Machine learning in video-based monitoring of epilepsy patients: feasibility in seizure detection, classification and documentation
We are delighted to congratulate Petri Ojanen on his outstanding achievement!
Petri has just completed and publicly defended his doctoral dissertation titled “Machine learning in video-based monitoring of epilepsy patients: feasibility in seizure detection, classification and documentation,” in which he investigated the role of AI in detecting and classifying epilepsy seizures.
The research was carried out by an exceptionally interdisciplinary team, assembled by Neuro Event Labs Oy, which brought together experts from both medical and engineering fields, including those specializing in artificial intelligence, video analysis, and signal processing.
Professor Jukka Peltola as the custos and professor João Cunha as the opponent. Professor João Cunha starts with:
“It’s a great honour and a pleasure to be here to be the opponent of thesis of Petri. These are not worth of circumstances. I would not cross Europe from coast to coast to be here and to discuss thesis with the candidate. This is an honor to be here and it’s already been a pleasure to interact with you.”
The dissertation provides valuable insights into how an AI-based approach can significantly improve the quality of epilepsy care. Petri examined how AI assists in automatically identifying and categorizing seizures. He also compared how the documentation of seizure in AI-based documentation and traditional diaries differed from each other using the Nelli® device by Neuro Event Labs. His research highlights interesting perspectives on how technology can support medical practice and patient well-being.
You can read the dissertation on: https://trepo.tuni.fi/handle/10024/156377