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Biocybernetic Adaptation Strategies: Machine awareness of human state for improved operational performance

Abstract : 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 system. The adaptation process usually makes use of an assessment of transient cognitive 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.
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Submitted on : Wednesday, February 20, 2019 - 3:25:21 PM
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Chad Stephens, Frédéric Dehais, Raphaëlle N. Roy, Angela Harrivel, Mary Carolyn Last, et al.. Biocybernetic Adaptation Strategies: Machine awareness of human state for improved operational performance. 12th International Conference on Augmented Cognition (AC 2018), Jul 2018, Las Vegas, NV, United States. pp.89-98, ⟨10.1007/978-3-319-91470-1_9⟩. ⟨hal-02042710⟩



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