XML based personalized exercise prescription system using hybrid reasoning technique

Abstract

To achieve a state of optimal health, sufficient exercise is imperative in everyday routine. However, it is merely impossible to determine how much exercise is sufficient for an individual without knowing his health and fitness status. This paper presents the detailed design of a personalized exercise prescription system. The system analyzes subject's health and fitness features and provides an optimal set of exercise prescriptions. To evaluate subject's health status and for risk stratification, any assessment device can easily communicate with the system as it uses flexible XML based protocols. The system uses hybrid reasoning technique to employ both the experts' knowledge and experience into the system. To validate the system, a comparison between system's prescription outcome and a control dataset is presented along with a case study.