Real-Time Adaptive Automation System Based on Identification of Operator Functional State in Simulated Process Control Operations
This paper proposes a new framework for the online monitoring and adaptive control of automation in complex and safety-critical human-machine systems using psychophysiological markers relating to humans under mental stress. The starting point of this framework relates to the assessment of the so-cal...
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| Veröffentlicht in: | IEEE transactions on systems, man and cybernetics. Part A, Systems and humans man and cybernetics. Part A, Systems and humans, 2010-03, Vol.40 (2), p.251-262 |
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| container_title | IEEE transactions on systems, man and cybernetics. Part A, Systems and humans |
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| creator | Ching-Hua Ting Mahfouf, M. Nassef, A. Linkens, D.A. Panoutsos, G. Nickel, P. Roberts, A.C. Hockey, G. |
| description | This paper proposes a new framework for the online monitoring and adaptive control of automation in complex and safety-critical human-machine systems using psychophysiological markers relating to humans under mental stress. The starting point of this framework relates to the assessment of the so-called operator functional state using psychophysiological measures. An adaptive fuzzy model linking heart-rate variability and task load index with the subjects' optimal performance has been elicited and validated offline via a series of experiments involving process control tasks simulated on an automation-enhanced Cabin Air Management System. The elicited model has been used as the basis for an online control system via the predictions of the system performance indicators corresponding to the operator stressful state. These indicators have been used by a fuzzy decision maker to modify the level of automation under which the system may operate. A real-time architecture has been developed as a platform for this approach. It has been validated in a series of human volunteer studies with promising improvement in performance. |
| doi_str_mv | 10.1109/TSMCA.2009.2035301 |
| format | Article |
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The starting point of this framework relates to the assessment of the so-called operator functional state using psychophysiological measures. An adaptive fuzzy model linking heart-rate variability and task load index with the subjects' optimal performance has been elicited and validated offline via a series of experiments involving process control tasks simulated on an automation-enhanced Cabin Air Management System. The elicited model has been used as the basis for an online control system via the predictions of the system performance indicators corresponding to the operator stressful state. These indicators have been used by a fuzzy decision maker to modify the level of automation under which the system may operate. A real-time architecture has been developed as a platform for this approach. 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(IEEE) Mar 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c358t-756b41bb5e1ad7b9cfc836ed7812dc747ba1ad08024db1e3bc65aa196fabbced3</citedby><cites>FETCH-LOGICAL-c358t-756b41bb5e1ad7b9cfc836ed7812dc747ba1ad08024db1e3bc65aa196fabbced3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5345873$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5345873$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ching-Hua Ting</creatorcontrib><creatorcontrib>Mahfouf, M.</creatorcontrib><creatorcontrib>Nassef, A.</creatorcontrib><creatorcontrib>Linkens, D.A.</creatorcontrib><creatorcontrib>Panoutsos, G.</creatorcontrib><creatorcontrib>Nickel, P.</creatorcontrib><creatorcontrib>Roberts, A.C.</creatorcontrib><creatorcontrib>Hockey, G.</creatorcontrib><title>Real-Time Adaptive Automation System Based on Identification of Operator Functional State in Simulated Process Control Operations</title><title>IEEE transactions on systems, man and cybernetics. Part A, Systems and humans</title><addtitle>TSMCA</addtitle><description>This paper proposes a new framework for the online monitoring and adaptive control of automation in complex and safety-critical human-machine systems using psychophysiological markers relating to humans under mental stress. The starting point of this framework relates to the assessment of the so-called operator functional state using psychophysiological measures. An adaptive fuzzy model linking heart-rate variability and task load index with the subjects' optimal performance has been elicited and validated offline via a series of experiments involving process control tasks simulated on an automation-enhanced Cabin Air Management System. The elicited model has been used as the basis for an online control system via the predictions of the system performance indicators corresponding to the operator stressful state. 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It has been validated in a series of human volunteer studies with promising improvement in performance.</description><subject>Adaptive Automation (AA)</subject><subject>Adaptive control</subject><subject>Adaptive systems</subject><subject>Automation</subject><subject>Computerized monitoring</subject><subject>Fuzzy</subject><subject>Fuzzy logic</subject><subject>Fuzzy set theory</subject><subject>Fuzzy systems</subject><subject>Human</subject><subject>Humans</subject><subject>Indicators</subject><subject>man-machine systems</subject><subject>Mathematical models</subject><subject>neural-fuzzy modeling and control</subject><subject>operator functional state (OFS)</subject><subject>Operators</subject><subject>Process control</subject><subject>Process controls</subject><subject>Programmable control</subject><subject>Psychology</subject><subject>psychophysiology</subject><subject>Real time systems</subject><subject>signal processing</subject><subject>Studies</subject><issn>1083-4427</issn><issn>2168-2216</issn><issn>1558-2426</issn><issn>2168-2232</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqFkT1v2zAQhoWiAZom-QPtQnTpJJefIjW6RtIESOAgdmeBHyeAgSS6JBXAY_556NrI0KUL-d7d895wb1V9IXhBCG5_bDcPq-WCYtyWhwmGyYfqnAihaspp87ForFjNOZWfqs8pPWNMOG_5efX6BHqot34EtHR6l_1LEXMOo84-TGizTxlG9FMncKjUdw6m7Htvj-PQo_UOos4hopt5soemHtAm6wzIF7sf56Fohx5jsJASWoUpxzCcbAVPl9VZr4cEV6f_ovp9c71d3db36193q-V9bZlQuZaiMZwYI4BoJ01re6tYA04qQp2VXBpdBlhhyp0hwIxthNakbXptjAXHLqrvx727GP7MkHI3-mRhGPQEYU6dkgIT1WL5X1JyJpkQhBTy2z_kc5hjOUFZJySjmCpRIHqEbAwpRei7XfSjjvuO4O6QXvc3ve6QXndKr5i-Hk0eAN4NgnGhJGNvuCeYeg</recordid><startdate>201003</startdate><enddate>201003</enddate><creator>Ching-Hua Ting</creator><creator>Mahfouf, M.</creator><creator>Nassef, A.</creator><creator>Linkens, D.A.</creator><creator>Panoutsos, G.</creator><creator>Nickel, P.</creator><creator>Roberts, A.C.</creator><creator>Hockey, G.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | Adaptive Automation (AA) Adaptive control Adaptive systems Automation Computerized monitoring Fuzzy Fuzzy logic Fuzzy set theory Fuzzy systems Human Humans Indicators man-machine systems Mathematical models neural-fuzzy modeling and control operator functional state (OFS) Operators Process control Process controls Programmable control Psychology psychophysiology Real time systems signal processing Studies |
| title | Real-Time Adaptive Automation System Based on Identification of Operator Functional State in Simulated Process Control Operations |
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