Psychophysiological responses to changes in workload during simulated air traffic control

Brookings, Jeffrey B.; Wilson, Glenn F.; Swain, Carolyne

doi:10.1016/0301-0511(95)05167-8

Cited by 384 publications

(276 citation statements)

References 21 publications

Supporting

Mentioning

249

Contrasting

Unclassified

Order By: Relevance

“…Both high temperature and high relative humidity reduce blink frequency. Visual performance demand (ie, work difficulty, complexity, and overload) also results in lower blink frequencies (49). VDU work is an important factor that reduces blink frequency and at the same time enhances the interblink interval significantly (50).…”

Section: Factors Influencing Blinking and The Formation Of Tear Filmmentioning

confidence: 99%

Eye irritation and environmental factors in the office environment-hypotheses, causes and a physiological model

Wolkoff¹,

Skov²,

Franck³

et al. 2003

Scand J Work Environ Health

View full text Add to dashboard Cite

Section: Factors Influencing Blinking and The Formation Of Tear Filmmentioning

confidence: 99%

Eye irritation and environmental factors in the office environment-hypotheses, causes and a physiological model

Wolkoff¹,

Skov²,

Franck³

et al. 2003

Scand J Work Environ Health

View full text Add to dashboard Cite

“…Previous research has linked eye-related features to cognitive, mental and memory load [31], [35] as well as emotional aspects, such as valence or negative affect [32], [34]. Brain-related Measurements.…”

Section: Biometric Datamentioning

confidence: 99%

Leveraging Biometric Data to Boost Software Developer Productivity

Fritz

Müller

2016

2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER)

View full text Add to dashboard Cite

Producing great software requires great productive developers. Yet, what does it really mean for an individual developer to be productive, and what can we do to best help developers to be productive? To answer these questions, research has traditionally focused on measuring a developer's output and therefore suffered from two drawbacks: the measures can only be calculated after a developer finished her work and these measures do not account for individual differences between developers. The recent advances in biometric sensor technology offer new opportunities to measure a developer's cognitive and emotional states in real-time and thus allow us to know more about what an individual developer is currently experiencing and what might foster or impede the developer's productivity. Results from recent research studies demonstrate the potential that biometric data has to accurately predict aspects of a developer's work, such as perceived task and code difficulty, progress and interruptibility of a developer. This opens up new opportunities for better supporting developers in their work and, for instance, prevent bugs from entering the code, reduce costly interruptions, and foster a better and more productive work day. Our vision is that biometric sensing will be integrated into a developer's work and that biometrics can be Abstract-Producing great software requires great productive developers. Yet, what does it really mean for an individual developer to be productive, and what can we do to best help developers to be productive? To answer these questions, research has traditionally focused on measuring a developer's output and therefore suffered from two drawbacks: the measures can only be calculated after a developer finished her work and these measures do not account for individual differences between developers.The recent advances in biometric sensor technology offer new opportunities to measure a developer's cognitive and emotional states in real-time and thus allow us to know more about what an individual developer is currently experiencing and what might foster or impede the developer's productivity. Results from recent research studies demonstrate the potential that biometric data has to accurately predict aspects of a developer's work, such as perceived task and code difficulty, progress and interruptibility of a developer. This opens up new opportunities for better supporting developers in their work and, for instance, prevent bugs from entering the code, reduce costly interruptions, and foster a better and more productive work day. Our vision is that biometric sensing will be integrated into a developer's work and that biometrics can be used to boost the productivity of each individual developer.

show abstract

“…In the experiment, each pilot repeated the same task to examine the reliability of the physiological measures, and similar response data was obtained for the two rounds. Brookings et al (1996) examined the sensitivity of physiological response to changes in cognitive workload during simulated air traffic control task. In the experiment, eye blink rate exhibited significant effects of task difficulty.…”

Section: Correlation To Workload In Flight Taskmentioning

confidence: 99%

“…In an experiment of air traffic control task (Brookings et al, 1996), subjects performed simulated traffic control tasks with varying traffic volume and traffic complexity. Two eye movement based workload measures, saccade rate and amplitude, were recorded together with other physiological measures during the control task.…”

Section: Correlation To Workload In Traffic Control Taskmentioning

confidence: 99%

Robust Multimodal Cognitive Load Measurement (RMCLM)

Chen¹

2013

View full text Add to dashboard Cite

This report summarizes the important research activities, study results and research accomplishments out of the RMCLM project in the past year period. The objective of this project includes research of the fundamental issues related to the use of multiple input modalities and their fusion to enable robust and automatic cognitive load measurement (CLM) in the real world. Firstly, we carried out a further literature review on physiological measures of cognitive workload to include the recent advances of physiological measures of cognitive workload. In the meantime, we examined the use of various features (e.g. spectral and approximate entropies, wavelet-based complexity measures, correlation dimension, Hurst exponent) of electroencephalogram (EEG) signals to evaluate changes in working memory load during the performance of a cognitive task with varying difficulty/load levels. Eye based CLM was also studied. Three types of eye activity were investigated: pupillary response, blink, and eye movement (fixation and saccade). We further investigated the linguistic feature based CLM in this study and analyzed novel linguistic features as potential indices of cognitive load. All together, we had carried out CLM study of three unobtrusive modalities, namely EEG, eye activity, and linguistic feature based CLM, in the past year period. List of Publications Report Documentation PageForm Approved OMB No. Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. REPORT DATE APR 20132. REPORT TYPE This report summarizes the important research activities, study results and research accomplishments out of the RMCLM project in the past year period. The objective of this project includes research of the fundamental issues related to the use of multiple input modalities and their fusion to enable robust and automatic cognitive load measurement (CLM) in the real world. Firstly, we carried out a further literature review on physiological measures of cognitive workload to include the recent advances of physiological measures of cognitive workload. In the meantime, we examined the use of various features (e.g. spectral and approximate entropies, wavelet-based complexity measures, correlation dimension, Hurst exponent) of electroencephalogram (EEG) signals to evaluate changes ...

show abstract

Psychophysiological responses to changes in workload during simulated air traffic control

Cited by 384 publications

References 21 publications

Eye irritation and environmental factors in the office environment-hypotheses, causes and a physiological model

Eye irritation and environmental factors in the office environment-hypotheses, causes and a physiological model

Leveraging Biometric Data to Boost Software Developer Productivity

Robust Multimodal Cognitive Load Measurement (RMCLM)

Contact Info

Product

Resources

About