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Grant: Collaborative Health Research Projects

Université de Montréal

$273,500.00

A multimodal seizure detection artificial intelligence-based smart wear

EF 2020-21

Résumé
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 selfconfidence), caretakers (evaluation and surveillance), and the healthcare system (reducing associated costs).
Programme
Collaborative Health Research Projects
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
538852-2019
Name nom
Nguyen, Dang Khoa
Department département
Médecine
Organization id
63
Institution établissement
Université de Montréal
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2019
Award amount
273500
Program id
CHRPJ
Program name en
Collaborative Health Research Projects
Program name fr
Projets de recherche concertée sur la santé
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
360
Committee name en
Collaborative Health Research Projects Selection Panel
Committee name fr
Comité de sélection de projets de recherche concertée sur la santé
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
9000
Research subject group en
Medical sciences
Research subject group fr
Sciences médicales
Research subject en
Medical sciences
Research subject fr
Sciences médicales
Installment
inst:2 - 4
Partie
3
Nb partie
4
Application title
A multimodal seizure detection artificial intelligence-based smart wear
Keyword
NSERC
Application 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 selfconfidence), caretakers (evaluation and surveillance), and the healthcare system (reducing associated costs).