Multi-expert evolving system for objective psychophysiological monitoring and fast discovery of effective personalized therapies

Diagnostics and monitoring in applied and clinical psychology is often based on subjective patient's questionnaires and observations. Lack of objective quantitative approaches could lead to biased conclusions and selection of sub-optimal therapies. However, established methods of modern psychophysiology indicate possibility of objective physiological measurement of certain psychological states and their dynamics. Nevertheless treatment personalization and optimization is very difficult task even in medicine, where many objective diagnostic tools are available. Previously we have proposed generic quantitative framework capable of discovering optimal combination of physiological indicators for early detection of emerging pathologies and efficient multi-expert characterization of complex and rare states. Ability of implicit encoding of great variety of patterns and regimes in training phase makes our system evolving in nature and capable of robust novelty detection without any formal online learning algorithms. Here we argue that the same approach could be also applicable to objective psychophysiological monitoring and fast discovery of effective personalized therapies in applied and clinical psychology. The web-based version of our system will be made available for researchers and psychology practitioners.