Literature DB >> 7647180

Biocybernetic system evaluates indices of operator engagement in automated task.

A T Pope1, E H Bogart, D S Bartolome.   

Abstract

A biocybernetic system has been developed as a method to evaluate automated flight deck concepts for compatibility with human capabilities. A biocybernetic loop is formed by adjusting the mode of operation of a task set (e.g., manual/automated mix) based on electroencephalographic (EEG) signals reflecting an operator's engagement in the task set. A critical issue for the loop operation is the selection of features of the EEG to provide an index of engagement upon which to base decisions to adjust task mode. Subjects were run in the closed-loop feedback configuration under four candidate and three experimental control definitions of an engagement index. The temporal patterning of system mode switching was observed for both positive and negative feedback of the index. The indices were judged on the basis of their relative strength in exhibiting expected feedback control system phenomena (stable operation under negative feedback and unstable operation under positive feedback). Of the candidate indices evaluated in this study, an index constructed according to the formula, beta power/(alpha power + theta power), reflected task engagement best.

Entities:  

Mesh:

Year:  1995        PMID: 7647180     DOI: 10.1016/0301-0511(95)05116-3

Source DB:  PubMed          Journal:  Biol Psychol        ISSN: 0301-0511            Impact factor:   3.251


  37 in total

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5.  Dynamic filtering improves attentional state prediction with fNIRS.

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7.  Emotional Activity Is Negatively Associated With Cognitive Load in Multimedia Learning: A Case Study With EEG Signals.

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Journal:  Front Psychol       Date:  2022-06-13

8.  GASICA: generic automated stress induction and control application design of an application for controlling the stress state.

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9.  Cardiovascular state changes in simulated work environments.

Authors:  Arjan Stuiver; Ben Mulder
Journal:  Front Neurosci       Date:  2014-12-05       Impact factor: 4.677

10.  Monitoring attentional state with fNIRS.

Authors:  Angela R Harrivel; Daniel H Weissman; Douglas C Noll; Scott J Peltier
Journal:  Front Hum Neurosci       Date:  2013-12-13       Impact factor: 3.169

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