AI empowered context-aware smart system for medication adherence. Issue 2 (12th June 2017)

• Record Type: Journal Article
• Authors: Wu, Qiong; Zeng, Zhiwei; Lin, Jun; Chen, Yiqiang
• Is Part Of: International journal of crowd science. Volume 1:Issue 2(2017)
• Page Start: 102
• Page End: 109
• Publication Date: 2017-06-12
• Subjects: Context awareness -- Argumentation and explainable AI -- Smart pillbox; Human-computer interaction -- Periodicals; Human computation -- Periodicals; Cooperating objects (Computer systems) -- Periodicals; 621.3984
• DOI: 10.1108/IJCS-07-2017-0006
• Languages: English
• ISSNs: 2398-7294

Abstract

Abstract : Purpose: Poor medication adherence leads to high hospital admission rate and heavy amount of health-care cost. To cope with this problem, various electronic pillboxes have been proposed to improve the medication adherence rate. However, most of the existing electronic pillboxes use time-based reminders which may often lead to ineffective reminding if the reminders are triggered at inopportune moments, e.g. user is sleeping or eating. Design/methodology/approach: In this paper, the authors propose an AI-empowered context-aware smart pillbox system. The pillbox system collects real-time sensor data from a smart home environment and analyzes the user's contextual information through a computational abstract argumentation-based activity classifier. Findings: Based on user's different contextual states, the smart pillbox will generate reminders at appropriate time and on appropriate devices. Originality/value: This paper presents a novel context-aware smart pillbox system that uses argumentation-based activity recognition and reminder generation.