As part of the EUNICE course “Decoding Life Signals: Innovations in Biomedical Signal Processing,” the SIPPRE Group is pleased to host Dr. Nyi Nyi Tun for an invited lecture on the future of EEG-based Brain-Computer Interface (BCI) systems.
📅 Date: Thursday, 22 May 2025 🕓 Time: 16:00 Greece time (15:00 EET) 📍 Platform: Microsoft Teams 🔗 Register here
In this session, Dr. Tun will explore how modern EEG-based BCIs are enabling non-invasive therapies in neurorehabilitation and discuss the role of AI techniques in advancing classification accuracy and system performance. The talk will bridge fundamental signal processing concepts with cutting-edge BCI applications aimed at improving the lives of people in need.
We’re excited to announce that the SIPPRE Lab has acquired a PlayStation console—transforming a popular gaming platform into a powerful research and teaching tool. Far beyond entertainment, the PlayStation will support interdisciplinary research, student projects, and diploma theses in fields such as signal processing, affective computing, and human–computer interaction.
Research & Educational Use
Our PlayStation setup will be used to explore:
BCI-controlled gameplay using EEG and EMG signals.
Emotion-adaptive games, where gameplay evolves based on real-time affective responses.
Multiplayer neural synchrony studies using EEG during cooperative or competitive gaming.
Psychoacoustic research and real-time analysis of sound environments in games.
Visual attention tracking using eye-tracking integrated with FPS/VR game mechanics.
Exergaming for rehabilitation and cognitive-motor training.
Neurophysiological immersion and flow assessment using HRV, GSR, and EEG.
Benchmarking biosignal hardware with structured, game-based protocols.
Getting Involved
Students: If you’re interested in conducting research using this setup, submit a 1–2 page proposal outlining your research question, methodology, and timeline.
Deadline: Proposals for the upcoming academic term are now being accepted. Priority will be given to innovative projects that explore human–computer interaction and emotional response in interactive environments.
For inquiries or to discuss potential projects, please contact Prof. Athanasios Koutras at koutras@uop.gr.
Let’s redefine gaming—as a gateway to next-generation research!
Artificial intelligence (AI) offers tremendous potential for improving medical imaging diagnostics. However, the “black box” nature of many AI models—particularly deep learning systems—presents significant challenges for clinical adoption. This Special Issue focuses on the rapidly evolving field of explainable AI (xAI), which aims to enhance transparency, interpretability, and trust in automated diagnostic systems.
Topics of Interest
We welcome submissions on various aspects of explainable AI in medical imaging, including but not limited to:
Novel methods and frameworks for interpretable AI in medical imaging
Theoretical foundations of explainable AI for medical applications
Algorithmic developments that enhance model transparency
Evaluation strategies for explainable medical imaging systems
Clinical validations of xAI techniques
Approaches balancing high performance with meaningful insights for clinicians
Guest Editors
Dr. Athanasios Koutras – University of the Peloponnese, Greece
Dr. Dermatas Evangelos – University of Patras, Greece
Dr. Ioanna Christoyianni – University of Patras, Greece
Dr. George Apostolopoulos – University of Patras, Greece
Important Information
Submission Deadline: November 20, 2025
Journal Section: Biomedical Engineering
Submission Types: Research articles, review articles, and short communications
How to Submit
Manuscripts should be submitted through the MDPI submission system. Please visit the Special Issue website for detailed submission instructions.
All submissions will undergo a rigorous peer-review process. Accepted papers will be published continuously in the journal and listed together on the Special Issue website.
Contact
For questions related to this Special Issue, please contact any of the Guest Editors or the SIPPRE Research Group.
Applied Sciences is an international, peer-reviewed, open-access journal published by MDPI. The journal has a CiteScore of 3.7 (2023) and is indexed in the Science Citation Index Expanded (Web of Science), Scopus, and other databases.
The SIPPRE Group at the ECE Department, is seeking volunteers to participate in our innovative NeuroRock EEG study.
The Experience
Listen to carefully selected instrumental rock music through high-quality headphones
Wear Enophones, a comfortable and non-invasive EEG headset that feels similar to regular headphones
Share your emotional responses to different music styles
Total time commitment: Approximately 60 minutes
What to Expect
During this relaxing session, you’ll listen to various rock music selections while we record your brain’s natural responses. The Enophones provide a comfortable recording experience with minimal setup—no gels or extensive preparation required.
This research supports our groundbreaking NeuroRock Hackathon where EUNICE students will analyze how the brain processes emotional aspects of music.
How to Participate
Please contact Associate Professor Athanasios Koutras (koutras [AT] uop.gr) for scheduling or additional information.
All data will be anonymized and handled according to research ethics guidelines.
The SIPPRE Group is thrilled to announce our first-ever NeuroRock Hackathon, exclusively for EUNICE students enrolled in the “Decoding Life Signals: Innovations in Biomedical Engineering” course.
The Challenge
Teams will analyze EEG data recorded while participants experience emotional rock music. Your mission: develop algorithms to decode emotional states from brain activity and predict subjective experiences.
Key Information
Deadline: June 5, 2025
Format: Work in pairs to develop Python-based analysis
Experience Required: None! We provide starter code and guidance
This is your chance to apply classroom knowledge to real neuroscience data and explore the fascinating intersection of music, emotions, and brain activity.
Ready to Rock Your Brain?
Keep an eye on your course announcements for complete details, or contact Prof. Athanasios Koutras with questions.
For EUNICE students only. No prior EEG experience necessary.
The Signal, Image Processing and Pattern Recognition Research Group (SIPPRE) is excited to announce the commencement of our EUNICE course “Decoding Life Signals: Innovations in Biomedical Engineering.”
We’re thrilled to welcome 23 talented students from Italy, Portugal, Germany, Ukraine, Poland, Spain and Greece to this innovative program. The international diversity of our cohort promises to bring unique perspectives and collaborative opportunities to our biomedical signal processing journey.
Starting this February, our students will: – Master real-time biosignal acquisition and analysis – Develop brain-computer interfaces – Apply machine learning in healthcare – Collaborate on international projects
First Lecture: 17/2/2025 Follow our progress and student achievements throughout the semester!
We are excited to announce that members of the SIPPRE Research Group are serving as Guest Editors for a special issue of the journal Electronics, titled:
“Recent Advances in Audio, Speech, and Music Processing and Analysis”
This special issue aims to highlight state-of-the-art research in audio, speech, and music processing, focusing on emerging applications, algorithms, and systems. Topics of interest include:
Speech recognition, speaker verification, and voice synthesis.
Audio compression and noise cancelation.
Music information retrieval and recommendation systems.
Autonomous and semi-autonomous computer musicians.
Guest Editors:
Dr. Athanasios Koutras (University of the Peloponnese, Greece)
Dr. Chrisoula Alexandraki (Hellenic Mediterranean University, Greece)
Submission Details:
Deadline: January 15, 2025
Impact Factor: 2.6
CiteScore: 5.3
This is an excellent opportunity for researchers and practitioners to disseminate innovative work in the field of audio, speech, and music processing. Accepted manuscripts will be published open-access, ensuring global visibility and accessibility.
For more information and manuscript submissions, visit the Special Issue Page.
We look forward to your contributions to this exciting field of research!
We are delighted to announce that members of the SIPPRE Research Group are serving as Guest Editors for a special issue of the journal Applied Sciences, titled:
“Diagnosis of Medical Imaging”
This special issue focuses on the latest advancements in medical imaging, including novel techniques, machine-learning approaches, and innovative diagnostic tools that push the boundaries of healthcare technology.
Guest Editors:
Dr. Athanasios Koutras, Dr. Evangelos Dermatas, Dr. Ioanna Christoyianni, Dr. George Apostolopoulos
Submission Details:
Deadline: April 20, 2025
Impact Factor: 2.5
CiteScore: 5.3
We invite researchers, practitioners, and industry professionals to contribute their work and share insights into this exciting field. Accepted papers will be published in an open-access format, ensuring maximum visibility and accessibility.
For more information and to submit your manuscript, visit the Special Issue Page.
We look forward to receiving your contributions and advancing the field of medical imaging together!
We are proud to announce the latest publication from our lab in the prestigious journal Electronics:
“Revealing Occult Malignancies in Mammograms Through GAN-Driven Breast Density Transformation”
Authored by Dionysios Anyfantis, PhD student at the SIPPRE Lab, in collaboration with our team, this work explores the application of CycleGANs to transform mammograms of dense breast tissue into lower-density representations. By doing so, the study significantly improves the detection of hidden abnormalities, contributing to the advancement of breast cancer diagnostics.
This innovative research highlights the intersection of deep learning and medical imaging, showcasing how AI can revolutionize healthcare and assist radiologists in making more accurate diagnoses.
Congratulations to Dionysios Anyfantis for this outstanding achievement and his continued contributions to medical imaging and AI research. We look forward to seeing more groundbreaking work from him in the future!
EUNICE (European University for Customized Education) is a prestigious alliance of nine universities across Europe, designed to foster innovation, interdisciplinary learning, and international collaboration. EUNICE aims to create a unified academic environment, offering students diverse opportunities to engage in cutting-edge courses, such as this one, that address global challenges and drive impactful research.
Course Highlights
This interdisciplinary course explores the fascinating world of biomedical signals (EEG, ECG, EMG) and provides a blend of theoretical and practical knowledge:
Data Analysis and Machine Learning: Process, analyze, and visualize biomedical data using tools like Python and MNE-Python.
Real-World Applications: Investigate applications in healthcare, such as Brain-Computer Interfaces (BCIs) and neural signal processing.
Expert Guidance: Learn from distinguished faculty and guest lecturers, bringing expertise from both academia and industry.
Course Details
Language of Instruction: English
Delivery Mode: Online, live sessions with practical exercises and collaborative projects.
Duration: February to May 2025 (12 weeks)
Eligibility: Open to Bachelor’s and Master’s students across EUNICE partner universities, with interest or background in Python programming and biomedical signal processing.
Additional Features
Live Demonstrations: Practical sessions with OpenBCI and EmotiBit, showcasing EEG and physiological signal acquisition techniques.
International Collaboration: Work in teams with students from various EUNICE universities, fostering global connections and interdisciplinary learning.
Resources: Access all course materials, including lecture notes, projects, and tools, through the SIPPRE Lab’s repository and GitHub page.
Join us in this unique opportunity to explore the cutting-edge intersection of technology and healthcare while benefiting from EUNICE’s commitment to international collaboration and quality education.
For enrollment details, visit the EUNICE website at EUNICE Courses or contact Prof. Athanasios Koutras at koutras@uop.gr.