STop Obesity Platform

Risultati finali

STOP Platform second release

Software release

Big Data Application layer first release

Software release

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

Software release

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

Software release

STOP Platform first release

Software release

Big Data Application layer second release.

Software release

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.

STOP website and promotional material

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

Pubblicazioni

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

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

Chatbot based Behaviour Analysis for Obesity Support Platform

Autori: Yanxin Wu, Ryan Donovan, Binh Vu, Felix Engel, Matthias Hemmje, and Haithem Afli
Pubblicato in: The 6th Collaborative European Research Conference, Numero Vol 2815, 2020
Editore: CEUR Workshop Proceedings

Towards Continuous Professional Monitoring of Health Status Based on Energetic Balancing

Autori: Vu, B., Bruchhaus, S., Moorhead, A., Zheng, H., D'Arco, L., Lynch, L., ... & Hemmje, M.
Pubblicato in: 2022 IEEE International Workshop on Sport, Technology and Research (STAR), 2022, Pagina/e 72-77
Editore: IEEE

Digital Storytelling: a learning perspective

Autori: Brunetti, E., Zampella, M., Di Fuccio, R., Ferrara, F., & Miglino, O.
Pubblicato in: PSYCHOBIT, 2021
Editore: CEUR Workshop Proceedings

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

Autori: Simone Sandri, Matthias Hemmje, Huiru Zheng, Felix Engel, Anne Moorhead, Haiying Wang, Raymond Bond, Mike McTear, Andrea Molinari, Paolo Bouquet
Pubblicato in: 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019, Pagina/e 1-6, ISBN 978-1-7281-1867-3
Editore: IEEE
DOI: 10.1109/bibm47256.2019.8983405

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

Autori: Raffaele Di Fuccio, Monica Zampella, Orazio Miglino
Pubblicato in: PSYCHOBIT 2020, Numero Vol. 2730, 2020, Pagina/e 24
Editore: CEUR Workshop Proceedings

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

Autori: Fusco, L., Diano, F., Somma, F., Di Fuccio, R., Ferrara, F., & Sica, L. S.
Pubblicato in: PSYCHOBIT, 2021
Editore: CEUR Workshop Proceedings

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

Autori: Leske, Mike, Francesca Bottacini, Haithem Afli, and Bruno G. N. Andrade
Pubblicato in: Methods and Protocols, Numero 5(3):42, 2022, ISSN 2409-9279
Editore: MDPI
DOI: 10.3390/mps5030042

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

Autori: Joshi, Praveen, Chandra Thapa, Seyit Camtepe, Mohammed Hasanuzzaman, Ted Scully, and Haithem Afli
Pubblicato in: Methods and Protocols, 2022, ISSN 2409-9279
Editore: MDPI
DOI: 10.3390/mps5040060

Enabling All In-Edge Deep Learning: A Literature Review

Autori: P. Joshi, M. Hasanuzzaman, C. Thapa, H. Afli and T. Scully
Pubblicato in: IEEE Access, Numero Vol 11, 2023, Pagina/e 3431-3460, ISSN 2169-3536
Editore: 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

Autori: Luigi D’Arco, Haiying Wang, Huiru Zheng
Pubblicato in: Methods and Protocols, Numero 5 (3), 2022, ISSN 2409-9279
Editore: MDPI
DOI: 10.3390/mps5030045

Deep Learning in Systems Medicine

Autori: 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
Pubblicato in: Briefings in Bioinformatics, Numero Volume 22, Numero 2, March 2021, 2021, Pagina/e 1543-1559, ISSN 1433-3058
Editore: Oxford Academic
DOI: 10.1093/bib/bbaa237

Risultati finali

Pubblicazioni

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