Journal article
Optical brain monitoring for operator training and mental workload assessment
NeuroImage (Orlando, Fla.), v 59(1)
02 Jan 2012
PMID: 21722738
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
An accurate measure of mental workload in human operators is a critical element of monitoring and adaptive aiding systems that are designed to improve the efficiency and safety of human-machine systems during critical tasks. Functional near infrared (fNIR) spectroscopy is a field-deployable non-invasive optical brain monitoring technology that provides a measure of cerebral hemodynamics within the prefrontal cortex in response to sensory, motor, or cognitive activation. In this paper, we provide evidence from two studies that fNIR can be used in ecologically valid environments to assess the: 1) mental workload of operators performing standardized (n-back) and complex cognitive tasks (air traffic control--ATC), and 2) development of expertise during practice of complex cognitive and visuomotor tasks (piloting unmanned air vehicles--UAV). Results indicate that fNIR measures are sensitive to mental task load and practice level, and provide evidence of the fNIR deployment in the field for its ability to monitor hemodynamic changes that are associated with relative cognitive workload changes of operators. The methods reported here provide guidance for the development of strategic requirements necessary for the design of complex human-machine interface systems and assist with assessments of human operator performance criteria.
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Details
- Title
- Optical brain monitoring for operator training and mental workload assessment
- Creators
- Hasan Ayaz - School of Biomedical Engineering, Science & Health Systems, College of Nursing and Health Professions, Drexel University, Philadelphia, PA 19104, USA. ayaz@drexel.eduPatricia A ShewokisScott BunceKurtulus IzzetogluBen WillemsBanu Onaral
- Publication Details
- NeuroImage (Orlando, Fla.), v 59(1)
- Publisher
- Elsevier; United States
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems; Nutrition Sciences
- Web of Science ID
- WOS:000296265500005
- Scopus ID
- 2-s2.0-79960762620
- Other Identifier
- 991014877806604721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Neuroimaging
- Neurosciences
- Radiology, Nuclear Medicine & Medical Imaging