Industrial Neuroscience in Aviation: Evaluation of Mental States in Aviation Personnel: Biosystems & Biorobotics, cartea 18
Autor Gianluca Borghini, Pietro Aricò, Gianluca Di Flumeri, Fabio Babilonien Limba Engleză Hardback – 15 mai 2017
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Specificații
ISBN-13: 9783319585970
ISBN-10: 3319585975
Pagini: 147
Ilustrații: XIII, 147 p. 44 illus., 39 illus. in color.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.41 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Biosystems & Biorobotics
Locul publicării:Cham, Switzerland
ISBN-10: 3319585975
Pagini: 147
Ilustrații: XIII, 147 p. 44 illus., 39 illus. in color.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.41 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Biosystems & Biorobotics
Locul publicării:Cham, Switzerland
Cuprins
From the Content: Introduction.- Preliminary Concepts.- Mental States in Aviation.
Textul de pe ultima copertă
This book discusses the emerging field of industrial neuroscience, and reports on the authors’ cutting-edge findings in the evaluation of mental states, including mental workload, cognitive control and training of personnel involved either in the piloting of aircraft and helicopters, or in managing air traffic. It encompasses neuroimaging and cognitive psychology techniques and shows how they have been successfully applied in the evaluation of human performance and human-machine interactions, and to guarantee a proper level of safety in such operational contexts. With an introduction to the most relevant concepts of neuroscience, neurophysiological techniques, simulators and case studies in aviation environments, it is a must-have for both students and scientists in the field of aeronautic and biomedical engineering, as well as for various professionals in the aviation world. This is the first book to intensively apply neurosciences to the evaluation of human factors and mental statesin aviation.
Caracteristici
Reports on the most important mental states studied in aviation operational contexts Describes machine learning algorithms for assessing operators’ cognitive and emotional states Discusses new findings obtained in both controlled and realistic environments Includes supplementary material: sn.pub/extras