Grant: Collaborative Health Research Projects (NSERC partnered)
University of Toronto
$360,000.00
Personalized Contingent Neurostimulation for Epilepsy by Machine Learning in Organic Brain Interfaces
FY 2019-20
Summary
Epilepsy is a chronic, neurological condition characterized by unpredictable, disabling seizures. This devastating disorder increases mortality by 4 times and depression by 2 times population rates. Unfortunately, epilepsy is extremely common, affecting 1 in 100 people, and in 33% of cases, medications do not prevent seizures. An emerging technology to aid such patients with drug-resistant epilepsy is contingent neurostimulation devices. These devices are implanted in a patient so that they can detect epileptiform activity and electrically stimulate the nervous system to prevent/abort seizures. Recently, two commercial contingent neurostimulators have been approved for treating epilepsy. These devices have proven successful at reducing seizure activity, however their efficacy is low. In particular, they are very unlikely to produce seizure freedom, which is necessary to restore patient independence and quality of life.
The primary reasons why existing neurostimulation devices have had such limited success are that: (a) they use rudimentary (sparse and large) electrodes that poorly interface with the brain and (b) they are extremely simplistic in their seizure detection and abortion capabilities due to the use of basic electronics as constrained by energy limitations of an implant. We propose to combine (a) the far superior brain-interfacing electrode technology from our partner Panaxium and (b) our energy-efficient state-of-the-art implantable electronic circuits that employ artificial intelligence for optimal seizure prediction and prevention - to greatly improve the seizure-freedom efficacy of the neuromodulation therapy for intractable epilepsy.
Our team is uniquely well qualified for this project. It is led by an expert in low-power biomedical and computational electronics (Genov), an epilepsy neurosurgeon and an expert in brain neurophysiology (Valiante), and Panaxium's Technology Commercialization Leader and a 20-year industry veteran (Weinroth).
Department
Program
Collaborative Health Research Projects (NSERC partnered)
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
CIHR Funding Decisions Database
As published
Id
415729
Name
Genov Roman
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Partnername
Natural Sciences and Engineering Research Council of Canada (NSERC)
Instname2
Neurosciences, Mental Health and Addiction
Theme2
Biomedical
Prcname2
Collaborative Health Research Projects - NSERC Partnered
Projecttitle
Personalized Contingent Neurostimulation for Epilepsy by Machine Learning in Organic Brain Interfaces
Programtype2
Operating Grants
Orgnameinp2
University of Toronto
Cihramount2
$360,000
Cihrequipment2
$15,000
Programname2
Collaborative Health Research Projects (NSERC partnered)
Keyworddelim
Applied Machine Learning; Epilepsy; Hardware Acceleration; Microelectonics; Neurostimulation
Abstract
Epilepsy is a chronic, neurological condition characterized by unpredictable, disabling seizures. This devastating disorder increases mortality by 4 times and depression by 2 times population rates. Unfortunately, epilepsy is extremely common, affecting 1 in 100 people, and in 33% of cases, medications do not prevent seizures. An emerging technology to aid such patients with drug-resistant epilepsy is contingent neurostimulation devices. These devices are implanted in a patient so that they can detect epileptiform activity and electrically stimulate the nervous system to prevent/abort seizures. Recently, two commercial contingent neurostimulators have been approved for treating epilepsy. These devices have proven successful at reducing seizure activity, however their efficacy is low. In particular, they are very unlikely to produce seizure freedom, which is necessary to restore patient independence and quality of life.
The primary reasons why existing neurostimulation devices have had such limited success are that: (a) they use rudimentary (sparse and large) electrodes that poorly interface with the brain and (b) they are extremely simplistic in their seizure detection and abortion capabilities due to the use of basic electronics as constrained by energy limitations of an implant. We propose to combine (a) the far superior brain-interfacing electrode technology from our partner Panaxium and (b) our energy-efficient state-of-the-art implantable electronic circuits that employ artificial intelligence for optimal seizure prediction and prevention - to greatly improve the seizure-freedom efficacy of the neuromodulation therapy for intractable epilepsy.
Our team is uniquely well qualified for this project. It is led by an expert in low-power biomedical and computational electronics (Genov), an epilepsy neurosurgeon and an expert in brain neurophysiology (Valiante), and Panaxium's Technology Commercialization Leader and a 20-year industry veteran (Weinroth).
Competitiondate
201910
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Genov, Roman; Weinroth, Aaron; Valiante, Taufik A
Approvedterm
3 ans 0 mois
Cihrcontribution2
Major Initiatives #2~ $360,000~ $15,000~