Health monitoring for elderly: an application using case-based reasoning and cluster analysis
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
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.
Health Monitoring, Elderly, Case-Based Reasoning, Cluster Analysis
Research subject Computer Science
IdentifiersURN: urn:nbn:se:oru:diva-28738DOI: 10.1155/2013/380239OAI: oai:DiVA.org:oru-28738DiVA: diva2:616988
FunderEU, FP7, Seventh Framework Programme