[Analysis of motor development within the first year of life: 3-D motion tracking without markers for early detection of developmental disorders]. / Analyse der Spontanmotorik im 1. Lebensjahr: Markerlose 3-D-Bewegungserfassung zur Früherkennung von Entwicklungsstörungen.
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
; 63(7): 881-890, 2020 Jul.
Article
em De
| MEDLINE
| ID: mdl-32572501
Children with motor development disorders benefit greatly from early interventions. An early diagnosis in pediatric preventive care (U2-U5) can be improved by automated screening. Current approaches to automated motion analysis, however, are expensive, require lots of technical support, and cannot be used in broad clinical application. Here we present an inexpensive, marker-free video analysis tool (KineMAT) for infants, which digitizes 3D movements of the entire body over time allowing automated analysis in the future.Three-minute video sequences of spontaneously moving infants were recorded with a commercially available depth-imaging camera and aligned with a virtual infant body model (SMIL model). The virtual image generated allows any measurements to be carried out in 3D with high precision. We demonstrate seven infants with different diagnoses. A selection of possible movement parameters was quantified and aligned with diagnosis-specific movement characteristics.KineMAT and the SMIL model allow reliable, three-dimensional measurements of spontaneous activity in infants with a very low error rate. Based on machine-learning algorithms, KineMAT can be trained to automatically recognize pathological spontaneous motor skills. It is inexpensive and easy to use and can be developed into a screening tool for preventive care for children.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Deficiências do Desenvolvimento
/
Movimento
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Screening_studies
Limite:
Child
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Humans
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Infant
País/Região como assunto:
Europa
Idioma:
De
Ano de publicação:
2020
Tipo de documento:
Article