Affiliations: [a] School of Information Science and Engineering, Lanzhou University, No. 222 Tianshui South Road, Lanzhou, Gansu 730000, China | [b] School of Software Engineering, Chongqing University, No. 174 Shazheng Road, Chongqing 400044, China | [c] Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, No. 174 Shazheng Road, Chongqing 400044, China
Abstract: Because of the increased lifespan, there is an immense increase in the demand of 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.
Keywords: Wellness condition, elderly care, RFID, biological data