Distributed brain co-processor for tracking spikes, seizures and behaviour during electrical brain stimulation

0558868 - ÚPT 2023 RIV GB eng J - Článek v odborném periodiku
Sladký, V. - Nejedlý, Petr - Mívalt, F. - Brinkmann, B. H. - Kim, I. - St Louis, E. K. - Gregg, N. M. - Lundstrom, B. N. - Crowe, C. M. - Attia, T. P. - Crepeau, D. - Balzekas, I. - Marks, V. S. - Wheeler, L. P. - Cimbálník, J. - Cook, M. - Janča, R. - Sturges, B. K. - Leyde, K. - Miller, K. J. - Van Gompel, J. J. - Denison, T. - Worrell, G. A. - Křemen, V.
Distributed brain co-processor for tracking spikes, seizures and behaviour during electrical brain stimulation.
Brain communications. Roč. 4, č. 3 (2022), č. článku fcac115. E-ISSN 2632-1297
Grant CEP: GA MŠMT(CZ) LTAUSA18056
Institucionální podpora: RVO:68081731
Klíčová slova: epilepsy * seizures * electrophysiology * machine learning
Obor OECD: Medical engineering
Impakt faktor: 4.8, rok: 2022
Způsob publikování: Open access
https://academic.oup.com/braincomms/article/4/3/fcac115/6581724

Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioural inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behaviour and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a handheld device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from nine humans and eight canines with epilepsy, and then implemented prospectively in out-of-sample testing in two pet canines and four humans with drug-resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain-stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures and correlation with patient behavioural reports. In the future, correlation of spikes and seizures with behaviour will allow more detailed investigation of the clinical impact of spikes and seizures on patients.
Trvalý link: https://hdl.handle.net/11104/0333248