ABSTRACT
Modern medical technology results in a large volume of data per patient, making the manual processing of the data by the physician a challenging and time-consuming task. This chapter outlines a general framework for predicting the state of an individual based on the stochastic fuzzy analysis of biomedical signals. It presents the necessary mathematical background from M. Kumar et al. required for designing an intelligent signal analysis algorithm. Biomedical signals typically possess a certain degree of randomness that cannot be explained in correlation to the physiological conditions. A case study by Kumar et al. is considered to demonstrate the application of the framework of intelligent signal analysis for medical decision support systems. The mathematical analysis of biomedical signals is meant for extracting the signal features relevant for functional state assessment. The stochastic fuzzy modeling and analysis techniques have much to offer in this area.
