Using motion capture technology to assess locomotor development in children.

Objective: Motor and cognitive development share biological background within the prefrontal cortex and cerebellum. Monitoring motor development is relevant to identify children at risk of developmental delays. However, access to timely assessment is prevented by its availability and cost. Affordable motion capture technology may provide an alternative to human assessment.
Methods: MotorSense uses this technology to guide and assess children executing age-related developmental motor tasks. It incorporates advanced heuristics informed by pattern recognition principles based on the developmental sequences of motor skills. MotorSense was evaluated with 16 4-6 year-old children from a rural primary school.
Results: A total of 506 jumps, 2415 steps and 831 hops were analysed. The analysis illustrates MotorSense Accuracy (MA), recognising jump forward (89.96%), jump high (83.34%), jump sideway (85.63%), hop (74.58%) and jog (92.34%), is as good as the sensor's precision. The analysis of the tasks' execution shows a high level of agreement between human and MotorSense's assessment on jump forward (91%), jump high (99%), jump sideway (93%), hop (94%) and jog (92%).
Conclusions: MotorSense helps address the shortage of affordable technologies to support the assessment of motor development using graded age-related developmental motor tasks. Furthermore, it could contribute towards the tele-detection of motor developmental delays.
Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
(© The Author(s) 2022.)