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Grant: Discovery Grants Program - Individual

Queen's University

$61,000.00

Sophstication of feedback control during voluntary behaviour

EF 2017-18

Résumé
Humans have a remarkable ability to make smooth and graceful movements. Perhaps our ability to make quick and accurate corrections when we are accidentally bumped or rapidly make changes in our movements such as weaving through a crowded shopping mall. By comparison, robotic movements are nothing short of clumsy and lack the speed and agility we take for granted. My long-term goal is to understand how the motor system is able to coordinate and learn the broad range of sensorimotor skills we use to move and interact in the world. My model system is whole-arm motor tasks performed in the horizontal plane. These two-dimensional tasks possess most of the complexity inherent in body movements, including intersegmental dynamics and redundancy in how one moves to a spatial goal. The research program uses a unique robotic device I developed called KINARM (Kinesiological Instrument for Normal and Altered Reaching Movements) that both monitors motion at the shoulder and elbow joints and can apply mechanical loads at one or both joints. My present focus is on using the ideas of optimal feedback control as a conceptual framework for studying the voluntary motor system. These type of controllers use sensory feedback in a sophisticated way, such that errors that influence the goal of a motor task are corrected and errors that won't influence performance are ignored. The projects will examine how the motor system responds to mechanical perturbations to correct errors in performance while considering obstacles in the environment, whether the two limbs are working together (bimanual control) or independently (unimanual control), or learn to compensate for novel loads applied to the limb. Artificial neural networks that control a model of the limb will also be examined to explore whether they demonstrate the same principles associated with optimal feedback and to complement and interpret our human experimental work. These projects will provide important details on human motor control. Such knowledge forms the basis for examining and understanding motor dysfunctions in various patient groups as well as for understanding motor skill acquisition related to motor development and sports.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
227920-2010
Name nom
Scott, Stephen
Department département
Biomedical and Molecular Sciences
Organization id
29
Institution établissement
Queen's University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2010
Award amount
61000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1502
Committee name en
Biological Systems and Functions
Committee name fr
Systèmes et fonctions biologiques
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
1903
Research subject group en
Biomedical engineering
Research subject group fr
Génie biomédical
Research subject en
Biomechanics
Research subject fr
Biomécanique
Partie
8
Nb partie
8
Application title
Sophstication of feedback control during voluntary behaviour
Keyword
NSERC
Application summary
Humans have a remarkable ability to make smooth and graceful movements. Perhaps our ability to make quick and accurate corrections when we are accidentally bumped or rapidly make changes in our movements such as weaving through a crowded shopping mall. By comparison, robotic movements are nothing short of clumsy and lack the speed and agility we take for granted. My long-term goal is to understand how the motor system is able to coordinate and learn the broad range of sensorimotor skills we use to move and interact in the world. My model system is whole-arm motor tasks performed in the horizontal plane. These two-dimensional tasks possess most of the complexity inherent in body movements, including intersegmental dynamics and redundancy in how one moves to a spatial goal. The research program uses a unique robotic device I developed called KINARM (Kinesiological Instrument for Normal and Altered Reaching Movements) that both monitors motion at the shoulder and elbow joints and can apply mechanical loads at one or both joints. My present focus is on using the ideas of optimal feedback control as a conceptual framework for studying the voluntary motor system. These type of controllers use sensory feedback in a sophisticated way, such that errors that influence the goal of a motor task are corrected and errors that won't influence performance are ignored. The projects will examine how the motor system responds to mechanical perturbations to correct errors in performance while considering obstacles in the environment, whether the two limbs are working together (bimanual control) or independently (unimanual control), or learn to compensate for novel loads applied to the limb. Artificial neural networks that control a model of the limb will also be examined to explore whether they demonstrate the same principles associated with optimal feedback and to complement and interpret our human experimental work. These projects will provide important details on human motor control. Such knowledge forms the basis for examining and understanding motor dysfunctions in various patient groups as well as for understanding motor skill acquisition related to motor development and sports.