A smartwatch-based medication adherence system

Haik Kalantarian, Nabil Alshurafa, Ebrahim Nemati, Tuan Le, Majid Sarrafzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

27 Scopus citations

Abstract

Poor adherence to prescription medication can compromise treatment effectiveness and cost the billions of dollars in unnecessary health care expenses. Though various interventions have been proposed for estimating adherence rates, few have been shown to be effective. Digital systems are capable of estimating adherence without extensive user involvement and can potentially provide higher accuracy with lower user burden than manual methods. In this paper, we propose a smartwatch-based system for detecting adherence to prescription medication based the identification of several motions using the built-in tri-axial accelerometers and gyroscopes. The efficacy of the proposed technique is confirmed through a survey of medication ingestion habits and experimental results on movement classification.

Original languageEnglish (US)
Title of host publication2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467372015
DOIs
StatePublished - Oct 15 2015
Event12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015 - Cambridge, United States
Duration: Jun 9 2015Jun 12 2015

Publication series

Name2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015

Other

Other12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015
CountryUnited States
CityCambridge
Period6/9/156/12/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Health Informatics
  • Instrumentation
  • Signal Processing

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