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Health rating scale development

Developing a health scale for active video games across multiple gaming platforms.

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The aim of this research is to obtain objective population level prevalence estimates of 7 to 11 year old children’s movement proficiency using the Microsoft Kinect Sensor. The Kinect Sensor is an off-the-shelf consumer product that holds the potential to radically alter the assessment and monitoring of children’s movement in a rapid and valid way.  To achieve our goal we propose to introduce a machine learning approach to train a computer with data captured by the Kinect Sensor to objectively assess four fundamental movement skills (FMS); overarm throw, kick, vertical jump and catching that represent core locomotion and object control proficiency.  

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