Grant: Alliance Grants
Université du Québec à Trois-Rivières
$45,000.00
Is my limb moving? Towards an objective measurement of the illusion of movement using neurophysiological biomarkers of sensorimotor functions and artificial intelligence
FY 2023-24
Summary
An estimated 50,000 new cases of stroke occur in Canada each year, resulting in death or severe disability, including physical. At present, rehabilitation of stroke-related physical disabilities focuses mainly on mobility rehabilitation. However, impairments related to proprioception, the ability to perceive body movement in the absence of vision, are often overlooked in rehabilitation. In recent years, musculo-tendinous vibration (MTV) has been used as a safe and effective stimulation device to study proprioception. Recent studies have shown that MTV is a promising system for aiding stroke rehabilitation. However, the mechanisms of MTV-induced illusions are still unclear. Indeed, the study of motion perception induced by MTV has always been a challenge, since perception is by nature subjective. And it still hinders the gathering of knowledge on proprioception and the current clinical use of MTV. The main aim of this project is to develop an objective method for detecting and quantifying motion illusions induced by MTV, based on healthy individuals only. This objective measurement method will estimate motion illusions on the basis of the combined processing of electromyographic (EEG) and electromyographic (EMG) signals. From these biosignals, reliable biomarkers will be determined and used with advanced machine learning methods to obtain an objective measure of motion illusions and proprioceptive coding. This innovative method, based on EEG and EMG signals, will be designed to achieve a high level of finesse and sensitivity in the detection of motion illusions. This degree of sophistication is needed to develop other future technologies based on VMT, whether to (i) diagnose a patient's perceptual state with good accuracy et (ii) establish a reliable prognosis for recovery. The application of this method is not limited to stroke; it can be extended to other populations suffering from sensorimotor disorders and have a major impact on the healthcare and quality of life of Canadians. To carry out this project, a national team of experts from cross-sectoral fields covering engineering and health sciences has been put together.
Program
Alliance Grants
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
586803-2023
Name nom
Nougarou, François FRA
Department département
Génie électrique et génie informatique
Organization id
59
Institution établissement
Université du Québec à Trois-Rivières
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2023
Award amount
45000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1102
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Biomedical engineering
Area of application fr
Génie biomédical
Research subject code
2510
Research subject group en
Electrical and electronic engineering
Research subject group fr
Adaptive, learning and evolutionary systems
Research subject en
Génie électrique et électronique
Research subject fr
Systèmes d'apprentissage adaptatifs et évolutifs
Application title
Is my limb moving? Towards an objective measurement of the illusion of movement using neurophysiological biomarkers of sensorimotor functions and artificial intelligence
Keyword
Artificial intelligence; Biosignal processing; Embedded system; EMG/EEG; Musculotendinous simulation; Proprioception; Real-time; Stroke
Application summary
An estimated 50,000 new cases of stroke occur in Canada each year, resulting in death or severe disability, including physical. At present, rehabilitation of stroke-related physical disabilities focuses mainly on mobility rehabilitation. However, impairments related to proprioception, the ability to perceive body movement in the absence of vision, are often overlooked in rehabilitation. In recent years, musculo-tendinous vibration (MTV) has been used as a safe and effective stimulation device to study proprioception. Recent studies have shown that MTV is a promising system for aiding stroke rehabilitation. However, the mechanisms of MTV-induced illusions are still unclear. Indeed, the study of motion perception induced by MTV has always been a challenge, since perception is by nature subjective. And it still hinders the gathering of knowledge on proprioception and the current clinical use of MTV. The main aim of this project is to develop an objective method for detecting and quantifying motion illusions induced by MTV, based on healthy individuals only. This objective measurement method will estimate motion illusions on the basis of the combined processing of electromyographic (EEG) and electromyographic (EMG) signals. From these biosignals, reliable biomarkers will be determined and used with advanced machine learning methods to obtain an objective measure of motion illusions and proprioceptive coding. This innovative method, based on EEG and EMG signals, will be designed to achieve a high level of finesse and sensitivity in the detection of motion illusions. This degree of sophistication is needed to develop other future technologies based on VMT, whether to (i) diagnose a patient's perceptual state with good accuracy et (ii) establish a reliable prognosis for recovery. The application of this method is not limited to stroke; it can be extended to other populations suffering from sensorimotor disorders and have a major impact on the healthcare and quality of life of Canadians. To carry out this project, a national team of experts from cross-sectoral fields covering engineering and health sciences has been put together.
