Seizure Detection with Wearable Devices and AI

Tracking seizures is crucial for epilepsy monitoring and treatment evaluation. Current epilepsy care relies on caretaker or patient seizure diaries, but often many seizures are missed. Automated electroencephalography (EEG)-based seizure detection systems are a useful support tool to objectively detect and register seizures during long-term video-EEG recording. However, this standard full scalp-EEG recording setup is of limited use outside the hospital, and a discreet, wearable device is needed for capturing seizures in the home setting. Wearable devices may be better tolerated and more suitable for long-term ambulatory monitoring.

Recording

Presentation

Practical information:

1 hours

Online

Philippe Dreesen

English

Target audience: everyone interested in AI

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AI for Times Series seminar
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Leertraject

Learning trajectory 'AI in healthcare'

After providing a brief introduction to the disease of epilepsy and its characteristics Dr. Chatzichristos will provide different use cases/approaches for analyzing EEG (as well as data from other modalities) for seizure prediction. The tools that will be presented for the time series analysis will range from “classical” AI models with handcrafted features to Deep Neural Network approaches. We will introduce the difficulties of creating a model that can be suitable for all types of epilepsy and discuss open issues concerning data quality and availability in the field of epilepsy.

Teacher / speaker

Christos Chatzichristos

www.linkedin.com/in/christoschatzichristos/

I am Christos Chatzichristos, currently a post-doctoral researcher at KU Leuven. My educational background revolves around electrical and computer engineering, with a specialization in Biomedical Applications and an emphasis on signal processing during both my Master's and Ph.D. studies. During my doctoral journey, I witnessed the profound impact of neural networks on the field of signal processing, marking the inception of my foray into the realm of AI applications. I hold a strong belief in fostering broad interdisciplinary collaborations, as I believe that research today cannot thrive in isolation within a single domain. Artificial intelligence stands as a potent tool to expedite healthcare research. However, to truly harness its potential, we must bridge the gap by facilitating healthcare professionals' understanding of fundamental AI concepts, just as they aid biomedical engineers in unraveling the mysteries of the human body. So, here's to using AI to accelerate healthcare research while ensuring that we all speak the same language – whether it's the language of algorithms or the language of anatomy!

AI for Time Series

Several research groups in the Flanders AI Research Program conduct world-class research on time series, both in the development of algorithms and tools, as in a wide area of application fields. In a recent poll in the Flanders AI community, ‘time series’ came up as the most wanted topic for future workshops or courses. With this seminar series, we bring together researchers that are interested in, or are conducting research related to, time series. We offer a varied program of national and international speakers.

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