Grant: Engage Plus Grants Program
York University
$9,125.00
Technology development finalization -Detecting concussion related mobility loss in athletes using the mobility assessment tool (MAT)
EF 2015-16
Résumé
Computer vision technologies have become widely employed in the biomedical domain. Such technology is preferred for efficiency and precision in many applications, especially for body detection and movement tracking. The objective of this project is to finalize development of the Mobility Assessment Tool (MAT) for assessment of mobility deterioration following mild brain injury. This is a validation of the algorithms for our non-invasive, unique, and purely objective computer vision video-tool. This tool was recently advanced from an early laboratory-based beta stage (initial Engage grant with Dr. Robert Allison in the Dept. of Electrical Engineering & Computer Science) to one with upgraded hardware that accurately tracked humans (our previous Engage grant). The system has now gone from a prototype to a validated operational product able to
perform a completely automated Modified Tinetti gate/balance test on adults. In this phase of the project we will finalize the algorithms of the developed product by comparing its performance with our own functional assessment tools in young adults who have suffered concussion. Validating the functionality of this device, in particular its ability to accurately discriminate healthy from clinically anomalous posture and gait, will allow PhD Associates to advance a patent application and approach investors for commercial development. PhD Associates will also be able to approach practitioners with an easy, precise, and low cost tool to estimate fall risk and incapacity from gait and balance (mobility) measurements. This work is important for the
advancement in medical kinematics which will impact Canadian research in the field of rehabilitation, diagnosis, and function assessment. Another target market for the MAT is the personal injury law and the insurance industry, both of which would benefit from simple, computerized quick assessment of functional mobility resulting from an accident. This project is a partnership between York University and PhD Associates, the expected duration of the project is 6 months.
Programme
Engage Plus Grants Program
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
486525-2015
Name nom
Sergio, Lauren
Department département
Kinesiology and Health Science, School of
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2015
Competition year année de concours
2015
Award amount
9125
Program id
EGP2
Program name en
Engage Plus Grants Program
Program name fr
Programme de subvention d'engagement partenarial Plus
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1553
Committee name en
Ontario Internal Decision Committee
Committee name fr
Comité de décision interne pour l'Ontario
Area of application code
518
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Medical equipment and apparatus
Area of application fr
Appareils et instruments médicaux
Research subject code
1901
Research subject group en
Biomedical engineering
Research subject group fr
Génie biomédical
Research subject en
Biomedical technology
Research subject fr
Technologie biomédicale
Partie
1
Nb partie
1
Application title
Technology development finalization -Detecting concussion related mobility loss in athletes using the mobility assessment tool (MAT)
Keyword
NSERC
Application summary
Computer vision technologies have become widely employed in the biomedical domain. Such technology is preferred for efficiency and precision in many applications, especially for body detection and movement tracking. The objective of this project is to finalize development of the Mobility Assessment Tool (MAT) for assessment of mobility deterioration following mild brain injury. This is a validation of the algorithms for our non-invasive, unique, and purely objective computer vision video-tool. This tool was recently advanced from an early laboratory-based beta stage (initial Engage grant with Dr. Robert Allison in the Dept. of Electrical Engineering & Computer Science) to one with upgraded hardware that accurately tracked humans (our previous Engage grant). The system has now gone from a prototype to a validated operational product able to
perform a completely automated Modified Tinetti gate/balance test on adults. In this phase of the project we will finalize the algorithms of the developed product by comparing its performance with our own functional assessment tools in young adults who have suffered concussion. Validating the functionality of this device, in particular its ability to accurately discriminate healthy from clinically anomalous posture and gait, will allow PhD Associates to advance a patent application and approach investors for commercial development. PhD Associates will also be able to approach practitioners with an easy, precise, and low cost tool to estimate fall risk and incapacity from gait and balance (mobility) measurements. This work is important for the
advancement in medical kinematics which will impact Canadian research in the field of rehabilitation, diagnosis, and function assessment. Another target market for the MAT is the personal injury law and the insurance industry, both of which would benefit from simple, computerized quick assessment of functional mobility resulting from an accident. This project is a partnership between York University and PhD Associates, the expected duration of the project is 6 months.