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Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
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Using motion capture technology to assess locomotor development in children.

Benoit Bossavit1,2, Inmaculada Arnedillo-Sánchez1

  • 1School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland.

Digital Health
|December 19, 2022
PubMed
Summary

MotorSense, an affordable motion capture system, accurately assesses children's motor development. This technology aids in identifying developmental delays and offers a cost-effective alternative to traditional assessments.

Keywords:
Child developmenthealth technology assessmentmotor skillsuser computer interfacevirtual systems

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Area of Science:

  • Pediatric Development
  • Biomedical Engineering
  • Movement Science

Background:

  • Motor and cognitive development are interconnected, with the prefrontal cortex and cerebellum playing key roles.
  • Monitoring motor development is crucial for early identification of developmental delays in children.
  • Current assessment methods for motor development face challenges in accessibility and cost.

Purpose of the Study:

  • To introduce MotorSense, an affordable motion capture technology for assessing children's motor development.
  • To evaluate the accuracy and reliability of MotorSense in analyzing age-related developmental motor tasks.
  • To explore the potential of MotorSense in addressing the shortage of accessible developmental assessment tools.

Main Methods:

  • MotorSense utilizes motion capture technology and pattern recognition heuristics to assess motor skills.
  • The system was evaluated with 16 children aged 4-6 years performing developmental motor tasks.
  • Data analysis focused on specific movements including jumps, steps, and hops.

Main Results:

  • MotorSense demonstrated high accuracy in recognizing various movements, with accuracy rates for specific jumps and jogging exceeding 80%.
  • The system showed a strong agreement with human assessments, with agreement levels for different tasks ranging from 91% to 99%.
  • Analysis included over 500 jumps, 2400 steps, and 800 hops, validating the system's performance across a substantial dataset.

Conclusions:

  • MotorSense provides an affordable technological solution for assessing motor development through age-related tasks.
  • The technology can help overcome limitations in access and cost associated with traditional developmental assessments.
  • MotorSense holds potential for the tele-detection of motor developmental delays, improving early intervention accessibility.