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A Case-Based Reasoning System for the Diagnosis of Individual Sensitivity to Stress in Psychophysiology
Mälardalens högskola, Akademin för innovation, design och teknik. (Artificial Intelligence )ORCID-id: 0000-0002-1212-7637
2009 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Increased stress is a continuing problem in our present world. Especiallynegative stress could cause serious health problems if it remainsundiagnosed/misdiagnosed and untreated. In the stress medicine, clinicians’measure blood pressure, ECG, finger temperature and breathing rate during anumber of exercises to diagnose stress-related disorders. One of the physiologicalparameters for quantifying stress levels is the finger temperature that helps theclinicians in diagnosis and treatment of stress. However, in practice, it is difficultand tedious for a clinician to understand, interpret and analyze complex, lengthysequential sensor signals. There are only few experts who are able to diagnose andpredict stress-related problems. A system that can help the clinician in diagnosingstress is important, but the large individual variations make it difficult to build sucha system.This research work has attempted to investigate several artificial Intelligencetechniques to develop an intelligent, integrated sensor system for diagnosis andtreatment plan in the Psychophysiological domain. To diagnose individualsensitivity to stress, case-based reasoning is applied as a core technique to facilitateexperience reuse by retrieving previous similar cases. Further, fuzzy techniques arealso employed and incorporated into the case-based reasoning system to handlevagueness, uncertainty inherently existing in clinicians reasoning process. Thevalidation of the approach is based on close collaboration with experts andmeasurements from twenty four persons used as reference.Thirty nine time series from these 24 persons have been used to evaluate theapproach (in terms of the matching algorithms) and an expert has ranked andestimated similarity which shows a level of performance close to an expert. Theproposed system could be used as an expert for a less experienced clinician or as asecond option for an experienced clinician to their decision making process.

Ort, förlag, år, upplaga, sidor
Västerås: Mälardalens högskola , 2009. , s. 172
Serie
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 102
Nyckelord [en]
Artificial Intelligence, Case-based reasoning, Sensor, Signals, Stress, Diagnosis, Computer-based system
Nationell ämneskategori
Teknik och teknologier
Forskningsämne
Datavetenskap
Identifikatorer
URN: urn:nbn:se:mdh:diva-5809ISBN: 978-91-86135-25-6 (tryckt)OAI: oai:DiVA.org:mdh-5809DiVA, id: diva2:214266
Presentation
2009-05-25, S2-172, Mälardalen University, Västerås, 13:30 (Engelska)
Opponent
Handledare
Projekt
Integrated Personal Health Optimizing System (IPOS)Tillgänglig från: 2009-05-05 Skapad: 2009-05-04 Senast uppdaterad: 2013-12-03Bibliografiskt granskad

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