title: Continuous activity monitoring and intelligent contextual prompting to improve medication adherence.
abstract: Poor medication adherence is a serious medical problem, particularly in older adults. Various solutions have been developed to remind people to take their medications, but these systems are usually simple time-based alarm systems that are not particularly effective. We describe a system that is context aware, and that utilizes information about past patterns of behavior plus the current context to provide prompts at the appropriate time and place. A case study from our initial deployment of the system to eleven older adults illustrates the possibilities and advantages of context aware prompting systems.
authors.affiliation: Digital Health Group at Intel Corporation, 20270 NW, Amberglen Ct, AG1-102, Beaverton, OR 97229, USA. jay.lundell@intel.com
authors.forename: Jay
authors.initials: J
authors.lastname: Lundell
authors.forename: Tamara L
authors.initials: TL
authors.lastname: Hayes
authors.forename: Sengul
authors.initials: S
authors.lastname: Vurgun
authors.forename: Umut
authors.initials: U
authors.lastname: Ozertem
authors.forename: Janna
authors.initials: J
authors.lastname: Kimel
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Kaye
authors.forename: Farzin
authors.initials: F
authors.lastname: Guilak
authors.forename: Misha
authors.initials: M
authors.lastname: Pavel
mesh_terms: D001185:Artificial Intelligence; D016903:Drug Monitoring / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D009043:Motor Activity / Q000187:drug effects* / Q000502:physiology*; D010349:Patient Compliance; D014584:User-Computer Interface