Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
An application for continuous behavioral health monitoring and delivering digital personalized behavior change interventions
Download
MB.pdf
Date
2021-12-10
Author
Başkaya, Mert
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
358
views
389
downloads
Cite This
In this thesis, a continuous behavioral health monitoring architecture is developed for chronic disease patients with a mobile application, a health data ingestion stack and a rule-based intervention engine. The mobile application is used for medical device integration and activity tracking. End-users also have interfaces to check their care plan activities, their adherence performances for them and to receive and configure motivational interventions and reminders about their activities. The ingestion stack is capable of stream and batch processing and used for collecting various health data and making the data available for the underlying intervention engine in the desired format. The rule-based intervention engine calculates and delivers interventions based on received patient data and defined intervention rules. Components presented in the architecture will be further validated in ADLIFE project containing seven pilot sites with a total of 577 healthcare professionals from 75 hospitals, clinics and primary care services.
Subject Keywords
Behavioral health
,
Medical device data
,
Health data processing
,
MHealth
URI
https://hdl.handle.net/11511/95114
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Understanding the perception towards using mHealth applications in practice: Physicians' perspective
Sezgin, Emre; Özkan Yıldırım, Sevgi; Yıldırım, İbrahim Soner (2018-03-01)
The objective of this study was to investigate physicians' perceptions to use mobile health applications in practice, and to identify influencing factors to use the technology. An mHealth technology acceptance model was proposed (M-TAM), and a cross-sectional survey was implemented using structured questionnaire to collect data. Online tools were used for inviting participants (physicians) and data collection from Turkey. The data was analyzed using Confirmatory Factor Analysis (CFA) and Structural Equation...
An Extensible security infrastructure for the secondary use of electronic health records in clinical research
Eryılmaz, Elif; Toroslu, İsmail Hakkı; Doğaç, Asuman; Department of Computer Engineering (2013)
In order to facilitate clinical research studies re-using Electronic Health Records (EHR) has a great potential. Besides interoperability, safeguarding the security and privacy of the medical data in the context of secondary use for clinical research is one of the most important challenges in this respect. In order to ensure that the clinical information is shared among EHR systems and clinical research systems in an ethical and safe way, there needs to be standards-based and adaptable security and privacy ...
Security and Privacy Concerns Regarding Genetic Data in Mobile Health Record Systems: An Empirical Study from Turkey
Özkan, Özlem; Aydın Son, Yeşim; Aydınoğlu, Arsev Umur (2019-06-01)
With the increasing use of genetic testing and applications of bioinformatics in healthcare, genetic and genomic data needs to be integrated into electronic health systems. We administered a descriptive survey to 174 participants to elicit their views on the privacy and security of mobile health record systems and inclusion of their genetic data in these systems. A survey was implemented online and on site in two genetic diagnostic centres. Nearly half of the participants or their close family...
A Data Transformation Methodology to Create Findable, Accessible, Interoperable, and Reusable Health Data: Software Design, Development, and Evaluation Study
Sınacı, Ali Anıl; Gencturk, Mert; Teoman, Huseyin Alper; Laleci Erturkmen, Gokce Banu; Alvarez-Romero, Celia; Martinez-Garcia, Alicia; Poblador-Plou, Beatriz; Carmona-Pírez, Jonás; Löbe, Matthias; Parra-Calderon, Carlos Luis (2023-03-08)
BACKGROUND: Sharing health data is challenging because of several technical, ethical, and regulatory issues. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have been conceptualized to enable data interoperability. Many studies provide implementation guidelines, assessment metrics, and software to achieve FAIR-compliant data, especially for health data sets. Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) is a health data content modeling and exchange s...
An open-source framework of neural networks for diagnosis of coronary artery disease from myocardial perfusion SPECT
Guner, Levent A.; Karabacak, Nese Ilgin; Akdemir, Ozgur U.; Karagöz, Pınar; KOCAMAN, SİNAN ALTAN; ÇENGEL, ATİYE; ÜNLÜ, MUSTAFA (2010-06-01)
The purpose of this study is to develop and analyze an open-source artificial intelligence program built on artificial neural networks that can participate in and support the decision making of nuclear medicine physicians in detecting coronary artery disease from myocardial perfusion SPECT (MPS).
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Başkaya, “An application for continuous behavioral health monitoring and delivering digital personalized behavior change interventions,” M.S. - Master of Science, Middle East Technical University, 2021.