Abstract
This article describes a new, AI-inspired telemedicine system for providing feedback on daily activity. Optimising daily levels of physical activity is an important focus in the treatment of chronic illnesses. An ambulatory monitoring and feedback system has been developed to monitor activity and provide feedback to help patients reach a healthy daily pattern. The system has shown positive effects in trials on different patient groups including COPD and obese patients. We describe the design and implementation of an intelligent feedback generation module that improves interaction with the patient by providing personalised dynamic context-aware feedback. An ontology of messages was designed, which the system uses to find appropriate feedback using context information to prune irrelevant paths. The system adapts based on derived probabilities concerning user preferences to certain message types. We aim to improve patient compliance to individual feedback messages and improve the user experience, leading to better overall treatment compliance.
Original language | Undefined |
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Title of host publication | 13th International Conference on Artificial Intelligence in Medicine, AIME 2011 |
Place of Publication | London |
Publisher | Springer |
Pages | 55-59 |
Number of pages | 5 |
ISBN (Print) | 978-3-642-22217-7 |
DOIs | |
Publication status | Published - 3 Jul 2011 |
Event | 13th Conference on Artificial Intelligence in Medicine, AIME 2011 - Bled, Slovenia Duration: 2 Jul 2011 → 6 Jul 2011 Conference number: 13 |
Publication series
Name | Lecture Notes in Artificial Intelligence |
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Publisher | Springer Verlag |
Volume | 6747 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 13th Conference on Artificial Intelligence in Medicine, AIME 2011 |
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Abbreviated title | AIME |
Country/Territory | Slovenia |
City | Bled |
Period | 2/07/11 → 6/07/11 |
Keywords
- METIS-278770
- IR-77994
- EWI-20460
- Ontologies
- Feedback
- Activity Monitoring