title: A personalized health-monitoring system for elderly by combining rules and case-based reasoning.
abstract: Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly's medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.
authors.affiliation: School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden.
authors.forename: Mobyen Uddin
authors.initials: MU
authors.lastname: Ahmed
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001185:Artificial Intelligence; D003658:Decision Making, Computer-Assisted; D015577:Geriatric Assessment; D006801:Humans; D057187:Independent Living; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D055986:Vital Signs; D059015:Wireless Technology