research-article

Investigating the viability of automated, intuitive, and contextual insights for chronic disease self-management using ubiquitous computing technologies

Author:

Dmitri KatzAuthors Info & Claims

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct

Pages 423 - 428

https://doi.org/10.1145/2968219.2971356

Published: 12 September 2016 Publication History

Abstract

High quality and affordable support for chronic health conditions is simultaneously one of the great challenges and opportunities for the application of ubiquitous computing technologies. Mobile networks of wearable connected devices and sensors have the potential to offer data driven personalized support and contextually aware real-time advice that could help people in their everyday lives. My initial research has suggested three key areas for the implementation of such systems: reducing workload, automating extraction of meaningful information, and the communication of insights in an intuitive, timely and emotionally sensitive manner. While there are many technical issues involved with realization, the human factors related to user interaction with personal data will be critical in building systems that motivate users to choose beneficial lifestyle choices, and will therefore be a major focus of my research.

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Cited By

Bhogireddy GMallela MPutta SDontireddy SOngwere T(2023)Gotta Track It: Designing a Mobile App for Hair-Fall Monitoring, Care, and Management Among Patients with Underlying ConditionsCompanion Publication of the 2023 ACM Designing Interactive Systems Conference10.1145/3563703.3596629(152-155)Online publication date: 10-Jul-2023
https://dl.acm.org/doi/10.1145/3563703.3596629
Li THaynes MJuhring JRucker BPrabhakar AOngwere T(2022)Designing a Mobile App with Patients with Discordant Chronic Comorbidities (DCCs): a Usability StudyNordic Human-Computer Interaction Conference10.1145/3546155.3546648(1-9)Online publication date: 8-Oct-2022
https://dl.acm.org/doi/10.1145/3546155.3546648
Mao SKhalifa YZhang ZShu KSuri ABouzid ZSejdic E(2021)Ubiquitous computingDigital Health10.1016/B978-0-12-818914-6.00002-8(211-230)Online publication date: 2021
https://doi.org/10.1016/B978-0-12-818914-6.00002-8

Index Terms

Investigating the viability of automated, intuitive, and contextual insights for chronic disease self-management using ubiquitous computing technologies
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
      1. Cognitive science
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct

September 2016

1807 pages

ISBN:9781450344623

DOI:10.1145/2968219

General Chairs:
Paul Lukowicz
DFKI and University of Kaiserslautern
,
Antonio Krüger
DFKI and Saarland University
,
Program Chairs:
Andreas Bulling
Max Planck Institute for Informatics
,
Youn-Kyung Lim
KAIST
,
Shwetak N. Patel
University of Washington

Copyright © 2016 ACM.

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Published: 12 September 2016

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UbiComp '16

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UbiComp '16: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 12 - 16, 2016

Germany, Heidelberg

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Bhogireddy GMallela MPutta SDontireddy SOngwere T(2023)Gotta Track It: Designing a Mobile App for Hair-Fall Monitoring, Care, and Management Among Patients with Underlying ConditionsCompanion Publication of the 2023 ACM Designing Interactive Systems Conference10.1145/3563703.3596629(152-155)Online publication date: 10-Jul-2023
https://dl.acm.org/doi/10.1145/3563703.3596629
Li THaynes MJuhring JRucker BPrabhakar AOngwere T(2022)Designing a Mobile App with Patients with Discordant Chronic Comorbidities (DCCs): a Usability StudyNordic Human-Computer Interaction Conference10.1145/3546155.3546648(1-9)Online publication date: 8-Oct-2022
https://dl.acm.org/doi/10.1145/3546155.3546648
Mao SKhalifa YZhang ZShu KSuri ABouzid ZSejdic E(2021)Ubiquitous computingDigital Health10.1016/B978-0-12-818914-6.00002-8(211-230)Online publication date: 2021
https://doi.org/10.1016/B978-0-12-818914-6.00002-8

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