Canada Spends Logo

Explore our Budget 2026 analysis

Grant: Collaborative Health Research Projects (NSERC partnered)

Université de Montréal

$435,407.00

A multimodal seizure detection artificial intelligence-based smart wear

FY 2018-19

Summary
Epilepsy is a chronic neurological condition that affects as many as 1 in every 100 Canadians. With the ageing of the population, the prevalence and incidence of epilepsy among the elderly is greater than any other age group due to the increasing number brain insults. The first line of treatment consists of long-term drug therapy but more than a third of patients are said to be drug-resistant and continue to suffer from disabling seizures. Due to their unpredictable nature, uncontrolled seizures represent a major personal handicap and source of worriment for patients (risks of injury and death). In addition, persistent seizures constitute a considerable public health burden due to high use of health care resources, high number of disability days or unemployment, and low annual income. For these patients, accurate and rapid detection of seizures could significantly improve their care. Indeed, a system capable of detecting seizures could alert family members, caretakers or medical personnel to intervene in a timely fashion to limit the risk of injuries and death. Hence, the main objective of this project is to develop a user-friendly artificial intelligence-based seizure detection system based on non-invasive multimodal physiological signals obtained through smart wearable devices. Social, ethical, environmental, economic, and legal implications will be taken into account to ensure a smooth and rapid translation to patients with epilepsy. Potential applications are numerous for the benefit of patients (reducing anxiety and enhancing self- confidence), caretakers (evaluation and surveillance), and the healthcare system (reducing associated costs).
Program
Collaborative Health Research Projects (NSERC partnered)
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
CIHR Funding Decisions Database

As published

Id
396502
Name
Nguyen Dang K
Region
Québec
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
A multimodal seizure detection artificial intelligence-based smart wear
Programtype2
Operating Grants
Orgnameinp2
Université de Montréal
Cihramount2
$435,407
Cihrequipment2
$45,186
Programname2
Collaborative Health Research Projects (NSERC partnered)
Keyworddelim
Artificial Intelligence; Classification; Epilepsy; Machine Learning; Monitoring; Seizure Control; Seizure Detection; Signal Processing; Smart-Wear
Abstract
Epilepsy is a chronic neurological condition that affects as many as 1 in every 100 Canadians. With the ageing of the population, the prevalence and incidence of epilepsy among the elderly is greater than any other age group due to the increasing number brain insults. The first line of treatment consists of long-term drug therapy but more than a third of patients are said to be drug-resistant and continue to suffer from disabling seizures. Due to their unpredictable nature, uncontrolled seizures represent a major personal handicap and source of worriment for patients (risks of injury and death). In addition, persistent seizures constitute a considerable public health burden due to high use of health care resources, high number of disability days or unemployment, and low annual income. For these patients, accurate and rapid detection of seizures could significantly improve their care. Indeed, a system capable of detecting seizures could alert family members, caretakers or medical personnel to intervene in a timely fashion to limit the risk of injuries and death. Hence, the main objective of this project is to develop a user-friendly artificial intelligence-based seizure detection system based on non-invasive multimodal physiological signals obtained through smart wearable devices. Social, ethical, environmental, economic, and legal implications will be taken into account to ensure a smooth and rapid translation to patients with epilepsy. Potential applications are numerous for the benefit of patients (reducing anxiety and enhancing self- confidence), caretakers (evaluation and surveillance), and the healthcare system (reducing associated costs).
Competitiondate
201810
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Nguyen, Dang K; Benard, Frederic; Gagnon, Marie-Pierre; Gosselin, Benoit; Laviolette, François; MERVEILLE, NICOLAS; Sawan, Mohamad
Approvedterm
3 ans 0 mois
Cihrcontribution2
Inst of Neurosc Mental Hlth &A~ $54,814~ $45,186~Major Initiatives #2~ $380,593~ $0~