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A case-based multi-modal clinical system for stress management
Mälardalen University, School of Innovation, Design and Engineering. (Intelligent Systems)ORCID iD: 0000-0003-3802-4721
2010 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often make their diagnosis and decision based on manual inspection of physiological signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. Today the diagnosis and decision is largely dependent on how experienced the clinician is interpreting the measurements.  A computer-aided decision support system for diagnosis and treatment of stress would enable a more objective and consistent diagnosis and decisions.

A challenge in the field of medicine is the accuracy of the system, it is essential that the clinician is able to judge the accuracy of the suggested solutions. Case-based reasoning systems for medical applications are increasingly multi-purpose and multi-modal, using a variety of different methods and techniques to meet the challenges of the medical domain. This research work covers the development of an intelligent clinical decision support system for diagnosis, classification and treatment in stress management. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques have been investigated to enable a more reliable and efficient diagnosis and treatment of stress such as case-based reasoning, textual information retrieval, rule-based reasoning, and fuzzy logic. Functionalities and the performance of the system have been validated by implementing a research prototype based on close collaboration with an expert in stress. The case base of the implemented system has been initiated with 53 reference cases classified by an experienced clinician. A case study also shows that the system provides results close to a human expert. The experimental results suggest that such a system is valuable both for less experienced clinicians and for experts where the system may function as a second option.

Place, publisher, year, edition, pages
Västerås: Mälardalen University , 2010. , 200 p.
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 118
Keyword [en]
stress management, diagnosis and treatment, multi-purpose and multi-modal, Case-based reasoning, textual information retrieval, rule-based reasoning, and fuzzy logic
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:mdh:diva-8910ISBN: 978-91-86135-57-7 (print)OAI: oai:DiVA.org:mdh-8910DiVA: diva2:301329
Presentation
2010-04-29, Pi, Högskoleplan 1, Västerås, 13:00 (English)
Opponent
Supervisors
Projects
IPOS, PROEK
Available from: 2010-03-04 Created: 2010-03-03 Last updated: 2017-01-25Bibliographically approved

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Ahmed, Mobyen Uddin
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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
  • rtf