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Health monitoring for elderly: an application using case-based reasoning and cluster analysis
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems)
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems)ORCID iD: 0000-0002-9607-9504
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems)ORCID iD: 0000-0002-3122-693X
2013 (English)In: ISRN Artificial Intelligence, ISSN 2090-7435, E-ISSN 2090-7443, Vol. 2013, no 2013, 1-11 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a framework to process and analyze data from a pulse oximeter which measures pulse rate and blood oxygen saturation from a set of individuals remotely. Using case-based reasoning (CBR) as the backbone to the framework, records are analyzed and categorized according to how well they are similar. Record collection has been performed using a personalized health profiling approach where participants wore a pulse oximeter sensor for a fixed period of time and performed specific activities for pre-determined intervals. Using a variety of feature extraction in time, frequency and time-frequency domains, and data processing techniques, the data is fed into a CBR system which retrieves most similar cases and generates alarm and flag according to the case outcomes. The system has been compared with an expert's classification and 90% match is achieved between the expert's and CBR classification. Again, considering the clustered measurements the CBR approach classifies 93% correctly both for the pulse rate and oxygen saturation. Along with the proposed methodology, this paper provides a basis for which the system can be used in analysis of continuous health monitoring and be used as a suitable method as in home/remote monitoring systems.

Place, publisher, year, edition, pages
2013. Vol. 2013, no 2013, 1-11 p.
Keyword [en]
Health Monitoring, Elderly, Case-Based Reasoning, Cluster Analysis
National Category
Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-28738DOI: 10.1155/2013/380239OAI: oai:DiVA.org:oru-28738DiVA: diva2:616988
Projects
SAAPHOREMOTE
Funder
EU, FP7, Seventh Framework Programme
Available from: 2013-04-20 Created: 2013-04-20 Last updated: 2017-10-17Bibliographically approved

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