This Small Business Innovation Research Phase I project explores an innovative approach to the analysis of complex biomedical signals, particularly those that exhibit chaotic dynamics. Recent research has suggested that such chaotic dynamics may be a useful physiological marker that may provide a new approach to the diagnosis and/or therapy of certain disease states. The present research will build on the success of a novel technique of nonlinear dynamics analysis (patent pending) that has demonstrated effectiveness in distinguishing chaos from random noise. The research will extend the capability and enhance the performance of this computational technique by mapping it to a neural network. The end product through Phase III of the project will be a commercial software package that enables the reliable detection and reconstruction of chaotic dynamics from biomedical signals for research and/or clinical use. The SBIR research will lead to a commercial software product that enables the detection and extraction of chaotic dynamics from complex biomedical signals.
