Modelling active play in preschool children using machine learning.

使用机器学习对学龄前儿童的主动游戏进行建模。

• 批准号: DP150100116
• 负责人: A/Prof Markus Hagenbuchner
• 金额: $ 19.78万
• 依托单位: University of Wollongong
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2015
• 资助国家: 澳大利亚
• 起止时间: 2015-06-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP150100116
• 关键词: Modelling; active; play; preschool; children

This interdisciplinary project explores novel machine learning approaches to modelling physical activity data in preschool children. The approach taken is considered the future of physical activity assessment and is expected to substantially enhance the measurement of physical activity and the evidence base that informs strategies to improve population health through physical activity promotion. The project aims to transform the understanding of young children's physical activity behaviour, and is expected to have important implications for the design of accurate and effective technology-based physical activity monitoring and intervention applications that could be delivered through the e-health initiative in Australia.

这个跨学科的项目探索了新的机器学习方法来模拟学龄前儿童的身体活动数据。所采取的办法被认为是体力活动评估的未来，预计将大大加强对体力活动的衡量，并为通过促进体力活动改善人口健康的战略提供依据。该项目旨在改变对幼儿身体活动行为的理解，预计将对设计准确有效的基于技术的身体活动监测和干预应用程序产生重要影响，这些应用程序可以通过澳大利亚的电子健康倡议提供。