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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00357965" target="_blank" >RIV/68407700:21230/22:00357965 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21460/22:00357965 RIV/68407700:21730/22:00357965

  • Result on the web

    <a href="https://doi.org/10.1093/braincomms/fcac115" target="_blank" >https://doi.org/10.1093/braincomms/fcac115</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1093/braincomms/fcac115" target="_blank" >10.1093/braincomms/fcac115</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioral inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behavior 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 hand-held 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 9 humans and 8 canines with epilepsy, and then implemented prospectively in out-of-sample testing in 2 pet canines and 4 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 behavioral reports. In the future correlation of spikes and seizures with behavior will allow more detailed investigation of the clinical impact of spikes and seizures on patients.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20601 - Medical engineering

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Brain Communications

  • ISSN

    2632-1297

  • e-ISSN

    2632-1297

  • Volume of the periodical

    4

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    16

  • Pages from-to

    1-16

  • UT code for WoS article

    000814811600002

  • EID of the result in the Scopus database

    2-s2.0-85136094010