AI techniques have valuable benefits to offer medical systems. Techniques such as abstraction, conceptualization (of sensor data), Semantic Nets, Case-Based Reasoning (CBR), Clustering, and User Modeling have been used to develop theories and a system that is able to classify complex medical measurements from a person that may need preventive actions and treatment for stress problems. The developed method and techniques are able to classify individual sensor data that can be used for a final classification of a person. Hearth rate variability, finger temperature, conductance, breathing and CO2 level are the measurements used in this clinical diagnosis process.
|Erik M. G.
Case Based Reasoning and Knowledge Discovery in Medical Applications with Time Series (Nov 2006) Peter Funk, Ning Xiong Computational Intelligence
Knowledge Discovery and Case Based Reasoning in Medical Applications with Time Series (Dec 2005) Peter Funk, Markus Nilsson, Ning Xiong In Workshop proceedings of the 6th International Conference on Case Based Reasoning
Clinical decision-support for diagnosing stress-related disorders by applying psychophysiological medical knowledge to an instance-based learning system (Nov 2005) Markus Nilsson, Peter Funk, Erik M. G. Olsson , Bo von Schéele, Ning Xiong Journal of Artificial Intelligence in Medicine
Detecting breaths in capnography time series (Aug 2005) Markus Nilsson, Mattias Karlsson , Andreas Selenwall , Peter Funk Workshop proceedings of the 6th International Conference on Case Based Reasoning
A Case Based Approach Using Behavioural Biometrics to Determine a Users Stress Level (Aug 2005) Johan Andrén , Peter Funk In Workshop proceedings of the 6th International Conference on Case Based Reasoning