Literature DB >> 11762443

A closed-loop system for examining psychophysiological measures for adaptive task allocation.

L J Prinzel1, F G Freeman, M W Scerbo, P J Mikulka, A T Pope.   

Abstract

A closed-loop system was evaluated for its efficacy in using psychophysiological indexes to moderate workload. Participants were asked to perform either 1 or 3 tasks from the Multiattribute Task Battery and complete the NASA Task Load Index after each trial. An electroencephalogram (EEG) was sampled continuously while they performed the tasks, and an EEG index (beta/alpha plus theta) was derived. The system made allocation decisions as a function of the level of operator engagement based on the value of the EEG index. The results of the study demonstrated that it was possible to moderate an operator's level of engagement through a closed-loop system driven by the operator's own EEG. In addition, the system had a significant impact on behavioral, subjective, and psychophysiological correlates of workload as task load increased. The theoretical and practical implications of these results for adaptive automation are discussed.

Entities:  

Mesh:

Year:  2000        PMID: 11762443     DOI: 10.1207/S15327108IJAP1004_6

Source DB:  PubMed          Journal:  Int J Aviat Psychol        ISSN: 1050-8414


  17 in total

1.  Predictive modeling of human operator cognitive state via sparse and robust support vector machines.

Authors:  Jian-Hua Zhang; Pan-Pan Qin; Jörg Raisch; Ru-Bin Wang
Journal:  Cogn Neurodyn       Date:  2013-01-20       Impact factor: 5.082

2.  Operator functional state estimation based on EEG-data-driven fuzzy model.

Authors:  Jianhua Zhang; Zhong Yin; Shaozeng Yang; Rubin Wang
Journal:  Cogn Neurodyn       Date:  2016-05-13       Impact factor: 5.082

3.  Surface EEG-Transcranial Direct Current Stimulation (tDCS) Closed-Loop System.

Authors:  Jorge Leite; Leon Morales-Quezada; Sandra Carvalho; Aurore Thibaut; Deniz Doruk; Chiun-Fan Chen; Steven C Schachter; Alexander Rotenberg; Felipe Fregni
Journal:  Int J Neural Syst       Date:  2017-04-11       Impact factor: 5.866

4.  Cardiovascular state changes in simulated work environments.

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

5.  Electrode replacement does not affect classification accuracy in dual-session use of a passive brain-computer interface for assessing cognitive workload.

Authors:  Justin R Estepp; James C Christensen
Journal:  Front Neurosci       Date:  2015-03-09       Impact factor: 4.677

6.  Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop.

Authors:  Kate C Ewing; Stephen H Fairclough; Kiel Gilleade
Journal:  Front Hum Neurosci       Date:  2016-05-18       Impact factor: 3.169

7.  Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment.

Authors:  Pietro Aricò; Gianluca Borghini; Gianluca Di Flumeri; Alfredo Colosimo; Stefano Bonelli; Alessia Golfetti; Simone Pozzi; Jean-Paul Imbert; Géraud Granger; Raïlane Benhacene; Fabio Babiloni
Journal:  Front Hum Neurosci       Date:  2016-10-26       Impact factor: 3.169

8.  Improving Challenge/Skill Ratio in a Multimodal Interface by Simultaneously Adapting Game Difficulty and Haptic Assistance through Psychophysiological and Performance Feedback.

Authors:  Carlos Rodriguez-Guerrero; Kristel Knaepen; Juan C Fraile-Marinero; Javier Perez-Turiel; Valentin Gonzalez-de-Garibay; Dirk Lefeber
Journal:  Front Neurosci       Date:  2017-05-01       Impact factor: 4.677

9.  Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

Authors:  Jianhua Zhang; Zhong Yin; Rubin Wang
Journal:  Front Neurosci       Date:  2017-03-17       Impact factor: 4.677

10.  The Brain Is Faster than the Hand in Split-Second Intentions to Respond to an Impending Hazard: A Simulation of Neuroadaptive Automation to Speed Recovery to Perturbation in Flight Attitude.

Authors:  Daniel E Callan; Cengiz Terzibas; Daniel B Cassel; Masa-Aki Sato; Raja Parasuraman
Journal:  Front Hum Neurosci       Date:  2016-04-27       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.