The general movement checklist: A guide to the assessment of general movements during preterm and term age

Aizawa, Carolina Yuri Panvequio; Einspieler, Christa; Genovesi, Fernanda Françoso; Ibidi, Silvia Maria; Hasue, Renata Hydeé

doi:10.1016/j.jped.2020.09.006

Cited by 31 publications

(27 citation statements)

References 25 publications

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“…The films last for a minimum of 2 and a maximum of 3 minutes. This timeframe was chosen, based on studies recommending at least 2 minutes (16,17), together with difficulties holding the smartphone steady and keep an infant satisfied for much longer than 3 minutes. When recording is finished, the app user can upload the film to a secure web-based platform supporting research data management at Linkoping University using REDCap (Research Electronic Data Capture).…”

Section: The Mhealth App -Neuromotion™mentioning

confidence: 99%

Usability and inter-rater reliability of the NeuroMotion app: A tool in General Movements Assessments

Svensson

Örtqvist

Bos

et al. 2021

European Journal of Paediatric Neurology

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Section: The Mhealth App -Neuromotion™mentioning

confidence: 99%

Usability and inter-rater reliability of the NeuroMotion app: A tool in General Movements Assessments

Svensson

Örtqvist

Bos

et al. 2021

European Journal of Paediatric Neurology

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“…In this paper we have proposed and evaluated several new interpretable motion features relating directly to the criteria associated with the GMA checklist [3] and optimality score [19]. Additionally, we have fused these features together to produce a more robust representation of infant body movement for classification.…”

Section: Discussionmentioning

confidence: 99%

“…Given that GM assessors typically look for specific movement patterns, we attempt to model these patterns through a set of orientation-based, displacement-based and frequency-based features. Specifically we aim to model the movements associated with the assessment criteria set out in the GMA checklist [3], and the passive movement assessment section of the Optimality Score neurological examination [19]. In this section we discuss details of the proposed new features, their relevance to the GMA, and the methods used for feature fusion.…”

Section: E Feature Extractionmentioning

confidence: 99%

A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants

McCay

Shum

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

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The early diagnosis of cerebral palsy is an area which has recently seen significant multi-disciplinary research. Diagnostic tools such as the General Movements Assessment (GMA), have produced some very promising results. However, the prospect of automating these processes may improve accessibility of the assessment and also enhance the understanding of movement development of infants. Previous works have established the viability of using posebased features extracted from RGB video sequences to undertake classification of infant body movements based upon the GMA. In this paper, we propose a series of new and improved features, and a feature fusion pipeline for this classification task. We also introduce the RVI-38 dataset, a series of videos captured as part of routine clinical care. By utilising this challenging dataset we establish the robustness of several motion features for classification, subsequently informing the design of our proposed feature fusion framework based upon the GMA. We evaluate our proposed framework's classification performance using both the RVI-38 dataset and the publicly available MINI-RGBD dataset. We also implement several other methods from the literature for direct comparison using these two independent datasets. Our experimental results and feature analysis show that our proposed pose-based method performs well across both datasets. The proposed features afford us the opportunity to include finer detail than previous methods, and further model GMA specific body movements. These new features also allow us to take advantage of additional body-part specific information as a means of improving the overall classification performance, whilst retaining GMA relevant, interpretable, and shareable features.

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“…A GMA é um instrumento de avaliação rápido e não invasivo baseado na observação e avaliação qualitativa das movimentações espontâneas dos RNs, por meio desse instrumento que avalia a integridade do Sistema Nervoso Central (SNC) é possível identificar bebês com risco de déficits neuromotores (Einspieler, et al, 2016a;Einspieler, et al, 2021). De acordo com Olsen et al (2018) a GMA quando comparada com outras escalas pode ser utilizada precocemente na avaliação de prematuros, por ser um instrumento observacional, pois não necessita de manuseio e consequentemente não precisa esperar o RNPT estabilizar para tolerar os manejos.…”

Section: Variáveisunclassified

“…De acordo com Olsen et al (2018) a GMA quando comparada com outras escalas pode ser utilizada precocemente na avaliação de prematuros, por ser um instrumento observacional, pois não necessita de manuseio e consequentemente não precisa esperar o RNPT estabilizar para tolerar os manejos. Sendo assim, a GMA torna-se bastante efetiva no que tange ao delineamento das intervenções precoces objetivando o desenvolvimento e crescimento adequado do RNPT (Einspieler, et al, 2021).…”

Section: Variáveisunclassified

Avaliação dos movimentos em recém-nascidos prematuros internados em uma unidade de cuidados intermediários neonatal

Rodrigues

Barros

Dutra

2021

RSD

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Objetivo: Avaliar os movimentos em recém-nascidos prematuros internados em uma unidade de cuidados intermediários neonatal, segundo a General Movements Assessment (GMA). Métodos: Trata-se de um estudo descritivo, exploratório de abordagem quantitativa e delineamento transversal, realizado em um Hospital Materno-Infantil no interior da Bahia, no período de julho a setembro de 2021, composto por uma amostra de 20 recém-nascidos pré-termos. Os instrumentos utilizados para coleta de dados da pesquisa foram: formulário do prontuário dos recém-nascidos pré-termos e a escala de GMA. Resultados: A população do estudo apresentou idade gestacional corrigida entre 33 e 39 semanas correspondendo a fase dos Writhing Movements, foi possível identificar que 65% apresentaram movimentação anormal, sendo 55% preditivo para paralisia cerebral espástica. Conclusão: O Profissional fisioterapeuta além de realizar intervenção neurosensoriomotora em recém-nascidos de alto risco para o desenvolvimento infantil, realiza avaliação a fim de detectar sinais clínicos para atrasos de desenvolvimento motor. Toda intervenção tem a finalidade de adequar o tônus muscular, diminuir a dor, estimular as sinergias musculares e facilitar o desenvolvimento neurosensóriomotor, percebeu-se no estudo que o instrumento de avaliação GMA, é um facilitador confiável, desde idades gestacionais bem precoces.

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The general movement checklist: A guide to the assessment of general movements during preterm and term age

Cited by 31 publications

References 25 publications

Usability and inter-rater reliability of the NeuroMotion app: A tool in General Movements Assessments

Usability and inter-rater reliability of the NeuroMotion app: A tool in General Movements Assessments

A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants

Avaliação dos movimentos em recém-nascidos prematuros internados em uma unidade de cuidados intermediários neonatal

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