Determining senior wellness status using an intelligent system based on wireless sensor network and bioinformation.

Because of the increased lifespan, there is an immense increase in the demand on healthcare services for senior wellness. In this study, we proposed a system based on biological data, such as body temperature, heart rate and blood pressure, and activity data of the elderly living in a stable environment, such as nursing home, to determine their wellness conditions. The Radio Frequency Identification (RFID) is used to monitor and record real-time location information of the elderly. A novel framework integrating the daily activity data and the biological data for determining the wellness status of an elderly has been modeled by using support vector machine (SVM). In this study, the established model was evaluated on 5 elderly people living in the geriatrics department at the third people's hospital of Lanzhou. The experimental results showed that with effective monitoring and alarm systems, the adverse effects on wellness conditions of elderly people living in a nursing home could be ameliorated to some extent, and the healthcare services for the elderly could be improved.