title: An intelligent health monitoring system using radio-frequency identification technology.
abstract: Long-term care (LTC) for the elderly has become extremely important in recent years. It is necessary for the different physiological monitoring systems to be integrated on the same interface to help oversee and manage the elderly's needs. This paper presents a novel health monitoring system for LTC services using radio-frequency identification (RFID) technology. Dual-band RFID protocols were included in the system, in which the high-frequency (HF) band of 13.56 MHz was used to identify individuals and the microwave band of 2.45 GHz was used to monitor physiological information. Distinct physiological data, including oxyhemoglobin saturation by pulse oximetry (SpO2), blood pressure, blood sugar, electrocardiogram (ECG) readings, body temperature, and respiration rate, were monitored by various biosensors. The intelligent RFID health monitoring system provided the features of the real-time acquisition of biomedical signals and the identification of personal information pertaining to the elderly and patients in nursing homes.
authors.affiliation: Department of Mechatronics Engineering, National Changhua University of Education, Changhua, Taiwan.
authors.forename: Yeong-Lin
authors.initials: YL
authors.lastname: Lai
authors.affiliation: Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, Taiwan.
authors.forename: Chin-Ling
authors.initials: CL
authors.lastname: Chen
authors.affiliation: Department of Health Care Administration, Chang Jung Christian University, Tainan, Taiwan.
authors.forename: Ching-Hisang
authors.initials: CH
authors.lastname: Chang
authors.affiliation: Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung, Taiwan.
authors.forename: Chih-Yu
authors.initials: CY
authors.lastname: Hsu
authors.affiliation: Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan.
authors.forename: Yeong-Kang
authors.initials: YK
authors.lastname: Lai
authors.affiliation: Shenzhen Graduate School, Harbin Institute of Technology, HIT Campus of Shenzhen University Town, Shenzhen, Guangdong, China.
authors.forename: Kuo-Kun
authors.initials: KK
authors.lastname: Tseng
authors.affiliation: Department of Mechatronics Engineering, National Changhua University of Education, Changhua, Taiwan.
authors.forename: Chih-Cheng
authors.initials: CC
authors.lastname: Chen
authors.affiliation: Department of Mechatronics Engineering, National Changhua University of Education, Changhua, Taiwan.
authors.forename: Chun-Yi
authors.initials: CY
authors.lastname: Zheng
mesh_terms: D001786:Blood Glucose; D001794:Blood Pressure; D001831:Body Temperature; D000067917:Cloud Computing; D004562:Electrocardiography; D006801:Humans; D008134:Long-Term Care / Q000379:methods*; D018670:Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods*; D010092:Oximetry; D057233:Radio Frequency Identification Device / Q000379:methods*; D058998:Remote Sensing Technology / Q000295:instrumentation / Q000379:methods*; D056152:Respiratory Rate
chemical_list: D001786:Blood Glucose
keywords: Radio frequency identification (RFID); health monitoring; long-term care (LTC); reader; tag