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Related Concept Videos

Anatomical Positions01:11

Anatomical Positions

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In anatomy, several standard anatomical positions are used as references for describing the position and orientation of different body parts. These positions help provide a common frame of reference when discussing anatomical structures. The anatomical position is the standard reference point for describing the body's position and orientation. In this position:
The body is upright, facing forward, and standing erect.
The feet are parallel and flat on the floor.
The arms are hanging by the...
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Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
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Postural Analysis in Ventral and Dorsal Decubitus Babies Using Deep Learning Techniques: A Protocol Study.

Sara Velázquez-Iglesias1, Vidal Moreno-Rodilla2, Belén Curto-Diego2

  • 1Department of Nursing and Physiotherapy, Universidad de Salamanca, 37007 Salamanca, Spain.

Journal of Clinical Medicine
|May 14, 2025
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Summary

Artificial intelligence (AI) offers objective infant postural assessment for early motor development analysis. This technology aids in identifying potential delays, improving timely interventions for babies aged 0-6 months.

Keywords:
artificial intelligencedeep learningmotor developmentneural networkspostural analysis

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Area of Science:

  • Pediatrics
  • Developmental Neuroscience
  • Biomedical Engineering

Background:

  • Postural analysis is crucial for understanding early motor development.
  • Technological advancements necessitate objective tools for assessing postural control.
  • Postural control is intrinsically linked to a baby's overall motor development.

Purpose of the Study:

  • To analyze infant posture in ventral and dorsal decubitus positions using artificial intelligence.
  • To establish objective parameters for postural assessment in babies aged 0-6 months.
  • To leverage deep learning for precise evaluation of infant postural development.

Main Methods:

  • Observational, cross-sectional study design.
  • Systematic kinesiological assessment of infants.
  • Image analysis of infants in ventral and dorsal decubitus using deep learning techniques on a glass platform.

Main Results:

  • Current methods lack objective assessment of the support area for typically developing babies.
  • Artificial intelligence (AI) shows promise for objective infant posture analysis and delay detection.
  • Deep learning techniques will define infant support areas based on age.

Conclusions:

  • Early detection of motor or postural delays is vital for effective treatment optimization.
  • AI can manage healthcare data complexity, providing insights into infant postural control.
  • AI facilitates clinical decision-making, reducing healthcare professional workload.