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Call for Papers
Focus Theme: “Machine Learning and Data Analytics in Pervasive Health”
Guest editors: Nuria Oliver, Oscar Mayora, Michael Marschollek
Deadline: July 28, 2017
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Archive (2016–2006)

Decision Support for Teletraining of COPD Patients

Journal: Methods of Information in Medicine
Subtitle: A journal stressing, for more than 50 years, the methodology and scientific fundamentals of organizing, representing and analyzing data, information and knowledge in biomedicine and health care
ISSN: 0026-1270
Topic:

Special Topic: Pervasive Healthcare
Guest Editors: B. Arnrich, O. Mayora, J. Bardram

DOI: https://doi.org/10.3414/ME09-02-0005
Issue: 2010 (Vol. 49): Issue 1 2010
Pages: 96-102

Decision Support for Teletraining of COPD Patients

B. Song (1), K.-H. Wolf (1), M. Gietzelt (1), O. Al Scharaa (1), U. Tegtbur (2), R. Haux (1), M. Marschollek (3)

(1) Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig – Institute of Technology and Hannover Medical School, Braunschweig, Germany; (2) Institute for Sports Medicine, Hannover Medical School, Hannover, Germany; (3) Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig – Institute of Technology and Hannover Medical School, Hannover, Germany

Keywords

Decision Support, COPD, JBoss Drools, Arden Syntax, training control

Summary

Background: Supervised physical training has been shown to promote rehabilitation of patients affected by chronic obstructive pulmonary disease (COPD). Currently, due to limited resources, not all COPD patients can be trained by an expert supervisor. Objectives: The objective of our research is to construct a decision support system (DSS) which observes and controls physical ergometer training sessions of COPD patients. Methods: A systematic literature review and expert interviews were carried out to build up the knowledge base for the DSS. Results: Nine production rules were established and standardized by Drools and Arden Syntax. The developed software autonomously controls training sessions on a bicycle ergometer on the basis of vital signs data. Thus it offers a new way for the rehabilitation of COPD patients. Conclusion: Evaluation with nine healthy subjects in a laboratory environment has confirmed its correct function, but the effects of its use for COPD patients’ rehabilitation and their quality of life have to be investigated in a further study.

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