research-article

Integrating mobile sensing and social network for personalized health-care application

Authors:

Kejie LuAuthors Info & Claims

SAC '15: Proceedings of the 30th Annual ACM Symposium on Applied Computing

Pages 527 - 534

https://doi.org/10.1145/2695664.2695767

Published: 13 April 2015 Publication History

Abstract

In the past decade, the rates of overweight and obesity have been increasing dramatically worldwide, which lead to serious health risks, including heart diseases, diabetes, and various cancers. Clearly, to improve the health conditions, physical activities and diet are the most important factors for people to control the weight and thus achieve healthy lifestyle. Motivated by the amazingly growth of smartphone ownership and the sensing technologies, in this paper, we propose a mobile-sensing based health recognition and recommendation framework, namely, H-Rec². The main idea is to use smartphone to unobtrusively record and analyze the user's physical activity and health status, and at the same time obtain the personalized health food recommendations from the remote server. To demonstrate the idea, we implemented a prototype system and conduct systematic experiments to evaluate performance. The evaluation results confirm the proposed approaches with regard to the effectiveness and usability.

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Min AMiller WRocha LBörner KBrattig Correia RShih P(2023)Understanding Contexts and Challenges of Information Management for Epilepsy CareProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580949(1-15)Online publication date: 19-Apr-2023
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Yamamoto SGu FIkematsu KKato KSugiura Y(2023)Maintenance-Free Smart Hand Dynamometer2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)10.1109/EMBC40787.2023.10340847(1-5)Online publication date: 24-Jul-2023
https://doi.org/10.1109/EMBC40787.2023.10340847
Cai YYu FKumar MGladney RMostafa J(2022)Health Recommender Systems Development, Usage, and Evaluation from 2010 to 2022: A Scoping ReviewInternational Journal of Environmental Research and Public Health10.3390/ijerph19221511519:22(15115)Online publication date: 16-Nov-2022
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Index Terms

Integrating mobile sensing and social network for personalized health-care application
1. Applied computing
  1. Life and medical sciences

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Published In

cover image ACM Conferences

SAC '15: Proceedings of the 30th Annual ACM Symposium on Applied Computing

April 2015

2418 pages

ISBN:9781450331968

DOI:10.1145/2695664

Conference Chairs:
Roger L. Wainwright
University of Tulsa
,
Juan Manuel Corchado
University of Salamanca, Spain
,
Program Chairs:
Alessio Bechini
University of Pisa, Italy
,
Jiman Hong
Soongsil University, South Korea

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 April 2015

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Funding Sources

International Science & Technology Cooperation Program of China
NSFC
State Key Laboratory of Software Development Environment

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SAC 2015

Sponsor:

SIGAPP

SAC 2015: Symposium on Applied Computing

April 13 - 17, 2015

Salamanca, Spain

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SAC '15 Paper Acceptance Rate 291 of 1,211 submissions, 24%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Min AMiller WRocha LBörner KBrattig Correia RShih P(2023)Understanding Contexts and Challenges of Information Management for Epilepsy CareProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580949(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580949
Yamamoto SGu FIkematsu KKato KSugiura Y(2023)Maintenance-Free Smart Hand Dynamometer2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)10.1109/EMBC40787.2023.10340847(1-5)Online publication date: 24-Jul-2023
https://doi.org/10.1109/EMBC40787.2023.10340847
Cai YYu FKumar MGladney RMostafa J(2022)Health Recommender Systems Development, Usage, and Evaluation from 2010 to 2022: A Scoping ReviewInternational Journal of Environmental Research and Public Health10.3390/ijerph19221511519:22(15115)Online publication date: 16-Nov-2022
https://doi.org/10.3390/ijerph192215115
Alwakeel LLano K(2022)Functional and Technical Aspects of Self-management mHealth Apps: Systematic App Search and Literature ReviewJMIR Human Factors10.2196/297679:2(e29767)Online publication date: 25-May-2022
https://doi.org/10.2196/29767
Kobayashi SMatsugu SShiokawa H(2022)Indexing complex networks for fast attributed kNN queriesSocial Network Analysis and Mining10.1007/s13278-022-00904-w12:1Online publication date: 16-Jul-2022
https://doi.org/10.1007/s13278-022-00904-w
Nagpal MBarbaric ASherifali DMorita PCafazzo J(2021)Patient-Generated Data Analytics of Health Behaviors of People Living With Type 2 Diabetes: Scoping ReviewJMIR Diabetes10.2196/290276:4(e29027)Online publication date: 20-Dec-2021
https://doi.org/10.2196/29027
De Croon RVan Houdt LHtun NŠtiglic GVanden Abeele VVerbert K(2021)Health Recommender Systems: Systematic ReviewJournal of Medical Internet Research10.2196/1803523:6(e18035)Online publication date: 29-Jun-2021
https://doi.org/10.2196/18035
Ferretto LBellei EBiduski DBin LMoro MCervi CDe Marchi A(2020)A Physical Activity Recommender System for Patients With Arterial HypertensionIEEE Access10.1109/ACCESS.2020.29835648(61656-61664)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2983564
Assaf MRizzotti-Kaddouri APunceva M(2019)Sleep Detection Using Physiological Signals from a Wearable Device5th EAI International Conference on IoT Technologies for HealthCare10.1007/978-3-030-30335-8_3(23-37)Online publication date: 14-Dec-2019
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Rubaiat SRahman MHasan M(2018)Important Feature Selection & Accuracy Comparisons of Different Machine Learning Models for Early Diabetes Detection2018 International Conference on Innovation in Engineering and Technology (ICIET)10.1109/CIET.2018.8660831(1-6)Online publication date: Dec-2018
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