2022
DOI: 10.3390/s22030866
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Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions

Abstract: Neurodevelopmental disorders (NDD) are impairments of the growth and development of the brain and/or central nervous system. In the light of clinical findings on early diagnosis of NDD and prompted by recent advances in hardware and software technologies, several researchers tried to introduce automatic systems to analyse the baby’s movement, even in cribs. Traditional technologies for automatic baby motion analysis leverage contact sensors. Alternatively, remotely acquired video data (e.g., RGB or depth) can … Show more

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Cited by 29 publications
(19 citation statements)
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“…Lastly, with new and advanced technologies [66][67][68], it is perhaps possible to assess infants' development more frequently. This will give us even more detailed information about infant motor development and perhaps an indication of periods when motor development is subject to change.…”
Section: Future Researchmentioning
confidence: 99%
“…Lastly, with new and advanced technologies [66][67][68], it is perhaps possible to assess infants' development more frequently. This will give us even more detailed information about infant motor development and perhaps an indication of periods when motor development is subject to change.…”
Section: Future Researchmentioning
confidence: 99%
“…All the above mentioned research have focused on a simple classification task, mostly as HB but have neither classified the correct head movement types nor have carried out a detailed repetitive head movement analysis. As pointed out by [14], the most of the research done so far do not carry out in-depth analysis ob repetitive head movements in order to automatically identify the neurodevelopmental disorders.…”
Section: Introductionmentioning
confidence: 99%
“…Researchers have begun developing systems to automatically analyze infant movement for early diagnosis of neurodevelopmental disorders 3,4,39 . However, automatic analysis of infant behaviour is complex since data are often captured in uncontrolled natural settings while the infant is freely moving and interacting with a variety of objects 40 . Handling information such as infants' physical variations, lighting changes, and examiner involvement results in a lack of robustness in classification for markerless capture of movement data (i.e., estimating 3D limb position and movement from video recordings).…”
Section: Introductionmentioning
confidence: 99%