Measuring biosignals of overweight and obese children for real-time feedback and predicting performance

Abstract

Child obesity is a serious problem in our modern world and shows an increase of 60% since 1990. Due to time and cost intensity of traditional therapy programs, scientists started to focus on IT-based interventions. Our paper focuses on measuring biosignals (e.g. heart rate) of obese children during fittest including different physical activities (e.g. running). We investigate whether it is possible to predict the performance of obese children during running tests based on static (e.g. BMI) as well as dynamic (e.g. heart rate) parameters. Here, we focused on heart rate-related parameters from the inverted U-shaped heart rate response of obese children during running tests. For future research, we plan to consider physical activity (e.g. step count) of the children at home. Our approach is a NeuroIS service, which uses low-cost devices making prediction on an individual’s future development and is also applicable to other domains (e.g. business information systems).