Measuring the Wellness Indices of the Elderly Using RFID Sensors Data in a Smart Nursing Home

摘要

In this study, we present a low-cost, flexible and data-driven intelligent system which could monitor and determine the wellness conditions of the elderly living in a nursing home in relation to their daily activities. Changes of daily activities are obtained in real time for reasonable forecasting of wellness indices. These tasks are achieved by a framework integrating spatial and temporal contextual information for determining the wellness of the elderly. The daily activities of the elderly are detected through the location information collected by the Radio Frequency Identification (RFTD) technology. A Support Vector Machine (SVM) model is trained using the activity data of 5 different elderly people living in a nursing home, and the results show that it performs well in forecasting wellness indices of the elderly.