STop Obesity Platform

Livrables

Obesity Care & Connected Health Platform Validation

This report documents the outcomes of executed trials and pilots for system validation and input for further developmentOthers as stated in the proposal OKK will be the deliverable lead because of there expertise and efforts in this WP

Report on STOP Platform requirements analysis, architecture specification, harmonization, integration and Deployment

This deliverable documents STOP Platform requirements analysis, architecture, harmonization, integration and Deployment specification.

STOP Platform Data and Knowledge Management, Pre-Processing and User Interaction requirements analysis, specification and implementation

This deliverable documents the Data-/ Knowledge Management and Pre-Processing and User Interaction requirements analysis, specification and implementation. The document will related, to insights from WP1

STOP Platform Information, Feature Extraction, Big Data and Machine Learning requirements analysis and architecture specification.

This deliverable documents Information and Feature Extraction requirements analysis and architecture specification. The document will related, to insights from WP1 Others as stated in the proposal CIT will be the deliverable lead, because of there expertise and efforts in this WP.

Big Data Application layer first release

Software release

STOP Data and Knowledge Management, Pre-Processing and User Interaction layer first release

Software release

STOP Platform first release

Software release

STOP website and promotional material

This deliverable documents the availability of the Website, promotion templates, ...

Publications

“STop Obesity Platform”: a gamified learning system to build a new healthier life-style

Auteurs: Zampella, M., Brunetti, E., Mugione, M., Di, Fuccio R.; Ponticorvo M., Ferrara, F.
Publié dans: Stat. Edu’21-New Perspectives in Statistics Education, 2022, ISBN 978-88-6887-124-6
Éditeur: FedOA-Federico II University Press
DOI: 10.6093/978-88-6887-124-6

Chatbot based Behaviour Analysis for Obesity Support Platform

Auteurs: Yanxin Wu, Ryan Donovan, Binh Vu, Felix Engel, Matthias Hemmje, and Haithem Afli
Publié dans: The 6th Collaborative European Research Conference, Numéro Vol 2815, 2020
Éditeur: CEUR Workshop Proceedings

Towards Continuous Professional Monitoring of Health Status Based on Energetic Balancing

Auteurs: Vu, B., Bruchhaus, S., Moorhead, A., Zheng, H., D'Arco, L., Lynch, L., ... & Hemmje, M.
Publié dans: 2022 IEEE International Workshop on Sport, Technology and Research (STAR), 2022, Page(s) 72-77
Éditeur: IEEE

Digital Storytelling: a learning perspective

Auteurs: Brunetti, E., Zampella, M., Di Fuccio, R., Ferrara, F., & Miglino, O.
Publié dans: 2021
Éditeur: CEUR Workshop Proceedings

Is there an Optimal Technology to Provide Personal Supportive Feedback in Prevention of Obesity?

Auteurs: Simone Sandri, Matthias Hemmje, Huiru Zheng, Felix Engel, Anne Moorhead, Haiying Wang, Raymond Bond, Mike McTear, Andrea Molinari, Paolo Bouquet
Publié dans: 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019, Page(s) 1-6, ISBN 978-1-7281-1867-3
Éditeur: IEEE
DOI: 10.1109/bibm47256.2019.8983405

STOP: a gamified approach to support obese patients in changing their health habits

Auteurs: Raffaele Di Fuccio, Monica Zampella, Orazio Miglino
Publié dans: PSYCHOBIT 2020, Numéro Vol. 2730, 2020, Page(s) 24
Éditeur: CEUR Workshop Proceedings

The SToP project app: promoting the creation of habits through explicit learning and self-monitoring

Auteurs: Fusco, L., Diano, F., Somma, F., Di Fuccio, R., Ferrara, F., & Sica, L. S.
Publié dans: PSYCHOBIT, 2021
Éditeur: CEUR Workshop Proceedings

Bi-Objective Genetic Algorithm Fitness Function for Feature Selection on Microbiome Datasets

Auteurs: Leske, Mike, Francesca Bottacini, Haithem Afli, and Bruno G. N. Andrade
Publié dans: Methods and Protocols, Numéro 5(3):42, 2022, ISSN 2409-9279
Éditeur: MDPI
DOI: 10.3390/mps5030042

Performance and Information Leakage in Splitfed Learning and Multi-Head Split Learning in Healthcare Data and Beyond

Auteurs: Joshi, Praveen, Chandra Thapa, Seyit Camtepe, Mohammed Hasanuzzaman, Ted Scully, and Haithem Afli
Publié dans: Methods and Protocols, 2022, ISSN 2409-9279
Éditeur: MDPI
DOI: 10.3390/mps5040060

Enabling All In-Edge Deep Learning: A Literature Review

Auteurs: P. Joshi, M. Hasanuzzaman, C. Thapa, H. Afli and T. Scully
Publié dans: IEEE Access, Numéro Vol 11, 2023, Page(s) 3431-3460, ISSN 2169-3536
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2023.3234761

Assessing Impact of Sensors and Feature Selection in Smart-Insole-Based Human Activity Recognition

Auteurs: Luigi D’Arco, Haiying Wang, Huiru Zheng
Publié dans: Methods and Protocols, Numéro 5 (3), 2022, ISSN 2409-9279
Éditeur: MDPI
DOI: 10.3390/mps5030045

Deep Learning in Systems Medicine

Auteurs: Haiying Wang, Estelle Pujos-Guillot, Blandine Comte, Joao Luis de Miranda, Vojtech Spiwok, Ivan Chorbev, Filippo Castiglione, Paolo Tieri, Steven Watterson, Roisin McAllister, Tiago de Melo Malaquias, Massimiliano Zanin, Taranjit Singh Rai, Huiru Zheng
Publié dans: Briefings in Bioinformatics, Numéro Volume 22, Numéro 2, March 2021, 2021, Page(s) 1543-1559, ISSN 1433-3058
Éditeur: Oxford Academic
DOI: 10.1093/bib/bbaa237

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