Health Monitoring for Elderly: An Application Using Case-Based Reasoning and Cluster Analysis

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.SAAPHOREMOT