Demo abstract: Mobile sensing to improve medication adherence

Ramin Fallahzadeh, Bryan Minor, Lorraine Evangelista, Diane J. Cook, Hassan Ghasemzadeh

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

4 Scopus citations

Abstract

One of major challenges in chronic disease self-management is the lack of medication adherence. Despite the proliferation of mobile technologies, the potential of using pervasive computing solutions for improved medication management has remained almost unexplored. In this paper, we present a smart-phone based system capable of delivering adaptive activity-aware medication reminders by learning the user's activity of daily living and detecting the most appropriate and effective timing for medication reminders centered around the initial user-specified schedule.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017
PublisherAssociation for Computing Machinery, Inc
Pages279-280
Number of pages2
ISBN (Electronic)9781450348904
DOIs
StatePublished - Apr 18 2017
Externally publishedYes
Event16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017 - Pittsburgh, United States
Duration: Apr 18 2017Apr 20 2017

Publication series

NameProceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017

Conference

Conference16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017
CountryUnited States
CityPittsburgh
Period4/18/174/20/17

Keywords

  • Activity learning
  • Medication adherence
  • Prompting

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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  • Cite this

    Fallahzadeh, R., Minor, B., Evangelista, L., Cook, D. J., & Ghasemzadeh, H. (2017). Demo abstract: Mobile sensing to improve medication adherence. In Proceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017 (pp. 279-280). (Proceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017). Association for Computing Machinery, Inc. https://doi.org/10.1145/3055031.3055045