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Individualized Stress Diagnosis Using Calibration and Case-Based Reasoning

Fulltext:


Authors:

Shahina Begum, Mobyen Uddin Ahmed, Peter Funk, Ning Xiong, Bo von Schéele

Research group:

Artificial Intelligence and Intelligent Systems

Publication Type:

Conference/Workshop Paper

Venue:

Proceedings of the 24th annual workshop of the Swedish Artificial Intelligence Society

Abstract

Diagnosing stress is difficult even for experts due to large individual variations. Clinician’s use today manual test procedures where they measure blood pressure, ECG, finger temperature and breathing speed during a number of exercises. An experienced clinician makes diagnosis on different readings shown in a computer screen. There are only very few experts who are able to diagnose and predict stress-related problems. In this paper we have proposed a combined approach based on a calibration phase and case-based reasoning to provide assistance in diagnosing stress, using data from the finger temperature sensor readings. The calibration phase helps to establish a number of individual parameters. The system uses a case-based reasoning approach and also feedback on how well the patient succeeded with the different test, used for giving similar cases reliability estimates.

Bibtex

@inproceedings{Begum1070,
author = {Shahina Begum and Mobyen Uddin Ahmed and Peter Funk and Ning Xiong and Bo von Sch{\'e}ele},
title = {Individualized Stress Diagnosis Using Calibration and Case-Based Reasoning},
editor = {L{\"o}fstr{\"o}m et al.},
pages = {59--69},
month = {May},
year = {2007},
booktitle = {Proceedings of the 24th annual workshop of the Swedish Artificial Intelligence Society},
url = {http://www.es.mdu.se/publications/1070-}
}