Scipediacontent: Scipediacontent moved page Draft Content 456180148 to Yeo et al 2017a

2021-01-28T19:27:30Z

Scipediacontent moved page Draft Content 456180148 to Yeo et al 2017a

Scipediacontent: Created page with " == Abstract == With the growing volume and complexity of air traffic, air traffic controllers (ATCOs) encounter heavier burden nowadays. Therefore, human factors study in ai..."

2021-01-28T19:27:25Z

Created page with " == Abstract == With the growing volume and complexity of air traffic, air traffic controllers (ATCOs) encounter heavier burden nowadays. Therefore, human factors study in ai..."

New page

== Abstract ==

With the growing volume and complexity of air traffic, air traffic controllers (ATCOs) encounter heavier burden nowadays. Therefore, human factors study in air traffic control (ATC) is increasingly essential, paving the way to a safer air transportation system. In this paper, we conducted an ATC experiment, where Electroencephalogram (EEG) data were collected throughout the experiment. Compared to traditional questionnaires and psychological tests used in human factors study, the proposed novel EEG approach provides monitoring of situation awareness (SA) in a non-invasive and non-interruptive fashion. SA was represented as the response latency in situation present assessment method (SPAM), which was predicted from EEG signals using three machine learning algorithms. Support vector regression obtained the lowest prediction error of 1.5 seconds, which is lower than 10% of the range of actual response latency. The results show that EEG is a promising approach forward in measuring situation awareness of ATCOs in both real-time and accurate manner.

== Original document ==

The different versions of the original document can be found in:

* [http://publica.fraunhofer.de/documents/N-509985.html http://publica.fraunhofer.de/documents/N-509985.html]

* [http://xplorestaging.ieee.org/ielx7/8114675/8122565/08123090.pdf?arnumber=8123090 http://xplorestaging.ieee.org/ielx7/8114675/8122565/08123090.pdf?arnumber=8123090],
: [http://dx.doi.org/10.1109/smc.2017.8123090 http://dx.doi.org/10.1109/smc.2017.8123090]

* [https://dblp.uni-trier.de/db/conf/smc/smc2017.html#YeoSLTSCMA17 https://dblp.uni-trier.de/db/conf/smc/smc2017.html#YeoSLTSCMA17],
: [https://academic.microsoft.com/#/detail/2773769508 https://academic.microsoft.com/#/detail/2773769508]

← Older revision	Revision as of 19:27, 28 January 2021
(No difference)

Yeo et al 2017a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 456180148 to Yeo et al 2017a

Scipediacontent: Created page with " == Abstract == With the growing volume and complexity of air traffic, air traffic controllers (ATCOs) encounter heavier burden nowadays. Therefore, human factors study in ai..."