Using machine learning for real-time activity recognition and estimation of energy expenditure

This work demonstrates how wireless accelerometers can be used for real-time automatic recognition of physical activity type, intensity, and duration and estimation of energy expenditure and may ultimately allow for the development of mobile phonebased just-in-time interventions to increase self-awareness ofPhysical activity patterns and increases in physical activity levels in real- time during free-living that scale to large populations.