elisabeth Silberg3, Toril Fjørtoft1, Alexander Refsum Jensenius4, Lars Adde1.   

Abstract

BackgroundAbsence of fidgety movements (FMs) at 3 months' corrected age is a strong predictor of cerebral palsy (CP) in high-risk infants. This study evaluates the association between computer-based video analysis and the temporal organization of FMs assessed with the General Movement Assessment (GMA).MethodsInfants were eligible for this prospective cohort study if referred to a high-risk follow-up program in a participating hospital. Video recordings taken at 10-15 weeks post term age were used for GMA and computer-based analysis. The variation of the spatial center of motion, derived from differences between subsequent video frames, was used for quantitative analysis.ResultsOf 241 recordings from 150 infants, 48 (24.1%) were classified with absence of FMs or sporadic FMs using the GMA. The variation of the spatial center of motion (CSD) during a recording was significantly lower in infants with normal (0.320; 95% confidence interval (CI) 0.309, 0.330) vs. absence of or sporadic (0.380; 95% CI 0.361, 0.398) FMs (P<0.001). A triage model with CSD thresholds chosen for sensitivity of 90% and specificity of 80% gave a 40% referral rate for GMA.ConclusionQuantitative video analysis during the FMs' period can be used to triage infants at high risk of CP to early intervention or observational GMA.

Entities:  

Mesh:

Year:  2017        PMID: 28745715     DOI: 10.1038/pr.2017.121

Source DB:  PubMed          Journal:  Pediatr Res        ISSN: 0031-3998            Impact factor:   3.756


  27 in total

1.  Movement analysis by accelerometry of newborns and infants for the early detection of movement disorders due to infantile cerebral palsy.

Authors:  Franziska Heinze; Katharina Hesels; Nico Breitbach-Faller; Thomas Schmitz-Rode; Catherine Disselhorst-Klug
Journal:  Med Biol Eng Comput       Date:  2010-05-06       Impact factor: 2.602

Review 2.  Reorganization after pre- and perinatal brain lesions.

Authors:  Martin Staudt
Journal:  J Anat       Date:  2010-10       Impact factor: 2.610

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

Authors:  Heike Philippi; Dominik Karch; Keun-Sun Kang; Katarzyna Wochner; Joachim Pietz; Hartmut Dickhaus; Mijna Hadders-Algra
Journal:  Dev Med Child Neurol       Date:  2014-05-21       Impact factor: 5.449

4.  Jerky spontaneous movements at term age in preterm infants who later developed cerebral palsy.

Authors:  Nao Kanemaru; Hama Watanabe; Hideki Kihara; Hisako Nakano; Tomohiko Nakamura; Junji Nakano; Gentaro Taga; Yukuo Konishi
Journal:  Early Hum Dev       Date:  2014-06-05       Impact factor: 2.079

Review 5.  Early identification and intervention in cerebral palsy.

Authors:  Anna Herskind; Gorm Greisen; Jens Bo Nielsen
Journal:  Dev Med Child Neurol       Date:  2014-07-09       Impact factor: 5.449

6.  Sensitivity and specificity of General Movements Assessment for diagnostic accuracy of detecting cerebral palsy early in an Australian context.

Authors:  Catherine Morgan; Cathryn Crowle; Traci-Anne Goyen; Caroline Hardman; Michelle Jackman; Iona Novak; Nadia Badawi
Journal:  J Paediatr Child Health       Date:  2015-08-19       Impact factor: 1.954

Review 7.  Prevalence, type, distribution, and severity of cerebral palsy in relation to gestational age: a meta-analytic review.

Authors:  E Himpens; C Van den Broeck; A Oostra; P Calders; P Vanhaesebrouck
Journal:  Dev Med Child Neurol       Date:  2008-03-18       Impact factor: 5.449

8.  Using computer-based video analysis in the study of fidgety movements.

Authors:  Lars Adde; Jorunn L Helbostad; Alexander Refsum Jensenius; Gunnar Taraldsen; Ragnhild Støen
Journal:  Early Hum Dev       Date:  2009-05-22       Impact factor: 2.079

9.  Intraventricular hemorrhage and neurodevelopmental outcomes in extreme preterm infants.

Authors:  Srinivas Bolisetty; Anjali Dhawan; Mohamed Abdel-Latif; Barbara Bajuk; Jacqueline Stack; Kei Lui
Journal:  Pediatrics       Date:  2013-12-30       Impact factor: 7.124

10.  Are sporadic fidgety movements as clinically relevant as is their absence?

Authors:  Christa Einspieler; Hong Yang; Katrin D Bartl-Pokorny; Xia Chi; Fei-Fei Zang; Peter B Marschik; Andrea Guzzetta; Fabrizio Ferrari; Arend F Bos; Giovanni Cioni
Journal:  Early Hum Dev       Date:  2015-03-04       Impact factor: 2.079

View more
  7 in total

1.  Healthcare applications of single camera markerless motion capture: a scoping review.

Authors:  Bradley Scott; Martin Seyres; Fraser Philp; Edward K Chadwick; Dimitra Blana
Journal:  PeerJ       Date:  2022-05-26       Impact factor: 3.061

2.  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

3.  Temporal and spatial localisation of general movement complexity and variation-Why Gestalt assessment requires experience.

Authors:  Ying-Chin Wu; Ilse M van Rijssen; Maria T Buurman; Linze-Jaap Dijkstra; Elisa G Hamer; Mijna Hadders-Algra
Journal:  Acta Paediatr       Date:  2020-06-22       Impact factor: 2.299

4.  The Subject Construction and Role Mental Model Construction of Erotic Movies Based on Lacan's Desire Theory.

Authors:  Shuqin Feng
Journal:  Occup Ther Int       Date:  2022-06-13       Impact factor: 1.565

5.  Automated Movement Analysis to Predict Cerebral Palsy in Very Preterm Infants: An Ambispective Cohort Study.

Authors:  Kamini Raghuram; Silvia Orlandi; Paige Church; Maureen Luther; Alex Kiss; Vibhuti Shah
Journal:  Children (Basel)       Date:  2022-06-07

6.  Machine Learning of Infant Spontaneous Movements for the Early Prediction of Cerebral Palsy: A Multi-Site Cohort Study.

Authors:  Espen A F Ihlen; Ragnhild Støen; Lynn Boswell; Raye-Ann de Regnier; Toril Fjørtoft; Deborah Gaebler-Spira; Cathrine Labori; Marianne C Loennecken; Michael E Msall; Unn I Möinichen; Colleen Peyton; Michael D Schreiber; Inger E Silberg; Nils T Songstad; Randi T Vågen; Gunn K Øberg; Lars Adde
Journal:  J Clin Med       Date:  2019-12-18       Impact factor: 4.241

Review 7.  AI Approaches Towards Prechtl's Assessment of General Movements: A Systematic Literature Review.

Authors:  Muhammad Tausif Irshad; Muhammad Adeel Nisar; Philip Gouverneur; Marion Rapp; Marcin Grzegorzek
Journal:  Sensors (Basel)       Date:  2020-09-17       Impact factor: 3.576

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.