This article explores the impact of children's exposure to mobile devices and presents a new method for detecting age groups based on their interactions. The study analyzes time series data from children coloring a tree using different selection techniques and classification algorithms, achieving high accuracy results. The findings suggest the importance of providing an age-appropriate environment for children using technology.
The research highlights the benefits and challenges associated with children's use of mobile devices, emphasizing the need for responsible exposure. Various studies are referenced to support the argument that digital device usage can have both positive and negative effects on child development. The proposed approach offers insights into improving educational applications for children through innovative technology solutions.
Key metrics such as accuracy results over 85% are achieved, outperforming previous approaches in the literature. The study focuses on analyzing time series data related to spatial, pressure, and kinematic information during interactions with mobile devices. Different classification algorithms like Dynamic Time Warping Barycenter Averaging (DBA) and Hidden Markov Models (HMM) are explored to enhance age group detection accuracy.
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by Juan Carlos ... о arxiv.org 03-08-2024
https://arxiv.org/pdf/2403.04574.pdfГлибші Запити