Adaptive Neurostimulation with Multi-Stage Control Loop: Application to Drug Resistant Epilepsy

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU142127" target="_blank" >RIV/00216305:26220/21:PU142127 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Adaptive Neurostimulation with Multi-Stage Control Loop: Application to Drug Resistant Epilepsy

Popis výsledku v původním jazyce

Responsive neural stimulation (RNS) delivers electrical stimulation in a brain region in response to brain activity to treat neurological disorders. RNS directed at seizures and abnormal epileptiform activity proved to be successful in reducing seizures in drug resistant epilepsy, but efficacy optimization can be slow. There is ongoing interest in systems where stimulation paradigms and network targets are optimized adaptatively over time. Here we present a system where a cascade of detectors in implanted neural sensing and stimulation (INSS) device and a handheld device enabling machine learning seizure detection algorithms to adaptively control stimulation parameters and brain targets. We developed a system for multi-stage control over adaptive neurostimulation paradigms. The system utilizes an INSS with continuous real-time intracranial EEG (iEEG) recording and bi-directional communication with a handheld for off-device programmable control. The adaptive RNS settings on the INSS device engage multi

Název v anglickém jazyce

Adaptive Neurostimulation with Multi-Stage Control Loop: Application to Drug Resistant Epilepsy

Popis výsledku anglicky

Responsive neural stimulation (RNS) delivers electrical stimulation in a brain region in response to brain activity to treat neurological disorders. RNS directed at seizures and abnormal epileptiform activity proved to be successful in reducing seizures in drug resistant epilepsy, but efficacy optimization can be slow. There is ongoing interest in systems where stimulation paradigms and network targets are optimized adaptatively over time. Here we present a system where a cascade of detectors in implanted neural sensing and stimulation (INSS) device and a handheld device enabling machine learning seizure detection algorithms to adaptively control stimulation parameters and brain targets. We developed a system for multi-stage control over adaptive neurostimulation paradigms. The system utilizes an INSS with continuous real-time intracranial EEG (iEEG) recording and bi-directional communication with a handheld for off-device programmable control. The adaptive RNS settings on the INSS device engage multi

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

20601 - Medical engineering

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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