The SIPPRE Research Group invites applications for a Diploma Thesis in the exciting field of multimodal analysis of player experience in gaming environments.
The project aims to design, implement, and evaluate a comprehensive experimental platform that records and analyzes the physiological and emotional responses of volunteers while playing on the PlayStation 4. Two contrasting genres will be studied:
🧩 Brain/cognitive games that require focus and strategic thinking.
⚡ Action games that emphasize speed, reflexes, and intense engagement.
By comparing these categories, the thesis will investigate how different gameplay conditions affect the brain, the body, and the emotions of players.
Multimodal Data Sources
The student will integrate and synchronize diverse signals, including:
🎮 Gameplay Recording via Elgato Cam Link.
🧠 EEG (OpenBCI) to monitor brain activity.
❤️ Physiological Signals (EmotiBit) – heart rate, GSR, SpO₂.
👀 Eye Tracking to measure focus and attention shifts.
😊 Facial Emotion Recognition from a webcam.
🎛️ Controller Interaction Logging using a custom Arduino or Raspberry Pi device to capture button presses in real time.
Student Role & Responsibilities
The candidate will:
Set up the full experimental environment and ensure precise synchronization of all devices.
Recruit and manage volunteers for controlled gaming experiments.
Implement data fusion across modalities (EEG, physiology, gaze, face, gameplay events).
Conduct emotion recognition and correlation analysis across different game types.
Applications & Research Impact
This work directly contributes to our ongoing SIPPRE research on Dynamic Difficulty Adjustment (DDA), where game difficulty adapts to the player’s state. Insights from this thesis could enable:
🎮 Adaptive Gaming Systems that adjust difficulty in real time based on stress, engagement, or fatigue.
🧠 Cognitive Workload Monitoring for training or educational games.
⚡ eSports Analytics to study performance under pressure.
🩺 Mental Health and Stress Research using games as experimental environments.
What the Student Will Gain
Experience with state-of-the-art multimodal recording and synchronization (EEG, EmotiBit, eye tracking, video capture).
Skills in signal processing, machine learning, and human–computer interaction.
Training in experimental design and data collection with human participants.
A project at the intersection of gaming, neuroscience, and AI, with potential for scientific publications.
This is a unique opportunity for a motivated student to combine gaming, biosignals, and adaptive AI to shape the future of interactive systems.
📩 Interested candidates should contact Assoc. Prof. Athanasios Koutras for further details.