Integrating Smartphone Sensor Technology to Enhance Fine Motor and Working Memory Skills in Pediatric Obesity: A Gamified Approach


Sudipta Saha
Saikat Basu
Koushik Majumder
Sourav Das


Childhood obesity remains a pervasive global challenge, often accompanied by deficits in working memory and fine motor skills among affected children. These deficits detrimentally impact academic performance. Despite limited evidence, home-based interventions targeting both fine motor skills and working memory remain underexplored. Leveraging game-based approaches holds promise in behavior modification, self-management of chronic conditions, therapy adherence, and patient monitoring. In this study, a novel smartphone-based game was meticulously developed to target the enhancement of working memory and fine motor skills in a cohort of thirty-two obese or overweight children. Over two weeks, participants engaged in regular gameplay sessions within the comfort of their homes. Pretest and post-test assessments yielded compelling evidence of significant improvements, with statistical significance established at a robust 95% confidence level. Notably, participants exhibited a progressive trend of improvement in their gameplay performance. Recognizing the profound impact of academic achievement on future socioeconomic trajectories, regardless of weight management outcomes, the importance of bolstering cognitive skills cannot be overstated. This innovative intervention offers a pragmatic and cost-effective solution to empower children to cultivate essential cognitive abilities within their home environment. By fostering the development of working memory and fine motor skills, this intervention holds promise in facilitating improved academic performance and, consequently, enhancing long-term prospects for these children.


How to Cite
Saha, S., Basu, S., Majumder, K., & Das, S. . (2024). Integrating Smartphone Sensor Technology to Enhance Fine Motor and Working Memory Skills in Pediatric Obesity: A Gamified Approach. International Journal of Next-Generation Computing, 15(1).


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