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Biocybernetic Adaptation Strategies: Machine Awareness of Human Engagement for Improved Operational Performance Human operators interacting with machines or computers continually adapt to the needs of the system ideally resulting in optimal performance. In some cases, however, deteriorated performance is an outcome. Adaptation to the situation is a strength expected of the human operator which is often accomplished by the human through self-regulation of mental state. Adaptation is at the core of the human operator's activity, and research has demonstrated that the implementation of a feedback loop can enhance this natural skill to improve training and human/machine interaction. Biocybernetic adaptation involves a “loop upon a loop,” which may be visualized as a superimposed loop which senses a physiological signal and influences the operator’s task at some point. Biocybernetic adaptation in, for example, physiologically adaptive automation employs the “steering” sense of “cybernetic,” and serves a transitory adaptive purpose – to better serve the human operator by more fully representing their responses to the sys- tem. The adaptation process usually makes use of an assessment of transient cog- nitive state to steer a functional aspect of a system that is external to the operator’s physiology from which the state assessment is derived. Therefore, the objective of this paper is to detail the structure of biocybernetic systems regarding the level of engagement of interest for adaptive systems, their processing pipeline, and the adaptation strategies employed for training purposes, in an effort to pave the way towards machine awareness of human state for self-regulation and improved operational performance.
Document ID
20190001869
Acquisition Source
Langley Research Center
Document Type
Conference Paper
Authors
Stephens, Chad
(NASA Langley Research Center Hampton, VA, United States)
Dehais, Frederic
(Institut Superieur de l'Aeronautique et de l'Espace Toulouse, France)
Roy, Raphaelle N.
(Institut Superieur de l'Aeronautique et de l'Espace Toulouse, France)
Harrivel, Angela
(NASA Langley Research Center Hampton, VA, United States)
Last, Mary Carolyn
(Analytical Mechanics Associates, Inc. Hampton, VA, United States)
Kennedy, Kellie
(NASA Langley Research Center Hampton, VA, United States)
Pope, Alan
(NASA Langley Research Center Hampton, VA, United States)
Date Acquired
March 26, 2019
Publication Date
July 15, 2018
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Report/Patent Number
NF1676L-28813
Report Number: NF1676L-28813
Funding Number(s)
WBS: WBS 340428.04.90.07.11
Distribution Limits
Public
Copyright
Public Use Permitted.
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