ADAPTIVE DECISION SUPPORT SYSTEM FOR AUTOMATIC PHYSICAL EFFORT PLAN GENERATION—DATA-DRIVEN APPROACH

Abstract

Mathematical models delivered using both expert knowledge and experimental data improve understanding of dynamic properties of the system under consideration. This is useful for different purposes, such as prediction, diagnosis, decision making, and system control. A data-driven approach has been found to be particularly useful in designing adaptive decision support systems. We demonstrate the usefulness of data-driven models in a custom application designed for sport training management. We have developed a system that makes use of expert knowledge together with measurement data (heart rate, electromyography, and acceleration) as well as environmental (Global Positioning System) in order to generate an optimal training plan. The system performs such tasks as modeling of the athlete's cardiovascular system, estimation of the athlete's parameters, and adaptation of the model to the athlete.