Elder Care Alert Management - Decision Support by a Logistic Regression Model

Abstract

The Elder Care project implies the use of a body sensor and a location device by each elderly. This architecture will originate a very large data set that should be treated by statistical methods. We purpose a logistic model approach, that will be used during the prototype implementation phase and after that in the comercial phase. In the prototype implementation phase (already running), an elders sample is going to be analyzed to eliminate some redundant or useless covariates, allowing a spare in the final equipment complexity and price. Besides, logistic model has an easy odds ratio interpretation, and so we will be able to determine elders problems risk factors. After the prototype implementation phase, we hope to have a better knowledge of elders risk factors and important covariates that must be considered. Again, the logistic model may be applied to correctly decide whenever an alarm signal should be sent for some monitorized elderly, preventing sensibility and specificity issues. The presented decision model will be used by a multi-agent system, in order to make reliable decisions using fewer resources.