title: Automatic identification of solid-phase medication intake using wireless wearable accelerometers.
abstract: We have proposed a novel solution to a fundamental problem encountered in implementing non-ingestion based medical adherence monitoring systems, namely, how to reliably identify pill medication intake. We show how wireless wearable devices with tri-axial accelerometer can be used to detect and classify hand gestures of users during solid-phase medication intake. Two devices were worn on the wrists of each user. Users were asked to perform two activities in the way that is natural and most comfortable to them: (1) taking empty gelatin capsules with water, and (2) drinking water and wiping mouth. 25 users participated in this study. The signals obtained from the devices were filtered and the patterns were identified using dynamic time warping algorithm. Using hand gesture signals, we achieved 84.17 percent true positive rate and 13.33 percent false alarm rate, thus demonstrating that the hand gestures could be used to effectively identify pill taking activity.
authors.lastname: Rui Wang
authors.forename: Zdenka
authors.initials: Z
authors.lastname: Sitova
authors.lastname: Xiaoqing Jia
authors.lastname: Xiang He
authors.forename: Tobi
authors.initials: T
authors.lastname: Abramson
authors.forename: Paolo
authors.initials: P
authors.lastname: Gasti
authors.forename: Kiran S
authors.initials: KS
authors.lastname: Balagani
authors.forename: Aydin
authors.initials: A
authors.lastname: Farajidavar
mesh_terms: D061725:Accelerometry / Q000295:instrumentation; D000203:Activities of Daily Living; D000328:Adult; D000465:Algorithms; D004867:Equipment Design; D006225:Hand; D006801:Humans; D055118:Medication Adherence; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D033281:Nontherapeutic Human Experimentation; D013607:Tablets; D059015:Wireless Technology / Q000295:instrumentation*
chemical_list: D013607:Tablets