Bridging the Early Diagnosis and Treatment Gap of Brain Diseases via Smart, Connected, Proactive and Evidence-based Technological Interventions

Livrables

D6.3 Trials Impact Assessment Report [lead: EY; due: M36]: This report will summarize the approach and key evidences emerged along with the social, economic and organizational assessment performed under Task 6.6, including indications on the different perspectives of target stakeholders (e.g. patients, physicians, hospitals, public institutions, etc.).

Demonstrations' Ethical Considerations and Clearance

D6.1 Demonstrations’ Ethical Considerations and Clearance [lead: ΕΥ; due: M28]: This deliverable will contain on ethical considerations and clearance of ALAMEDA services.

Digital Healthcare Innovation Hub Architecture and Specifications

D72 Digital Healthcare Innovation Hub Architecture and Specifications lead UNISYS due M9 This deliverable will contain detailed specifications of the services of the Digital Healthcare Innovation Hub and of its architecture based on T71

Stakeholder Engagement Plan - Interim Implementation Report

D73 Stakeholder Engagement Plan Interim Implementation Report lead WISE due M18 This deliverable will contain an interim implementation report of the stakeholder including patient engagement plan based on T72

Stakeholder Engagement Plan - Final Report

D7.8 Stakeholder Engagement Plan – Final Report [lead: WISE; due: M36]: This deliverable will contain the final report on the stakeholder (including patient) engagement plan, based on T7.2.

Dissemination Plan and Material

D82 Dissemination Plan and Material lead WISE due M6 This deliverable will present the ALAMEDA dissemination and communication strategy plan and graphical identity of the dissemination material

Report on the Analysis of Privacy and Security Implications

D7.7 Report on the Analysis of Privacy and Security Implications [lead: PLU; due: M36]: This deliverable report on the privacy and security implications, collecting the main outcomes of T7.5 in this respect.

Field Trials Report

D6.2 Field Trials Report [lead: FISM; due: M35]: This deliverable will contain a report of all three use cases implementations in Greece, Italy, and Romania. Key lessons learned and next steps will be included.

Description Methodology & Design Principles of ALAMEDA AI Toolkit Version 2.0

D5.4 Description Methodology & Design Principles of ALAMEDA AI Toolkit – Version 2.0 [lead: ICCS; due: M20]: Updated report on ALAMEDA AI Toolkit specifications.

ALAMEDA Services for Third-Party Healthcare Vendors and Developers

D7.4 ALAMEDA Services for Third-Party Healthcare Vendors and Developers [lead: WCS; due: M24]: This deliverable will contain an initial report on testing and validation procedures and services for third-party vendors based on T7.4.

Design of Stakeholder Engagement Plan

D71 Design of Stakeholder Engagement Plan lead WISE due M5 This deliverable will contain the initial plan of stakeholder including patient engagement based on T72

ALAMEDA Digital Healthcare Innovation Hub Prototype

D7.5 ALAMEDA Digital Healthcare Innovation Hub Prototype [lead: UNISYS; due: M34]: Online and fully functional Digital Healthcare Innovation Hub based on T7.3.

Integration and Validation of Third-Party Healthcare

D7.6 Integration and Validation of Third-Party Healthcare Solutions [lead: WCS; due: M34]: This deliverable will contain the final report on integration and validation of third-party healthcare solutions based on T7.4.

Description Methodology & Design Principles of ALAMEDA AI Toolkit Version 1.0

D51 Description Methodology Design Principles of ALAMEDA AI Toolkit Version 10 lead ICCS due M12 Report on ALAMEDA AI Toolkit specifications An updated version of D51 will be provided on month 20

Project Website and Social Media

D8.1 Project Website and Social Media [lead: WISE; due: M3]: This deliverable is output of T8.2 activities.

ALAMEDA Digital Companion App and Experts Dashboards

D52 ALAMEDA Digital Companion App and Experts Dashboards lead WCS due M14 Prototype implementation

ALAMEDA Toolkit 1.0

D53 ALAMEDA AI Toolkit 10 lead CTL due M18 Working implementation of ALAMEDA AI Toolkit

ALAMEDA Toolkit 2.0

D5.5 ALAMEDA AI Toolkit 2.0 [lead: CTL; due: M30]: Working implementation of ALAMEDA AI Toolkit 2.0.

Publications

ALAMEDA: Towards the Technology-Enabled Optimisation of Brain Healthcare Continuum

Auteurs: Valentina Tageo and ALAMEDA H2020 Project Consortium
Publié dans: Healthcare Innovation, 2023, Page(s) 185-242, ISBN 978-1-80061-420-8
Éditeur: World Scientific Publishing Europe Ltd.
DOI: 10.1142/9781800614192_0008

Monitoring and Predicting Health Status in Neurological Patients: The ALAMEDA Data Collection Protocol

Auteurs: Sorici, A.; Băjenaru, L.; Mocanu, I.G.; Florea, A.M.; Tsakanikas, P.; Ribigan, A.C.; Pedullà, L.; Bougea, A.
Publié dans: Healthcare, Numéro 11, 2023, ISSN 2227-9032
Éditeur: MDPI
DOI: 10.3390/healthcare11192656

Multi-Sensors for Human Activity Recognition

Auteurs: Athina Tsanousa; Georgios Meditskos; Stefanos Vrochidis; Ioannis Kompatsiaris
Publié dans: Sensors, Numéro 8, 2023, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s23104617

Internet of Things Technologies and Machine Learning Methods for Parkinson’s Disease Diagnosis, Monitoring and Management: A Systematic Review

Auteurs: Konstantina-Maria Giannakopoulou; Ioanna Roussaki; Konstantinos Demestichas
Publié dans: Sensors, Numéro 4, 2022, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s22051799

Shared Decision-Making to Improve Health-Related Outcomes for Adults with Stroke Disease

Auteurs: Lidia Bajenaru; Alexandru Sorici; Irina Georgiana Mocanu; Adina Magda Florea; Florina Anca Antochi; Athena Cristina Ribigan
Publié dans: Healthcare, Numéro 11, 2023, ISSN 2227-9032
Éditeur: MDPI
DOI: 10.3390/healthcare11121803

Impact of<i>APOE</i>genotype on cognition in idiopathic and genetic forms of Parkinson’s disease

Auteurs: Christos Koros; Kathrin Brockmann; Athina-Maria Simitsi; Anastasia Bougea; Hui Liu; Ann-Kathrin Hauser; Claudia Schulte; Stefanie Lerche; Ioanna Pachi; Nikolaos Papagiannakis; Roubina Antonelou; Athina Zahou; Isabel Wurster; Efthymia Efthymiopoulou; Ion Beratis; Matina Maniati; Marina Moraitou; Helen Michelakakis; Georgios Paraskevas; Sokratis G. Papageorgiou; Constantin Potagas; Dimitra Papadimit
Publié dans: Movement Disorders, 2023, ISSN 0885-3185
Éditeur: John Wiley & Sons Inc.
DOI: 10.1101/2022.11.06.22281991

Usability of the Virtual Supermarket Test for Older Adults with and without Cognitive Impairment

Auteurs: Stelios, Zygouris; Sofia, Segkouli; Andreas, Triantafyllidis; Dimitrios, Giakoumis; Magdalini, Tsolaki; Konstantinos, Votis; Dimitrios, Tzovaras
Publié dans: Journal of Alzheimer's Disease Reports, Numéro 1, 2022, ISSN 2542-4823
Éditeur: IOS Press
DOI: 10.3233/adr-210064

A comprehensive survey on deep facial expression recognition: challenges, applications, and future guidelines

Auteurs: Muhammad Sajjad, Fath U Min Ullah, Mohib Ullah, Georgia Christodoulou, Faouzi Alaya Cheikh, Mohammad Hijji, Khan Muhammad, Joel J.P.C. Rodrigues
Publié dans: Alexandria Engineering Journal, Numéro 68, 2023, Page(s) 817-840, ISSN 1110-0168
Éditeur: Alexandria University
DOI: 10.1016/j.aej.2023.01.017

Optimized efficient attention-based network for facial expressions analysis in neurological health care

Auteurs: Muhammad Munsif, Muhammad Sajjad, Mohib Ullah, Adane Nega Tarekegn, Faouzi Alaya Cheikh, Panagiotis Tsakanikas, Khan Muhammad
Publié dans: Computers in Biology and Medicine, Numéro Volume 179, 2024, Page(s) 108822, ISSN 0010-4825
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.compbiomed.2024.108822

InSEption: A Robust Mechanism for Predicting FoG Episodes in PD Patients

Auteurs: Dimitris Dimoudis; Nikos Tsolakis; Christoniki Magga-Nteve; Georgios Meditskos; Stefanos Vrochidis; Ioannis Kompatsiaris
Publié dans: Electronics, Numéro 12, 2023, ISSN 2079-9292
Éditeur: MDPI
DOI: 10.3390/electronics12092088

FoGGAN: Generating Realistic Parkinson’s Disease Freezing of Gait Data Using GANs

Auteurs: Nikolaos Peppes; Panagiotis Tsakanikas; Emmanouil Daskalakis; Theodoros Alexakis; Evgenia Adamopoulou; Konstantinos Demestichas
Publié dans: Crossref, Numéro 4, 2023, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s23198158

Ambiental Factors in Parkinson’s Disease Progression: A Systematic Review

Auteurs: Anastasia Bougea; Nikolas Papagiannakis; Athina-Maria Simitsi; Elpida Panagiotounakou; Chrysa Chrysovitsanou; Efthalia Angelopoulou; Christos Koros; Leonidas Stefanis
Publié dans: MEDICINA, Numéro 12, 2023, ISSN 1648-9144
Éditeur: MDPI
DOI: 10.3390/medicina59020294

Mobile App Interventions for Parkinson’s Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review

Auteurs: Andreas Triantafyllidis; Sofia Segkouli; Stelios Zygouris; Christina Michailidou; Konstantinos Avgerinakis; Evangelia Fappa; Sophia Vassiliades; Anastasia Bougea; Nikos Papagiannakis; Ioannis Katakis; Evangelos Mathioudis; Alexandru Sorici; Lidia Bajenaru; Valentina Tageo; Francesco Camonita; Christoniki Magga-Nteve; Stefanos Vrochidis; Ludovico Pedullà; Giampaolo Brichetto; Panagiotis Tsakanikas
Publié dans: Sensors, Numéro 6, 2023, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s23073396

Balancing between holistic and cumulative sentiment classification

Auteurs: Pantelis Agathangelou; Ioannis Katakis
Publié dans: Online Social Networks and Media, Numéro 8, 2022, ISSN 2468-6964
Éditeur: Elsevier
DOI: 10.1016/j.osnem.2022.100199

Towards Detecting Freezing of Gait Events Using Wearable Sensors and Genetic Programming.

Auteurs: Nega Tarekegn, A., Alaya Cheikh, F., Sajjad, M., Ullah, M.
Publié dans: Artificial Intelligence and Soft Computing. ICAISC 2023. Lecture Notes in Computer Science, Numéro 14125, 2023, ISBN 978-3-031-42505-9
Éditeur: Springer, Cham
DOI: 10.1007/978-3-031-42505-9_24

Deep learning based speech emotion recognition for Parkinson patient

Auteurs: Habib Khan and Mohib Ullah and Fadi Al-Machot and Faouzi Alaya Cheikh and Muhammad Sajjad
Publié dans: Electronic Imaging, Numéro 9, 2023
Éditeur: Society for Imaging Science and Technology
DOI: 10.2352/ei.2023.35.9.ipas-298

Ince-PD Model for Parkinson’s Disease Prediction Using MDS-UPDRS I & II and PDQ-8 Score

Auteurs: Nikos Tsolakis, Christoniki Maga-Nteve, Georgios Meditskos, Stefanos Vrochidis & Ioannis Kompatsiaris
Publié dans: Artificial Intelligence Applications and Innovations, 2023, Page(s) 267–278, ISBN 978-3-031-34111-3
Éditeur: Springer, Cham
DOI: 10.1007/978-3-031-34111-3_23

An Affective Multi-modal Conversational Agent for Non Intrusive Data Collection from Patients with Brain Diseases

Auteurs: Chloe Chira, Evangelos Mathioudis, Christina Michailidou, Pantelis Agathangelou, Georgia Christodoulou, Ioannis Katakis, Efstratios Kontopoulos, Konstantinos Avgerinakis
Publié dans: Chatbot Research and Design. CONVERSATIONS 2022. Lecture Notes in Computer Science, Numéro 13815, 2023, ISSN 1611-3349
Éditeur: Springer, Cham
DOI: 10.1007/978-3-031-25581-6_9

Enhancing Human Activity Recognition Through Sensor Fusion And Hybrid Deep Learning Model

Auteurs: A. N. Tarekegn, M. Ullah, F. A. Cheikh and M. Sajjad
Publié dans: 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), 2023, ISBN 979-8-3503-0261-5
Éditeur: IEEE
DOI: 10.1109/icasspw59220.2023.10193698

AI and IoT Enabled Sleep Stage Classification

Auteurs: Zografakis, D.; Tsakanikas, P.; Roussaki, I. and Giannakopoulou, K.
Publié dans: Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, Numéro 4, 2023, Page(s) 155-161, ISBN 978-989-758-631-6
Éditeur: Scitepress
DOI: 10.5220/0011631300003414

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