Data science team Konstantinidis Dimitrios CERTH Position Postdoctoral researcher What is your role in iPROLEPSIS? Researcher and technical developer What are your main activities in the project? I am mainly involved in the research activities of CERTH, concerning psoriatic nail detection and classification, range-of-motion assessment through the execution of active video tests and nutrition and physical activity recommendations. What is your motivation? I am deeply passionate about artificial intelligence and deep learning, with a strong interest in uncovering hidden patterns within data that can lead to highly accurate and reliable predictions. I find great satisfaction in developing advanced machine learning techniques to transform data into innovative solutions that contribute to real-world progress. Nikos Melanitis Ainigma Position Data Scientist What is your role in iPROLEPSIS? Data Scientist, Digital health and predictive modelling What are your main activities in the project? To design and implement novel approaches for improved management of PsA, through personalized models that warn patients for high risk of PsA exacerbation (flare). What is your motivation? To be part of the digital innovation in Health, enabling better disease management and personalised, precision medicine. Kosmas Dimitropoulos CERTH Position Principal Researcher (Researcher of Grade B’) What is your role in iPROLEPSIS? Principal Investigator for CERTH What are your main activities in the project? I am mainly involved in the research activities of CERTH, concerning psoriatic nail detection and classification, range-of-motion assessment through the execution of active video tests and nutrition and physical activity recommendations. What is your motivation? I am deeply motivated by the intersection of Artificial Intelligence and healthcare. I aspire to contribute to research that applies deep learning techniques to personalized medicine, enabling more accurate, data-driven, and patient-specific approaches to diagnosis and treatment. Eleni Vasileiou Signal Processing & Biomedical Technology Unit (SPBTU) – Aristotle University of Thessaloniki (AUTH) Position Research assistant working on digital health technologies and AI-enabled healthcare tools What is your role in iPROLEPSIS? AI Researcher & Data Scientist | Digital health and predictive modelling What are your main activities in the project? My main activities focus on developing digital, passively captured indicators that support risk prediction and monitoring models for psoriatic arthritis. I work on digital phenotyping of inflammatory symptoms with an emphasis on tracking motor manifestations using smart devices and wearables. This involves designing methods to analyze data from daily living activities – such as sleep, walking, and hand movements – to capture subtle physiological and behavioral changes associated with disease onset and progression. These efforts aim to identify key drivers of psoriatic arthritis and support personalized models for disease risk, progression prediction, and inflammation monitoring. What is your motivation? I am deeply motivated by the potential of digital health technologies to bring a more human and data-informed approach to healthcare. By combining AI with continuous, real-world data, we can reveal patterns often hidden in traditional clinical assessments. What drives me is the belief that these insights can empower both patients and clinicians to make earlier and more informed decisions, ultimately improving health outcomes and quality of life. My goal is to contribute to a future where technology enhances understanding, prevention, and personalized care for chronic conditions. Coordination Clinical Experts Data Science Software Development Ethics, Legal and Exploitation Dissemination and Communication

< BACK iPROLEPSIS presented at PhD DEI 2023 Nov 13, 2023 Highlights from PhD DEI 2023 Organised by the Universidade de Lisboa (the Instituto Superior Técnico), the PhD DEI 2023 event on 10 November 2023 served as a platform for introducing new PhD students to the Department of Engineering and Informatics (DEI). The event fostered an environment of knowledge-sharing and collaboration among students from the Doctoral Program in Computer Science and Engineering and the Doctoral Program in Digital Media. One of the standout presentations at PhD DEI 2023 was the poster presentation on the iPROLEPSIS Exergames. This presentation, delivered by Bárbara Ramalho, a PhD student from the FMH-ULisboa team, highlighted the general concepts and objectives of the iPROLEPSIS project. The iPROLEPSIS Exergames were developed through a co-design process, emphasizing collaborative and innovative approaches to game design aimed at promoting physical activity and health. Read more: We now know the audience's favorite posters from PhD DEI 2023! - Departamento de Engenharia Informática (DEI) ( ulisboa.pt ) 1/1 PREVIOUS NEXT

Ethics, legal and exploitation team Dr. Ioannis Drivas DIADIKASIA BUSINESS CONSULTING SYMVOULOI EPICHEIRISEON AE (DBC) Position Principal researcher focusing on the development of digital biomarkers and their translation into healthcare tools and interventions. What is your role in iPROLEPSIS? Project Manager What are your main activities in the project? As Project Manager, I coordinate all iPROLEPSIS-related activities assigned to DBC. What is your motivation? My motivation stems from a strong commitment to upholding ethical and legal standards in research while maximizing the impact and real-world use of the iPROLEPSIS results. Coordination Clinical Experts Data Science Software Development Ethics, Legal and Exploitation Dissemination and Communication

iProlepsis psoriatic arthritis project is a comprehensive multiscale model employing novel trustworthy AI-based analysis of multisource and heterogenous data. iPROLEPSIS project objectives and work packages Project aspires to shed light upon the health-to-PsA transition with a comprehensive multiscale / multifactorial PsA model employing novel trustworthy AI-based analysis of multisource and heterogenous (i.a., in-depth health, environmental, genetic, behavioral) data. Project objectives iPROLEPSIS consortium works on 7 ambitious key objectives in the field of Psoriatic Arthritis (PsA). PsA inflamation drivers Discover PsA inflammation drivers through AI-driven health, environmental and omics data mining. Role of mast cells Investigate the role of mast cells and features from non-invasive skin microvascular/joint imaging in inflammatory symptoms tracking. Personalised interventions Develop ICT-based personalised interventions to sustain or even improve quality-of-life. Co-creative ecosystem Co-create the iPROLEPSIS ecosystem with key stakeholders, following ethical, inclusive and trustworthy AI principles. Digital biomarkers Develop and validate objective digital biomarkers for tracking inflammatory symptoms and disease activity. Trustwothy AI models Build trustworthy AI models for personalised PsA risk prediction, early diagnosis and high disease activity prognosis. Digital health ecosystem Develop and clinically validate the iPROLEPSIS digital health ecosystem to empower persons with/at risk of PsA and healthcare professionals. Work packages The 6 Work Packages of the project will bring together various and complementary expertise from consortium partners. WP1 WP2 WP3 WP4 WP5 WP6 Work Package 1: Management and coordination WP1 is dedicated to project management and coordination aiming to enable a smooth project workflow; Ensure optimal contractual, administrative, financial, scientific, technical, IP and innovation management; Assure project quality and safeguard ethics, regulatory compliance and proper data management. Work Package 2: Knowledge mining, foundation and participatory design WP2 aims to create a foundational body of knowledge concerning PsA, associated conditions and inflammation; Identify, retrieve and curate datasets relevant to R&D activities of the project; Identify user needs and effectively engage with key stakeholders for steering research questions and co-creating the iPROLEPSIS digital care tools; Establish and monitor practices for ensuring adherence of iPROLEPSIS AI-driven components to trustworthy AI principles. Work Package 3: Research on PsA inflammation drivers and monitoring WP3 is dedicated to identify drivers related to PsA and associated inflammation leveraging new and existing multi-source health relevant data; Develop smartphone/wearable-based digital biomarkers (dBMs) for assessing PsA inflammatory symptoms; Shed light on changes in the joints and skin microvasculature related to PsA and the role of mast cells in associated inflammation; Through data fusion, develop a multiscale/multifactorial PsA model, emphasising on the prediction of the transition of high-risk individuals and PsO patients to PsA and of PsA patients to advanced inflammatory state. Work Package 4: Development of the iPROLEPSIS digital health ecosystem for personalised preventive care WP4 will technically specify the iPROLEPSIS ecosystem and set up a robust data management infrastructure and DevOps/MLOps platforms; Through an agile approach, develop the iPROLEPSIS minimum viable products (MVPs) for personalised PsA care including: 1) the patient app incorporating (dBM-based)PsA monitoring, knowledge, targeted interventions and tailored AI-driven lifestyle recommendations, 2) the serious gaming suite for health and wellness, 3) the app for HCPs allowing them to remotely monitor patients and view predictions on their course. Work Package 5: Clinical studies WP5 will develop the study protocols and carry out the process for their timely approval by concerned bodies; Set up a system for coordinating recruitment and efficiently managing clinical data and reporting; Organise and conduct four clinical studies: two multicentre prospective cohort studies for discovery and validation of PsA inflammation drivers and digital biomarkers, one observational study on PsA and changes in the joints and skin microvasculature, and one multicentre proof-of-concept randomised controlled trial (RCT) evaluating the effectiveness of the iPROLEPSIS digital care tools. Work Package 6: Dissemination, communication and exploitation WP6 will maximise visibility of the project and its outcomes and facilitate knowledge exchange while engaging a wide network of stakeholders; Develop PsA-related educational content; Set out a roadmap for regulatory approval of the iPROLEPSIS digital tools; Perform a thorough socio-economic/market analysis and develop concrete joint/individual exploitation plans. PROJECT VISION

< BACK World Psoriasis Day: iPROLEPSIS featured by HaDEA Oct 29, 2025 On World Psoriasis Day, the European Health and Digital Executive Agency (HaDEA) highlights how the iPROLEPSIS project is advancing early detection and personalised care for psoriatic arthritis Psoriatic arthritis (PsA) is a chronic inflammatory condition that can cause irreversible joint damage if left undiagnosed or untreated. To address this challenge, iPROLEPSIS is developing AI-driven predictive models and digital tools that help identify individuals at risk, enable earlier diagnosis, and support more personalised treatment pathways. In a recent interview with Prof. Leontios Hadjileontiadis , project coordinator, HaDEA explores how iPROLEPSIS brings together clinicians, researchers, and data scientists to transform psoriatic arthritis management across Europe. The discussion covers the project’s use of AI and biological data to build comprehensive patient profiles, its collaborative approach between dermatology and rheumatology, and the importance of EU funding and ethical, cross-border cooperation in enabling innovation. Read the full article on HaDEA’s website: https://hadea.ec.europa.eu/news/world-psoriasis-day-exploration-how-horizon-europe-project-improving-early-detection-psoriatic-2025-10-29_en World Psoriasis Day 2025.png World Psoriasis Day 2025.png 1/1 PREVIOUS NEXT

Coordination team Vasilis Charisis Signal Processing & Biomedical Technology Unit (SPBTU) – Aristotle University of Thessaloniki Position Principal researcher focusing on the development of digital biomarkers and their translation into healthcare tools and interventions. What is your role in iPROLEPSIS? Scientific and Technical Coordinator. What are your main activities in the project? I manage the project's day-to-day operations and scientific coherence, driving the timely delivery of outcomes. Our team (SPBTU) is pioneering the use of AI and digital biomarkers from everyday smart devices to create predictive models for PsA symptoms. We are also developing a dedicated mobile app that supports patients by improving sleep patterns using binaural beat technology. What is your motivation? My motivation is rooted in a long-standing commitment to improving chronic disease management through accessible, non-invasive technology. In iPROLEPSIS, I am driven to apply advanced AI and biomedical engineering principles to address the significant challenges faced by PsA patients. We aim to create tangible, personalized digital tools that not only predict disease flares early but actively enhance patients' quality of life, ensuring our cutting-edge research delivers real clinical benefits. Coordination Clinical Experts Data Science Software Development Ethics, Legal and Exploitation Dissemination and Communication

< BACK "The Kite" Breathing Serious Game: Agile Co-Design for Psoriatic Arthritis Jul 31, 2024 Enhancing PsA Management through Innovative Breathing Exercises and Game-Based Therapy Latest research initiative under the iPROLEPSIS project: “The Kite” Breathing Serious Game: Agile Co-Design for Psoriatic Arthritis presented at IEEE MELECON 2024. This study is part of a broader effort to develop and validate innovative digital biomarkers for managing Psoriatic Arthritis (PsA) through the Artificial Intelligence-Personalised Game Suite (AI-PGS). Abstract: Serious Games (SGs) have the potential to provide clinical care and enhance patients’ quality of life, while incorporating an element of entertainment. As part of the iPROLEPSIS Horizon Europe project, we introduce two Sensorimotor Art games designed as SGs to assist Psoriatic Arthritis (PsA) patients in managing their symptoms. These SGs provide a platform for self-expression and pain relief through engaging in rhythmic puzzle activities. The co-design process for the proposed Sensorimotor Art games followed an agile methodology, involving 14 experts (including clinicians, researchers, and game developers), to gather feedback on game requirements, storyboards, and mechanics. From the thematic analysis of the transcribed discussion, four main themes emerged, namely: Clinical value (Theme 1), Motor skills and adaptation (Theme 2), Creative engagement (Theme 3), and Feedback and future directions (Theme 4). Clinical value underlines the therapeutic benefits of Sensorimotor Art games for pain distraction and emotional well-being. Motor skills and adaptation focus on hand/finger use and adapting games for older patients. Creative engagement emphasizes fostering creativity, a positive environment, and goal achievement. Finally, feedback and future directions highlight the importance of continuous feedback and occupational therapists’ involvement in coming sessions. The development of Sensorimotor Art games lays the groundwork for digital interventions to alleviate psychological distress and improve fine motor symptoms in PsA patients. At the same time, these SGs can also provide insights to healthcare providers and policymakers for developing future digital solutions tailored to PsA patients. Read the full publication: https://zenodo.org/records/13141465 IEEE_MELECON_2024 .pdf Download PDF • 1.33MB 1/1 PREVIOUS NEXT

< BACK iPROLEPSIS Newsletter No. 5 Jul 10, 2024 Discover Insights from Clinicians, Collaborative Efforts, and Key Events Welcome to the fifth edition of the iPROLEPSIS project newsletter. In this issue, we bring you insightful interviews with clinicians specialising in psoriatic arthritis, insights into recent clustering and networking activities, and reflections on key past events. iPROLEPSIS_Newsletter No. 5 .pdf Download PDF • 8.01MB 1/1 PREVIOUS NEXT

< BACK iPROLEPSIS Newsletter No. 8 Apr 28, 2025 Latest News from iPROLEPSIS Welcome to the eighth edition of the iPROLEPSIS newsletter, where we share the latest updates and progress from the project. iPROLEPSIS project newsletter Issue No. 8_Apr 2025 .pdf Download PDF • 3.38MB 1/1 PREVIOUS NEXT

Learning Hub Explore resources to help you understand and manage psoriatic arthritis. Learning hub Key Facts Handbook News Feed Quizzes Search How is psoriatic arthritis diagnosed? See related Handbook section PREVIOUS NEXT

< BACK iPROLEPSIS Innovative Federated Learning Approach at IEEE IST 2023 Oct 23, 2023 Enhancing Federated Learning Through Advanced Weight Distribution Analysis IEEE International Conference on Imaging Systems and Techniques (IST) conference served as a platform for presenting iPROLEPSIS research in federated learning, specifically focusing on novel methods for weight aggregation. Title: Federated Learning Aggregation based on Weight Distribution Analysis Abstract: Federated learning has recently been proposed as a solution to the problem of using private or sensitive data for training a central deep model, without exchanging the local data. In federated learning, local models are trained on the client side using the available data, while a server is responsible for aggregating the weights of these models into a global model. However, the traditional weight averaging approach does not take into consideration the importance of the different weights for the performance of a model. To this end, this work proposes a novel federated learning weight aggregation method that estimates the statistical distance of each client's parameters from the Gaussianity, and weighs the contribution of each client to the global model accordingly so that the most significant information is retained and enhanced. To create an accurate global model, a complex weighted averaging of the parameters of clients' models at the layer level is performed, considering as low quality the parameters following the Gaussian distribution. The proposed method can be employed to both convolutional and linear layers and it is based on the notion that parameters following a Gaussian distribution do not significantly affect the output of a model. Experiments with different network architectures and a comparison with a plethora of state-of-the-art approaches on three well-known image classification datasets demonstrate the superiority of the proposed method for federated learning weight aggregation. Read the full publication here: (PDF) Federated Learning Aggregation based on Weight Distribution Analysis ( researchgate.net ) https://ieeexplore.ieee.org/document/10355708 1/1 PREVIOUS NEXT

< BACK Europe Day 2024 May 9, 2024 Celebrating Europe Day with iPROLEPSIS sister projects Happy Europe Day 2024! Today we celebrate unity in diversity, innovation and collaboration across the continent. As projects funded under the same Horizon Europe call topic: "Personalised blueprint of chronic inflammation in health-to-disease transition", we're proud to contribute to the common goals of understanding the risk factors that trigger the transition from health to disease, providing personalised prevention measures and reducing the burden of chronic diseases. Within iPROLEPSIS , we aim to develop a suite of digital health tools designed to detect early transitions to psoriatic arthritis, predict flares for timely intervention, and provide personalised recommendations and interventions for managing the disease. With our unique consortium of 15 partners from 9 countries, we are strengthening international and cross-border collaboration to advance research, technology and health progress in Europe and beyond. Join us in commemorating this special day by exploring the impactful work of our sister projects: GlycanTrigger , ENDOTARGET , IMMEDIATE , miGut-Health , AIDA EU project , PREVALUNG EU , PRAESIIDIUM , CARE-IN-HEALTH , Intercept-T2D , INITIALISE , Halt-RONIN , Together, we're shaping a brighter, more inclusive, and sustainable Europe through groundbreaking research and cross-border connections. Europe Day sister projects .png Europe Day sister projects .png 1/1 PREVIOUS NEXT