Konstantia Zarkogianni, Greece

National Technical University of Athens School of Electrical and Computer Engineering
Konstantia Zarkogianni received the diploma in Electrical and Computer Engineering (2003) from the Aristotle University of Thessaloniki, Greece, the MSc Degree in Electronic and Computer Engineering (2005) from the Technical University of Crete, Greece, and the PhD degree (2011) from the NTUA, Greece. Since 2005, she is a member of the BIOmedical Simulations and IMaging Laboratory of NTUA. In October 2017, she was appointed as permanent laboratory teaching staff at the School of Electrical and Computer Engineering of the NTUA. Her current research interests include clinical decision support systems, control systems, physiological systems modelling, diabetes management, multiscale modelling and serious games design in health. She has authored or coauthored 12 papers in refereed international journals, one chapter in book, and 26 papers in international conference proceedings. She has participated as research associate and principle investigator in national and EU funded projects. She has been a guest editor of the special issue on Emerging Technologies for the Management of Diabetes Mellitus (Springer Journal of Medical and Biological Engineering and Computing [MBEC], 2015). She has been a member of the Editorial Board of the SpringerPlus journal in 2016 and reviewer for international scientific journals (IEEE Transactions on Biomedical Engineering, IEEE Journal of Biomedical and Health Informatics, Springer Medical & Biological Engineering & Computing, Elsevier Journal of Biomedical Informatics, and JSM Diabetology and Management). She is a member of the Institute of Electrical and Electronics Engineers (ΙΕΕΕ) and the Technical Chamber of Greece.

Presenter of 2 Presentations

ORAL PRESENTATION SESSION

THE ENDORSE PILOT TRIAL

Abstract

Background and Aims

Within the Greek funded project, named “ENDORSE”, an innovative integrated platform is developed harnessing the power of Artificial Intelligence, sensing and gamification technologies, facilitating self-disease management in children with Type 1 Diabetes Mellitus (T1DM) while supporting decision making in formal and informal caregivers. A two phase pilot randomized trial is foreseen to evaluate its effectiveness.

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Methods

Particular use cases based on the applied insulin treatment are defined involving children 6-16 years old. Taking into consideration the current clinical methods for managing T1DM in Greece along with the necessary approvals from the national ethical committee, a clinical protocol is drafted specifying, amongst others, inclusion/exclusion criteria (e.g. diabetes duration>1 year, without celiac disease, without complications) and monitored parameters.

Results

Following a training phase, the participants receive hardware (e.g. Insulclock devices and activity trackers) and software modules to use them for 3 months during their daily habits while performing monthly screening visits to the “Agia Sofia” Children’s Hospital. In Phase 1 pilot, 30 patients are recruited. This phase represents a feasibility study to implement the technical equipment into patient care and to collect new data for improving the ENDORSE recommendation engine. In Phase 2 pilot, 70 patients are recruited and randomly assigned (2/3:1/3) into an intervention and a control group.

Conclusions

The ENDORSE pilot trial tests the feasibility of implementing advanced ICT technologies into routine clinical care of T1DM children while improving patients’ satisfaction and clinical outcomes. Acknowledgements: Supported within the framework of the ENDORSE project, which is funded by the NSRF (Grant agreement: Τ1ΕΔΚ-03695)

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ORAL PRESENTATION SESSION

A COMPREHENSIVE APPROACH TO EMPOWER SELF-MANAGEMENT OF HEALTH IN CHILDHOOD OBESITY BASED ON GAMIFICATION MECHANISMS AND BIOFEEDBACK

Abstract

Background and Aims

Modern m-health technologies open new perspectives in managing childhood obesity. Within the Greek funded project, named “ENDORSE”, an innovative software ecosystem is developed incorporating Artificial Intelligence and gamification technologies capable of delivering tools and services facilitating self- management of health while engaging the active involvement of formal and informal caregivers.

Methods

ENDORSE applies a parent-child multicomponent intervention including dietary, physical activity, educational and behavioral components. It implements a goal-oriented approach which includes periodic assessment of child’s weight, behavioral lifestyle and needs in order to accordingly adjust goal settings and improve adherence. Obese children are trained and encouraged to adopt healthy diet and physical activity through their interaction with the ENDORSE serious game. Aiming at optimizing the parental role, a mobile application has been developed facilitating daily self-monitoring of goals and communication with healthcare professionals.

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Results

The ENDORSE platform has the capability to leverage data from different sources (e.g. activity trackers, mobile apps) in order to create a complete user profile. Personalized, tailored messages and reminders targeting child and parents, along with recommendations for goal settings adjustment and adherence reports, are produced by the ENDORSE recommendation engine with the aim to achieve personalization and adaptation.

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Conclusions

The ENDORSE platform implements modern m-health technologies into routine clinical care of obese children. Future work includes the execution of pilot trials to evaluate its effectiveness in terms of improving health outcomes and user’s acceptance. Acknowledgements: Supported within the framework of the ENDORSE project, which is funded by the NSRF (Grant agreement: Τ1ΕΔΚ-03695)

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