Beyond Noise: Generative AI-Powered Signal Processing for Accurate and Reliable Sensing
TOMOAKI OTSUKI*, Miao Pan, Mondher Bouazizi
This half-day workshop is organized and provided by the EMBS Biomedical Signal processing Technical Committee and is geared toward undergraduate/graduate students and early PhD students entering the field of biomedical signal processing. We draw from our collective teaching experience and research interests to convey fundamental signal processing, modeling, and exemplary biomedical applications. In particular, the workshop includes lectures on time-frequency analysis, higher-order (bispectral) analysis, real-time EEG signal processing, multivariate biosignal analysis, and complexity analysis. Speakers list and tentative agenda follow below.
Exploring Wearable EEG & BCI: Applications in Health, Cognitive Performance, and Neurofeedback
Leonhard Schreiner*
The objective of the workshop is to educate the audience on technological developments in various preclinical and clinical neuroimaging applications. This workshop will elaborate on neuroimaging aspects using structural magnetic resonance imaging (MRI), functional MRI, and emerging optoacoustic imaging methods. In part-1, we will focus on the analysis of structural and functional MRI for clinical applications: (i) for structural MRI, the talk will focus on extraction of early neuroimaging biomarkers for vascular cognitive impairment, (ii) for fMRI, the focus will be on phenomenological models of brain activity to capture brain dynamics in electrophysiological data, including methods to link these dynamics to behaviour in a streamlined fashion. In part-2, we will introduce optoacoustic physics and associated image formation/analysis methods. This part will also expand on different optoacoustic molecular imaging biomarkers (both endogeneous and exogeneous) relevant for brain imaging. Next, we will elaborate on the use of optoacoustics for amyloid-beta deposit imaging in Alzheimer’s disease and dynamic cerbro-vascular imaging. Lastly, first in-human optoacoustic brain imaging results will be presented. Our workshop will also aim to provide an interactive and hands-on experience via software tools and interactive coding sessions, thereby enabling practical engagement for participants on brain MR image analysis and optoacoustic reconstruction.
Foundational frameworks in Biomedical Signal Processing
Gaetano Valenza*, Sridhar Krishnan
THIS WORKSHOP AIMS TO ENGAGE PARTICIPANTS IN EXPLORING KEY THEMES SURROUNDING DIVERSITY, EQUITY, AND INCLUSIVENESS (DEI), DATA REPRESENTATIVITY, AND FAIRNESS IN HEALTHCARE RESEARCH. IT WILL HIGHLIGHT THE PIVOTAL ROLE OF THE EUROPEAN OPEN SCIENCE CLOUD (EOSC) IN PROMOTING OPEN AND EQUITABLE HEALTHCARE INNOVATION. THROUGH A COMBINATION OF KEYNOTE PRESENTATIONS, PANEL DISCUSSIONS, AND INTERACTIVE SESSIONS, ATTENDEES WILL GAIN INSIGHTS INTO FOSTERING INCLUSIVE ENVIRONMENTS, ENSURING DIVERSE DATA REPRESENTATION, AND ACHIEVING FAIRNESS IN HEALTHCARE DATA. BY THE END OF THE WORKSHOP, PARTICIPANTS WILL BE EQUIPPED WITH STRATEGIES TO INTEGRATE DEI PRINCIPLES INTO THEIR WORK, LEVERAGE THE EOSC FOR ENHANCED DATA SHARING AND COLLABORATION, AND CONTRIBUTE TO MORE EQUITABLE HEALTHCARE INNOVATIONS. THE WORKSHOP WILL FEATURE A COMBINATION OF KEYNOTE PRESENTATIONS, PANEL DISCUSSIONS, INTERACTIVE SESSIONS, AND GROUP ACTIVITIES. PARTICIPANTS WILL HAVE AMPLE OPPORTUNITIES TO NETWORK AND COLLABORATE ON PROJECTS AIMED AT PROMOTING EQUITY IN HEALTHCARE THROUGH TRANSLATIONAL ENGINEERING. BY THE END OF THE WORKSHOP, PARTICIPANTS WILL HAVE A COMPREHENSIVE UNDERSTANDING OF HOW TO INTEGRATE DEI PRINCIPLES, ENSURE DATA REPRESENTATIVITY, MAINTAIN FAIRNESS, AND LEVERAGE THE EOSC TO ADVANCE EQUITABLE HEALTHCARE INNOVATIONS. PROPOSED TALKS: 1) “THE POWER OF DEI: TRANSFORMING HEALTHCARE.2) INNOVATION FOR THE BETTER”, 3) “FROM BIAS TO FAIRNESS: TECHNIQUES FOR ENSURING, 4) REPRESENTATIVITY IN HEALTHCARE DATA”, 5) “BRIDGING GAPS: LEVERAGING THE EUROPEAN OPEN, 6) SCIENCE CLOUD FOR INCLUSIVE HEALTHCARE RESEARCH” (STEFANO DICIOTTI, UNIVERSITY OF BOLOGNA), 7) “ETHICAL DATA USAGE: NAVIGATING CHALLENGES IN ENSURING FAIRNESS AND EQUITY”
Exploring Altered States of Consciousness Through EEG and Brain-Computer Interfaces
Sébastien Rimbert*, Laurent Bougrain, Jérémie Mattout
This workshop will focus on the neural mechanisms underlying altered states of consciousness, exploring findings from both classical EEG methods and advanced brain-computer interfaces (BCIs). By addressing conditions such as general anesthesia, locked-in syndrome, disorders of consciousness, and states induced by hypnosis or pharmacological agents, the complementary talks aim to highlight the neuronal processes driving these states and their implications for both basic neuroscience and clinical practice. The workshop will feature six expert speakers who will present recent advances in EEG-based techniques for monitoring awareness during anesthesia, detecting neural signatures of response attempts in locked-in patients, patients with disorders of consciousness or other altered states. The workshop will also address technical challenges such as reliable signal acquisition, data interpretation in different clinical and experimental settings, and the integration of classical and innovative methods. Designed for researchers, clinicians and engineers in neuroscience, neurotechnology and related disciplines, this half-day workshop provides an interdisciplinary platform to discuss the opportunities and challenges of using EEG and BCI technologies. Participants will gain a deeper understanding of consciousness research and its potential to improve both scientific knowledge and patients’ outcomes.
Large animal models in neural engineering /neuroprosthetics
Suzan Meijs*, Benjamin William Metcalfe, Leen Jabban, Thomas Guiho
The use of large animal models has become increasingly important in recent years, particularly in the field of neuroprosthetics. Whether using electrostimulation to explore the nervous system or to assess new approaches of functional rehabilitation, intermediate models speed up the transfer of results to humans. As the size and geometry of the medical devices are thought for implantation in humans, EU regulations implicitly suggest the use of large animals for preclinical validation phases (2017/745 Regulation on medical devices). However, large animal models are often seen as comparatively costly, complex, and ethically challenging when compared t o rodent alternatives. In this workshop we will challenge these assumptions by demonstrating the potential for in-vivo, ex-vivo, and in-vitro preparations in the context of peripheral nerve, spinal cord and cortical interfaces showing the different ways in which cost, complexity, and ethical challenges can be balanced. We will discuss acute and chronic implantation and illustrate practical examples of all cases.
Neurodegeneration studies with MRI and Optoacoustics
Vaanathi Sundaresan*, Jaya Prakash
The rapid expansion of biomedical data from diverse sources presents opportunities to advance healthcare and precision medicine through multimodal AI. Between 2021 and 2024, the increasing number of EMBC papers featuring “multimodal” in their abstracts reflects a growing research trend. Open-source, accessible, reusable, and reproducible tools enable the EMBS and broader research community to build on state-of-the-art developments efficiently and accelerate innovation. This workshop will equip attendees with the knowledge, skills, and tools required to address multimodal AI challenges while promoting open research. The first part of the workshop will focus on open research practices. Participants will engage in interactive Python tutorials using PyKale, a PyTorch-based library for multimodal and transfer learning. These tutorials will ntroduce essential skills, including version control, automated testing, and configuration management while promoting a standardised pipeline in PyKale: data loading, preprocessing, embedding, prediction, evaluation, and interpretation. The second part will explore multimodal AI techniques for biomedical data analysis, focusing on domain adaptation and multimodal fusion. Participants will work in groups based on their preferences in real-world applications, including cardiovascular disease assessment, brain disorder diagnosis, cancer classification, and drug-target prediction. All examples will follow a standardised file and directory structure, using the pipeline introduced earlier. To ensure hands-on experimentation and collaborative learning, public medical imaging, omics, and molecular datasets such as MIMIC, ABIDE, ROSMAP, BRCA, BindingDB, and BioSNAP will be used. Organisers and speakers will be available to answer questions. Led by the leading experts in multimodal AI and creators of PyKale, this workshop will be highly valuable for researchers and practitioners. Bring a laptop to participate fully.
Wearables for eHealth and Wellness: from research and innovation to clinical translation
Mariangela Filosa*, Calogero Maria Oddo, Bjoern M Eskofier
Vascular diseases remain a leading cause of mortality worldwide, emphasizing the need for innovative diagnostic and treatment methods. Minimally invasive endovascular interventions, such as aneurysm repair, stent placement, and drug delivery, offer faster recovery and reduced mortality compared to open surgeries. However, challenges like radiation exposure, limited 3D imaging for cannulation tasks, and lack of assistive features persist. Robot-assisted technologies, including steerable catheters and guidewires, have emerged as transformative solutions, improving precision, stability, and access to complex anatomies. This workshop will explore clinical opportunities, technical requirements, and transaltional challenges in robot-assisted endovascular interventions. Structured into four sessions—Clinical Perspectives, Navigation Strategies, Technical Challenges and Translational Pathways, and Regulatory Process and Clinical Translation—it features invited talks, panel discussions, and opportunities for early-stage researchers to present. Key topics include robotic sensing, actuation, human-machine interfaces, control strategies, and regulatory hurdles. Through this structure, the workshop aims to foster interdisciplinary collaboration and knowledge exchange among researchers, clinicians, and industry and regulatory professionals, offering an interactive platform to address current limitations and critical challenges and inspire innovation in robotic endovascular systems. Attendees will gain insights into cutting-edge developments and engage in discussions to shape the future of this transformative field.
NeuroWearX for Smart Aging: Developing Next Generation Wearable AgeTech for Our Parents, Elderly Loved Ones, and Our Future Selves
Ker-Jiun Wang*, Ramana Vinjamuri, Zhi-Hong Mao, Midori Sugaya, Jun Ueda
AI is becoming an integral component of translational cutting-edge research for healthcare applications. As the use of AI in clinical decision-making is becoming more prevalent, these decisions do have significant moral and ethical implications, potentially exacerbating existing health disparities. Despite this, ethics is often an afterthought in model development process, a practice that is at odds with the fundamental principle of medicine: to do no harm. Ethical AI ought to be fundamental in AI healthcare applications. The main aim of this workshop is to equip AI practitioners in positioning foundational ethics as an integral part of model development process,rather than a quality that models are evaluated on post-hoc. We will address current technical challenges inembedding ethical principles into the very genesis of human-centric model development, representing a paradigm shift from measuring and mitigating impacts to preventing them by leveraging trustworthy AI. We will discuss how to practically integrate ethics in research proposal and conceptualization. A key aim of our workshop is to present an international multi-faceted approach to reviewing/understanding ‘explainable AI’ from an ethics point of view, and aid our audience to shape them under that lens as we highlight the ethical challenges that arises from these. Hence, the format will consist of (a) lighting talks from experts (Drs. Crockett, Alonso-moral, Latham, and Obafemi-Ajayi) in the field; (b) interactive small group activities with hands-on exercises (facilitated by Drs. Obafemi-Ajayi & Crockett) to encourage attendees to apply ideas from the talks to model development scenarios. We will present a structured holistic overview of ethical AI model development in healthcare from various perspectives including philosophy, bioethics, andinformatics. The workshop format balances interdisciplinary dialogue with experiential learning through case study group exercises.
Innovative Health and Medical Technologies in the AI Era
LI LI*, Hairong zheng, Kang Ping Lin, Leandro Pecchia, Chengyu Liu, Giuseppe Fico
Rationale: Artificial intelligence (AI) technologies are advancing ata rapid pace, and their integration into biomedical data analysis holds significant promise for enhancing accuracy, efficiency, and automation. The demand for advanced techniques in predictive diagnosis, early disease detection, and personalized treatment pathways in healthcare and AI industries is growing steadily. Summary: Researchers can leverage AI to extract valuable insights from biomedical data, enabling more accurate diagnostics, personalized monitoring, and effective treatment strategies.This session explores the potential of AI algorithms, including machine learning and deep learning, to enhance biomedical signal and image interpretation. We will discuss techniques for reducing computational complexity without compromising the performance of AI models. By the end of the workshop, participants will have a comprehensive understanding of the techniques and tools necessary to implement and optimize AI-driven biomedical signal and image processing for deployment in healthcare, fitness, and biomedical research. During an interactive session, participants will explore the following topics: -Introduction to tools used for AI-based signal processing. Detection of seizure in EEG using a time-frequency-based convolutional neural network Classification of brain MRI using deep learning. Optimization of signal source separation algorithm using convolution neural network We invite EMBC2025 attendees to join experienced researchers in this half-day workshop to explore cutting-edge techniques and discover practical tools and valuable tips for navigating the world of biomedical data analysis and AI. The workshop is suitable for individuals with all levels of experience in data processing. While no prior knowledge is required, experienced users will benefit from the introduction of new tools, tips, and tricks for applying advanced techniques to biomedical data.
Design and Assessment Wearable Robotics (DAWR) – Bridging the Gap Between Existing and Desired Evaluation Outcomes
Maria Lazzaroni*, Jesús Ortiz, Chiara Lambranzi, Nicholas Cartocci, David Beckwée, Shaoping Bai
Evaluating wearable devices, such as exoskeletons, is essential to determine their effectiveness. However, there is currently no standardized approach to this process, and professionals from various disciplines often struggle to communicate due to the differing metrics they use. This workshop aims to bring together individuals involved in the evaluation and design of exoskeletons and wearable devices, as well as stakeholders, across their entire lifecycle – from conceptualization to application. It highlights the importance of evaluating these technologies from multiple perspectives, including those of developers and end users, to ensure they deliver meaningful benefits. Evaluation is a cornerstone of the iterative design process, aligning the expectations and outputs of diverse stakeholders and helping the designers create user-centered solutions that fit end users’ needs. We have invited six speakers representing clinical and industrial perspectives, including evaluators, designers and end-users. Participants will discuss desired validation outcomes, explore how others’ outputs can contribute to their goals, and identify gaps between existing and needed outputs. This collaborative effort aims to close the loop by addressing these gaps and fostering innovation. The workshop will feature a live demonstration of two exoskeletons: an industrial model and a clinical one. This hands-on session encourages real-time engagement, with participants exploring how theoretical concepts translate into practical applications. The workshop is ideal for professionals involved in the design and evaluation of wearable technologies, not just exoskeletons, who currently have limited interaction with other disciplines. Attendees will gain valuable insights, learn to navigate cross-disciplinary challenges and contribute to creating more effective and user-centered technologies. The session would also have a call for abstracts to encourage participation and dialogue with the participants.
Navigating the MDR for a scientist
Sadaf Salamzadeh, Lejla Alic*
WITH THE RAPID DEVELOPMENT OF INTELLIGENT SYSTEMS, AI IS PLAYING A CRUCIAL ROLE IN ENHANCING CLINICAL DECISION-MAKING, DISEASE DETECTION, AND PROMOTING INDEPENDENT LIVING AMONG AGING POPULATIONS. THIS WORKSHOP WILL FEATURE EXPERT SPEAKERS DISCUSSING CUTTING-EDGE APPLICATIONS, RANGING FROM THE USE OF WEARABLE DEVICES FOR DIAGNOSIS AND ETHICAL AI IN CLINICAL DECISION-MAKING TO THE ROLE OF DIGITAL HEALTH SOLUTIONS IN PROMOTING HEALTHY AGING AND INDEPENDENCE. WE WILL EXPLORE A RANGE OF APPLICATIONS, FROM TRADITIONAL MACHINE LEARNING APPROACHES TO CUTTING-EDGE DEEP LEARNING TECHNIQUES, LLMS, AND FOUNDATION MODELS. DURING AN INTERACTIVE SESSION, PARTICIPANTS WILL EXPLORE REAL-WORLD PRACTICAL SCENARIOS, INCLUDING EXPLORING THE ROLE OF WEARABLE DEVICES IN DETECTING COMMON INFECTIONS, AND GAIN INSIGHTS INTO SCALING WEARABLE SENSING FOUNDATION MODELS FOR PERSONALIZED AND SCALABLE HEALTH MONITORING. THEY WILL GAIN INSIGHTS INTO THE CRITICAL CONSIDERATIONS OF DEPLOYING TECHNOLOGY AND RESPONSIBLE AI TO SUPPORT THE NEEDS OF THE AGING POPULATION, WHICH IS GROWING EXPONENTIALLY WORLDWIDE. THE WORKSHOP WILL ALSO COVER THE INTEGRATION OF LARGE LANGUAGE MODELS TO DESIGN INTELLIGENT HEALTH AGENTS, OFFERING A COGNITIVE EDGE IN DELIVERING TAILORED HEALTH GUIDANCE AND DECISION SUPPORT. LED BY EXPERIENCED AI RESEARCHERS FROM BOTH ACADEMIA AND INDUSTRY, THIS WORKSHOP OFFERS A UNIQUE OPPORTUNITY TO BE AT THE FOREFRONT OF AI INNOVATION IN HEALTHCARE. WHILE THE WORKSHOP HAS BEEN DESIGNED FOR INDIVIDUALS AT ALL EXPERIENCE LEVELS, IT WELCOMES NEWCOMERS WITHOUT PRIOR KNOWLEDGE WHILE OFFERING VALUABLE INSIGHTS TO EXPERIENCED PARTICIPANTS. EXPERTS WILL BENEFIT FROM LEARNING ABOUT THE LATEST TOOLS, TIPS, AND STRATEGIES FOR APPLYING CUTTING-EDGE AI TECHNIQUES TO REAL-WORLD HEALTH APPLICATIONS. FINALLY, ATTENDEES WILL LEAVE WITH ACTIONABLE KNOWLEDGE AND A DEEPER UNDERSTANDING OF HOW AI AND DIGITAL HEALTH TECHNOLOGIES ARE REVOLUTIONIZING PATIENT OUTCOMES AND CARE STRATEGIES
Federated Learning with CAFEIN for TRUSTroke: From Theoretical Insights to Real-World Use Cases
Diogo Reis Santos*, Sara Zullino, Michele Carminati, Carolina Migliorelli, Alessandro Redondi, Marco Di Gennaro
Federated learning (FL) has emerged as a transformative paradigm for securely integrating and analyzing sensitive, heterogeneous datasets distributed across multiple institutions. It is particularly well-suited for biomedical applications, where data governance, privacy, ownership, and regulatory considerations are paramount. This workshop provides a comprehensive, cross-domain overview of federated data harmonization, federated analytics, federated training, and relevant regulation using the CAFEIN federated learning platform and the TRUSTroke project as a central case study. We will examine how these approaches streamline multi-center collaborations while respecting data privacy, proprietary constraints, and evolving regulatory requirements. The workshop will cover prerequisites for data harmonization, emphasizing the importance of FAIR (Findable, Accessible, Interoperable, and Reusable) data practices across multiple centers. We will discuss essential data exploration steps for preparing datasets for machine learning using federated analytics and differential privacy. We will also delve into the training of federated models, including tree-based and deep learning approaches, while addressing current techniques, limitations, and considerations for network and model security within a federated platform. Participants will learn how CAFEIN’s scalable,privacy-preserving infrastructure supports real-world applications in TRUSTroke, a European artificial intelligence project aimed at optimizing stroke treatment. We will also explore additional use cases, such as enhancing cancer risk prediction, improving medical supply chain logistics, detecting atrial fibrillation, and analyzing brain tumor MRI. Finally, we will address the pressing need to understand, comply with, and prepare for the current regulatory environment surrounding medical AI.
Fostering Diversity, Equity, and Inclusiveness in Healthcare Innovation: Leveraging the European Open Science Cloud for Equitable Biomedical Engineering (Part 2)
Stefano Diciotti*, Matteo Lai, Luca Gilli, Shalini Kurapati, Giulia Raffaella De Luca
Generative AI is rapidly transforming healthcare by enabling automated documentation, enhancing clinical decision support, and improving patient engagement. However, challenges such as model reliability, ethical considerations, and regulatory compliance must be addressed to ensure safe and effective implementation. This workshop aligns with the EMBS mission by providing a comprehensive look at cutting-edge AI technologies in clinical practice. By bringing together experts from medicine, pharmacy, and AI, the workshop fosters interdisciplinary collaboration and equips attendees with actionable skills to implement AI-driven solutions responsibly. The workshop provides an in-depth exploration of Generative AI in clinical applications, focusing on its benefits, challenges, and best practices for integration into healthcare workflows. Attendees will gain practical insights into natural language processing for electronic health records, prompt engineering for large language models (LLMs), and effective implementation strategies. Through hands-on demonstrations and interactive discussions, participants will learn how to optimize AI-generated content for accuracy and clinical relevance. The workshop is designed for healthcare professionals, researchers, and AI developers aiming to harness Generative AI for improving patient care and decision-making
Advances in Generative AI for Clinical Applications
Khanita Duangchaemkarn*, Chiraphat Boonnag
The rapid proliferation of low-cost sensors and ambient sensing technologies has enabled novel applications in healthcare, smart environments, and human activity recognition. However, many of these devices suffer from hardware limitations, leading to high noise levels, signal distortions, and inconsistencies in data quality. Additionally, ambient sensing methods, such as WiFi-based activity recognition and remote vital sign monitoring, are highly susceptible to interference and environmental disturbances, significantly degrading sensing accuracy and reliability. This workshop explores how Generative AI, Large Language Models (LLMs), and diffusion models can address these challenges by learning the underlying structure of signals and reconstructing clean, reliable data from noisy, incomplete, or distorted inputs. By applying deep learning-based denoising, signal enhancement, and cross-modal AI techniques, we can develop intelligent, self-correcting sensing systems that compensate forhardware imperfections and environmental noise. Attendees will gain insights into cutting-edge AI techniques for sensor data reconstruction, signal restoration, and adaptive noise filtering, fostering interdisciplinary collaboration between AI researchers, signal processing experts, and biomedical engineers. This workshop fosters interdisciplinary collaboration between AI researchers, signal processing experts, and biomedical engineers, driving the development of more robust, AI-powered sensing technologies that enhance the accuracy and reliability of ambient and non-invasive monitoring systems.
Open Biomedical Multimodal AI Research: From Pixels to Molecules
Shuo Zhou*, Haiping Lu, Tingting Zhu, Peter Charlton, Xianyuan Liu, Peizhen Bai, Sina Tabakhi
WEARABLE EEG AND BCI SYSTEMS ARE TRANSFORMING HOW WE ASSESS BRAIN FUNCTION, OFFERING NEW OPPORTUNITIES IN HEALTH MONITORING, COGNITIVE PERFORMANCE EVALUATION, AND NEUROFEEDBACK APPLICATIONS. AS THESE TECHNOLOGIES BECOME MORE ACCESSIBLE, RESEARCHERS AND PRACTITIONERS CAN INTEGRATE THEM INTO REAL-WORLD SCENARIOS, FROM MENTAL HEALTH ASSESSMENTS TO NEUROREHABILITATION AND HUMAN-MACHINE INTERACTION. THIS WORKSHOP EXPLORES THE LATEST ADVANCEMENTS IN EEG-BASED NEUROTECHNOLOGIES, DEMONSTRATING HOW WEARABLE SYSTEMS CAN BE USED FOR COGNITIVE WORKLOAD TRACKING, NEUROFEEDBACK TRAINING, AND DEVELOPING EEG BIOMARKERS FOR NEUROLOGICAL CONDITIONS. PARTICIPANTS WILL EXPLORE LOW-CHANNEL / DRY ELECTRODE EEG DEVICES HANDS-ON, LEARNING HOW TO SET UP, ACQUIRE, AND ANALYZE BRAIN ACTIVITY DATA USING VARIOUS SOFTWARE TOOLS, INCLUDING PYTHON-BASED PLATFORMS AND OTHER WIDELY USED EEG PROCESSING ENVIRONMENTS. THE WORKSHOP WILL PROVIDE EXPERT INSIGHTS AND INTERACTIVE EXERCISES, ALLOWING ATTENDEES TO WORK DIRECTLY WITH EEG SIGNALS, PREPROCESS DATA, AND EXPLORE REAL-TIME APPLICATIONS SUCH AS DETECTING MENTAL STATES AND MONITORING NEUROPHYSIOLOGICAL RESPONSES. THE WORKSHOP WILL FEATURE DISCUSSIONS ON EMERGING TRENDS IN EEG AND BCI RESEARCH, INCLUDING THEIR INTEGRATION WITH VIRTUAL ENVIRONMENTS, GAMIFICATION TECHNIQUES, AND NEUROADAPTIVE SYSTEMS. ADDITIONALLY, THE ROLE OF EEG-BASED BIOMARKERS IN COGNITIVE HEALTH AND NEUROMODULATION WILL BE EXPLORED, HIGHLIGHTING THEIR POTENTIAL FOR IMPROVING DIAGNOSIS AND TREATMENT STRATEGIES IN NEUROLOGICAL DISORDERS. DESIGNED FOR RESEARCHERS, ENGINEERS, AND PROFESSIONALS IN NEUROSCIENCE, BIOMEDICAL ENGINEERING, AND RELATED FIELDS, THIS WORKSHOP OFFERS AN INTERACTIVE AND PRACTICAL INTRODUCTION TO WEARABLE EEG AND BCI APPLICATIONS. NO PRIOR EXPERIENCE IS REQUIRED, BUT ATTENDEES WITH A BACKGROUND IN SIGNAL PROCESSING OR NEUROSCIENCE WILL BENEFIT FROM ADVANCED DEMONSTRATIONS AND TOOL INTEGRATIONS.
Ethical Foundations of AI in Healthcare: Methodical Approaches to Addressing Technical Challenges and Implementing Effective Solutions
Tayo Obafemi-ajayi*
The ongoing digital revolution is redefining the landscape of healthcare, surpassing the constraints of traditional approaches and unlocking new paradigms for personalized health management. This transformation is driven by the convergence of rapid technological advancements, including miniaturized electronics, cutting-edge sensors, and the seamless integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies. At the forefront of this evolution, wearable devices are emerging as pivotal enablers of real-time, user-friendly health monitoring,f ostering a more proactive and data-driven healthcare ecosystem. Despite their growing popularity, most wearable technologies remain confined to consumer markets, primarily serving fitness and activity-tracking purposes. However, their full potential extends far beyond, holding the promise of revolutionizing clinical practice and wellness monitoring. The transition of wearables from lifestyle gadgets to clinically validated tools can facilitate the systematic deployment of eHealth strategies, enabling continuous and remote health monitoring, early detection of anomalies, and timely, personalized interventions. This workshop will explore the latest advancements and challenges in wearable technologies, bridging the gap between research, industrial innovation, and clinical adoption. Starting with cutting-edge research on novel technological and methodological solutions, we will transition to industrial perspectives, addressing the critical aspects of Lab to Market strategies. Additionally, the workshop will highlight the clinical significance of wearables within the eHealth framework, emphasizing their role in the 5P approach to medicine and their potential impact on healthcare system management. Experts from each field will discuss with the attendees throughout this journey into the ongoing major changes of health and wellness enabled by wearables.
Innovation Across Scales in Neural Engineering: from Basic Research to Market Transformation
Michela Chiappalone, Jose del R. Millan, Gert Cauwenberghs, Erika Ross Ellison, Metin Akay, Paul Sajda
This workshop will explore innovation in neural engineering across different levels, spanning from fundamental research to applied and clinical advancements. We will start by emphasizing the critical role of basic and applied research in shaping new, low
Technology Readiness Level (TRL) technologies, and discuss how even early-stage research holds immense potential for disruptive breakthroughs, despite the extended timelines needed for market realization. We will then continue by introducing medium to high TRL research and technologies, which are closer to real-world application and/or currently undergoing clinical trials. Additionally, we will showcase recent market-ready products that have emerged from advancements in the neural engineering field, highlighting the strategies for successfully transitioning these pioneering ideas from the lab to real-world practical solutions. Our experts, from diverse fields and professional backgrounds, will share insights into innovations happening at various levels, from molecular/cellular research to systems-level interventions, each contributing to the future of neural engineering at different paces. They will be involved in two sessions of round table discussions with the attendees and selected students and young professionals who will be given the opportunity to pitch their latest research results. During the discussion we will also explore the importance of interdisciplinary collaborations in
overcoming the challenges associated with scaling up innovations and achieving translational success in this rapidly evolving domain.