title: eFurniture for home-based frailty detection using artificial neural networks and wireless sensors.
abstract: The purpose of this study is to integrate wireless sensor technologies and artificial neural networks to develop a system to manage personal frailty information automatically. The system consists of five parts: (1) an eScale to measure the subject's reaction time; (2) an eChair to detect slowness in movement, weakness and weight loss; (3) an ePad to measure the subject's balancing ability; (4) an eReach to measure body extension; and (5) a Home-based Information Gateway, which collects all the data and predicts the subject's frailty. Using a furniture-based measuring device to provide home-based measurement means that health checks are not confined to health institutions. We designed two experiments to obtain optimum frailty prediction model and test overall system performance: (1) We developed a three-step process to adjust different parameters to obtain an optimized neural identification network whose parameters include initialization, L.R. dec and L.R. inc. The post-process identification rate increased from 77.85% to 83.22%. (2) We used 149 cases to evaluate the sensitivity and specificity of our frailty prediction algorithm. The sensitivity and specificity of this system are 79.71% and 86.25% respectively. These results show that our system is a high specificity prediction tool that can be used to assess frailty.
authors: Department of Computer Science and Information Engineering, Healthy Aging Research Center, Chang Gung University, Taiwan, ROC.
authors: Yu-Chuan
authors: YC
authors: Chang
authors: Chung-Chih
authors: CC
authors: Lin
authors: Pei-Hsin
authors: PH
authors: Lin
authors: Chun-Chang
authors: CC
authors: Chen
authors: Ren-Guey
authors: RG
authors: Lee
authors: Jing-Siang
authors: JS
authors: Huang
authors: Tsai-Hsuan
authors: TH
authors: Tsai
mesh_terms: D000368:Aged; D005104:Expert Testimony; D005260:Female; D016330:Frail Elderly; D006798:Housing; D006801:Humans; D007374:Interior Design and Furnishings; D008297:Male; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D016571:Neural Networks, Computer; D017216:Telemedicine / Q000295:instrumentation*; D059015:Wireless Technology / Q000295:instrumentation*