Grant: Collaborative Research and Development Grants
Concordia University
$199,000.00
Biometric approaches to inferring pilot trainee's affective and cognitive states
EF 2018-19
Résumé
Flight safety requires effective pilot training, which aims to equip pilot trainees with the capabilities to make correct decisions in different flight scenarios. The effectiveness of pilot training depends largely on an instructor's ability to maintain a detailed awareness of the training situation. Armed with this information, instructors can adapt a student's training to his/her specific needs in order to maximize the training benefits. This awareness relies on the quantification of pilot trainee's cognitive (thinking) and affective (emotion/feeling) states in relation to decision making and performance.*Human cognitive/affective states can be inferred from biometric data. For instance, brain waves and eye movements can measure cognitive states. Mental workload can be estimated from brain wave measurement, pupil diameter, skin conductance, cardiac measures and respiration rate. Affective state such as mental stress and other emotions can be inferred from body movements, facial expressions, and other biometric data. The objective of this proposed project is to develop biometric approaches for the quantification of pilot trainee's cognitive and affective states during the pilot training process. The deliverable from this proposed*project will be an integrated solution to quantify pilot trainee's cognitive and affective states. As a result, a novel framework will be developed to bring advanced biometric measurement technologies and algorithms from the laboratory setting into the simulator-based pilot training environment. This framework can be easily extended to other complex yet critical field applications such as medical and military mission training. This proposed project team will include three universities: Concordia University, University of Montreal, and McGill University, an national research lab: National Research Council Canada, three companies: CAE, Marivent, and GlobVision, and one research consortium: CRIAQ (Consortium for Research and Innovation in Aerospace in Québec).
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
514052-2017
Name nom
Zeng, Yong
Department département
Concordia Institute for Information Systems Engineering (CIISE)
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2017
Award amount
199000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
703
Area of application group en
Transportation systems and services
Area of application group fr
Services et systèmes de transport
Area of application en
Aerospace
Area of application fr
Aérospatial
Research subject code
1605
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Human factors engineering
Research subject fr
Génie des facteurs humains
Partie
1
Nb partie
1
Application title
Biometric approaches to inferring pilot trainee's affective and cognitive states
Keyword
NSERC
Application summary
Flight safety requires effective pilot training, which aims to equip pilot trainees with the capabilities to make correct decisions in different flight scenarios. The effectiveness of pilot training depends largely on an instructor's ability to maintain a detailed awareness of the training situation. Armed with this information, instructors can adapt a student's training to his/her specific needs in order to maximize the training benefits. This awareness relies on the quantification of pilot trainee's cognitive (thinking) and affective (emotion/feeling) states in relation to decision making and performance.*Human cognitive/affective states can be inferred from biometric data. For instance, brain waves and eye movements can measure cognitive states. Mental workload can be estimated from brain wave measurement, pupil diameter, skin conductance, cardiac measures and respiration rate. Affective state such as mental stress and other emotions can be inferred from body movements, facial expressions, and other biometric data. The objective of this proposed project is to develop biometric approaches for the quantification of pilot trainee's cognitive and affective states during the pilot training process. The deliverable from this proposed*project will be an integrated solution to quantify pilot trainee's cognitive and affective states. As a result, a novel framework will be developed to bring advanced biometric measurement technologies and algorithms from the laboratory setting into the simulator-based pilot training environment. This framework can be easily extended to other complex yet critical field applications such as medical and military mission training. This proposed project team will include three universities: Concordia University, University of Montreal, and McGill University, an national research lab: National Research Council Canada, three companies: CAE, Marivent, and GlobVision, and one research consortium: CRIAQ (Consortium for Research and Innovation in Aerospace in Québec).
