Electroencephalography (EEG) is a non-invasive neuroimaging technique that measures the electrical activity of the brain through electrodes placed on the scalp. EEG can be used for various research applications, including studying brain function and activity, identifying neurological disorders, and investigating the effects of drugs or other interventions on brain activity. EEG is particularly useful for studying brain activity in real-time and identifying the timing and location of brain activity associated with specific cognitive processes or behaviors. It can also be used in clinical settings to diagnose and monitor neurological disorders such as epilepsy, sleep disorders, and traumatic brain injuries. Additionally, EEG can be used to investigate the effects of various interventions, such as cognitive training or neurofeedback, on brain activity and function.
For surfers, catching the perfect wave can induce a state of pure ecstasy known as the “stoke”. But what’s happening in the brain during this ultimate ride? Wearable Sensing created a custom dry EEG system that measures brainwaves during surfing. They partnered with Red Bull to use this technology on professional surfers to uncover the neurophysiological aspects of surfing. The dry EEG system is worn on the head like a swimming cap, and it allows for the measurement of brain activity in real-time during surfing. By studying the brainwaves of surfers during their best rides, researchers hope to understand what goes on in the brain during moments of flow and peak performance, and ultimately unlock the secrets to achieving that elusive state of “stoke”.
In this study, wearable sensors and machine learning-based algorithms were used to predict hypoxia in-flight. The group used Wearable Sensing’s dry-EEG technology to collect sensor data from 85 participants during a two-phase study. Participants wore aviation flight masks, which regulated their oxygen intake while performing cognitive tests and simulated flying tasks. EEG data was collected and analyzed using principal component analysis and machine learning algorithms, including Naïve Bayes, decision tree, random forest, and neural network algorithms, to classify the data as normal or hypoxic. The results showed high sensitivity and specificity, indicating potential for developing a real-time, in-flight hypoxia detection system.
This paper proposes a protocol for assessing stress using wearable sensing technology, including Electroencephalography (EEG), Electrocardiography (ECG), and the Perceived Stress Scale, in combination with a Virtual Reality phobia induction setting. Wearable Sensing’s dry EEG technology is used to measure brain activity and investigate functional brain connectivity associated with stress. The proposed protocol can be expanded with the incorporation of machine learning algorithms for automatic stress level classification.
Hairston, David W; Whitaker, Keith W; Ries, Anthony J; Vettel, Jean M; Bradford, Cortney J; Kerick, Scott E; McDowell, Kaleb
Usability of four commercially-oriented EEG systems Journal Article
In: Journal of Neural Engineering, vol. 11, no. 4, pp. 046018, 2014.
@article{hairston2014usability,
title = {Usability of four commercially-oriented EEG systems},
author = {David W Hairston and Keith W Whitaker and Anthony J Ries and Jean M Vettel and Cortney J Bradford and Scott E Kerick and Kaleb McDowell},
url = {https://iopscience.iop.org/article/10.1088/1741-2560/11/4/046018/meta},
year = {2014},
date = {2014-07-01},
journal = {Journal of Neural Engineering},
volume = {11},
number = {4},
pages = {046018},
publisher = {IOP Publishing},
abstract = {Electroencephalography (EEG) holds promise as a neuroimaging technology that can be used to understand how the human brain functions in real-world, operational settings while individuals move freely in perceptually-rich environments. In recent years, several EEG systems have been developed that aim to increase the usability of the neuroimaging technology in real-world settings. Here, the usability of three wireless EEG systems from different companies are compared to a conventional wired EEG system, BioSemi's ActiveTwo, which serves as an established laboratory-grade 'gold standard' baseline. The wireless systems compared include Advanced Brain Monitoring's B-Alert X10, Emotiv Systems' EPOC and the 2009 version of QUASAR's Dry Sensor Interface 10–20. The design of each wireless system is discussed in relation to its impact on the system's usability as a potential real-world neuroimaging system. Evaluations are based on having participants complete a series of cognitive tasks while wearing each of the EEG acquisition systems. This report focuses on the system design, usability factors and participant comfort issues that arise during the experimental sessions. In particular, the EEG systems are assessed on five design elements: adaptability of the system for differing head sizes, subject comfort and preference, variance in scalp locations for the recording electrodes, stability of the electrical connection between the scalp and electrode, and timing integration between the EEG system, the stimulus presentation computer and other external events.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
McDonald, Neil J; Anumula, Harini A; Duff, Eric; Soussou, Walid
Noncontact ECG system for unobtrusive long-term monitoring Conference
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE 2012, ISSN: 1557-170X.
@conference{mcdonald2012noncontact,
title = {Noncontact ECG system for unobtrusive long-term monitoring},
author = {Neil J McDonald and Harini A Anumula and Eric Duff and Walid Soussou},
doi = {10.1109/EMBC.2012.6346254},
issn = {1557-170X},
year = {2012},
date = {2012-11-12},
booktitle = {2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
pages = {1614--1618},
organization = {IEEE},
abstract = {This paper describes measurements made using an ECG system with QUASAR's capacitive bioelectrodes integrated into a pad system that is placed over a chair. QUASAR's capacitive bioelectrode has the property of measuring bioelectric potentials at a small separation from the body. This enables the measurement of ECG signals through fabric, without the removal of clothing or preparation of skin. The ECG was measured through the subject's clothing while the subject sat in the chair without any supporting action from the subject. The ECG pad system is an example of a high compliance system that places minimal requirements upon the subject and, consequently, can be used to generate a long-term record from ECG segments collected on a daily basis, providing valuable information on long-term trends in cardiac health.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Soussou, Walid; Rooksby, Michael; Forty, Charles; Weatherhead, James; Marshall, Sandra
EEG and eye-tracking based measures for enhanced training Conference
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE 2012, ISSN: 1557-170X.
@conference{soussou2012eeg,
title = {EEG and eye-tracking based measures for enhanced training},
author = {Walid Soussou and Michael Rooksby and Charles Forty and James Weatherhead and Sandra Marshall},
doi = {10.1109/EMBC.2012.6346256},
issn = {1557-170X},
year = {2012},
date = {2012-11-12},
booktitle = {2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
pages = {1623--1626},
organization = {IEEE},
abstract = {This paper describes a project whose goal was to establish the feasibility of using unobtrusive cognitive assessment methodologies in order to optimize efficiency and expediency of training. QUASAR, EyeTracking, Inc. (ETI), and Safe Passage International (SPI), teamed to demonstrate correlation between EEG and eye-tracking based cognitive workload, performance assessment and subject expertise on XRay screening tasks. Results indicate significant correlation between cognitive workload metrics based on EEG and eye-tracking measurements recorded during a simulated baggage screening task and subject expertise and error rates in that same task. These results suggest that cognitive monitoring could be useful in improving training efficiency by enabling training paradigms that adapts to increasing expertise.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Slater, Jeremy D; Kalamangalam, Giridhar P; Hope, Omotola
Quality assessment of electroencephalography obtained from a “dry electrode” system Journal Article
In: Journal of Neuroscience Methods, vol. 208, no. 2, pp. 134–137, 2012.
@article{slater2012quality,
title = {Quality assessment of electroencephalography obtained from a “dry electrode” system},
author = {Jeremy D Slater and Giridhar P Kalamangalam and Omotola Hope},
doi = {https://doi.org/10.1016/j.jneumeth.2012.05.011},
year = {2012},
date = {2012-07-01},
journal = {Journal of Neuroscience Methods},
volume = {208},
number = {2},
pages = {134--137},
publisher = {Elsevier},
abstract = {This study examines the difference in application times for routine electroencephalography (EEG) utilizing traditional electrodes and a “dry electrode” headset. The primary outcome measure was the time to interpretable EEG (TIE). A secondary outcome measure of recording quality and interpretability was obtained from EEG sample review by two blinded clinical neurophysiologists. With EEG samples obtained from 10 subjects, the average TIE for the “dry electrode” system was 139 s, and for the conventional recording 873 s (p < 0.001). The results support the hypothesis that such a “dry electrode” system can be applied with more than an 80% reduction in the TIE while still obtaining interpretable EEG.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
McDonald, Neil J; Soussou, Walid
Quasar's qstates cognitive gauge performance in the cognitive state assessment competition 2011 Conference
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE IEEE, 2011, ISSN: 1557-170X.
@conference{mcdonald2011quasar,
title = {Quasar's qstates cognitive gauge performance in the cognitive state assessment competition 2011},
author = {Neil J McDonald and Walid Soussou},
doi = {10.1109/IEMBS.2011.6091614},
issn = {1557-170X},
year = {2011},
date = {2011-12-01},
booktitle = {2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
pages = {6542--6546},
publisher = {IEEE},
organization = {IEEE},
abstract = {The Cognitive State Assessment Competition 2011 was organized by the U.S. Air Force Research Laboratory (AFRL) to compare the performance of real-time cognitive state classification software. This paper presents results for QUASAR's data classification module, QStates, which is a software package for real-time (and off-line) analysis of physiologic data collected during cognitive-specific tasks. The classifier's methodology can be generalized to any particular cognitive state; QStates identifies the most salient features extracted from EEG signals recorded during different cognitive states or loads.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Estepp, Justin R; Monnin, Jason W; Christensen, James C; Wilson, Glenn F
Evaluation of a Dry Electrode System for Electroencephalography: Applications for Psychophysiological Cognitive Workload Assessment Journal Article
In: vol. 54, no. 3, pp. 210–214, 2010.
@article{estepp2010evaluation,
title = {Evaluation of a Dry Electrode System for Electroencephalography: Applications for Psychophysiological Cognitive Workload Assessment},
author = {Justin R Estepp and Jason W Monnin and James C Christensen and Glenn F Wilson},
doi = {First Published September 1, 2010 Research Article https://doi.org/10.1177/154193121005400305},
year = {2010},
date = {2010-09-01},
booktitle = {Proceedings of the Human Factors and Ergonomics Society Annual Meeting},
volume = {54},
number = {3},
pages = {210--214},
organization = {SAGE Publications Sage CA: Los Angeles, CA},
abstract = {Advances in state-of-the-art dry electrode technology have led to the development of a novel dry electrode system for electroencephalography (QUASAR, Inc.; San Diego, California, USA). While basic systems-level testing and comparison of this dry electrode system to conventional wet electrode systems has proved to be very favorable, very limited data has been collected that demonstrates the ability of QUASAR's dry electrode system to replicate results produced in more applied, dynamic testing environments that may be used for human factors applications. In this study, QUASAR's dry electrode headset was used in combination with traditional wet electrodes to determine the ability of the dry electrode system to accurately differentiate between varying levels of cognitive workload. Results show that the accuracy in cognitive workload assessment obtained with wet electrodes is comparable to that obtained with the dry electrodes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Antonenko, Pavlo; Paas, Fred; Grabner, Roland; Gog, Tamara Van
Using Electroencephalography to Measure Cognitive Load Journal Article
In: Educational Psychology Review, vol. 22, no. 4, pp. 425–438, 2010.
@article{antonenko2010using,
title = {Using Electroencephalography to Measure Cognitive Load},
author = {Pavlo Antonenko and Fred Paas and Roland Grabner and Tamara Van Gog},
doi = {dx.doi.org/10.1007/s10648-010-9130-y},
year = {2010},
date = {2010-04-29},
journal = {Educational Psychology Review},
volume = {22},
number = {4},
pages = {425--438},
publisher = {Springer},
abstract = {Application of physiological methods, in particular electroencephalography (EEG), offers new and promising approaches to educational psychology research. EEG is identified as a physiological index that can serve as an online, continuous measure of cognitive load detecting subtle fluctuations in instantaneous load, which can help explain effects of instructional interventions when measures of overall cognitive load fail to reflect such differences in cognitive processing. This paper presents a review of seminal literature on the use of continuous EEG to measure cognitive load and describes two case studies on learning from hypertext and multimedia that employed EEG methodology to collect and analyze cognitive load data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Fielder, James
Electroencephalogram (EEG) Study of Learning Effects across Addition Problems Technical Report
PEBL Technical Report Series 2010.
@techreport{fielder2010electroencephalogram,
title = {Electroencephalogram (EEG) Study of Learning Effects across Addition Problems},
author = {James Fielder},
url = {http://www.quasarusa.com/pdf/Fielder_2010_EEG%20Study%20of%20Learning%20Effects%20across%20Addition%20Problems.pdf},
year = {2010},
date = {2010-01-01},
institution = {PEBL Technical Report Series},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
Estepp, Justin R; Christensen, James C; Monnin, Jason W; Davis, Iris M; Wilson, Glenn F
Validation of a Dry Electrode System for EEG Conference
Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 53, no. 18, SAGE Publications Sage CA: Los Angeles, CA 2009.
@conference{estepp2009validation,
title = {Validation of a Dry Electrode System for EEG},
author = {Justin R Estepp and James C Christensen and Jason W Monnin and Iris M Davis and Glenn F Wilson},
doi = {https://doi.org/10.1177/154193120905301802},
year = {2009},
date = {2009-10-01},
booktitle = {Proceedings of the Human Factors and Ergonomics Society Annual Meeting},
volume = {53},
number = {18},
pages = {1171--1175},
organization = {SAGE Publications Sage CA: Los Angeles, CA},
abstract = {Electroencephalography (EEG) has been used for over 80 years to monitor brain activity. The basic technology of using electrodes placed on the scalp with conductive gel or paste (“wet electrodes”) has not fundamentally changed in that time. An electrode system that does not require conductive gel and skin preparation represents a major advancement in this technology and could significantly increase the utility of such a system for many human factors applications. QUASAR, Inc. (San Diego, CA) has developed a prototype dry electrode system for EEG that may well deliver on the promises of dry electrode technology; before any such system could gain widespread acceptance, it is essential to directly compare their system with conventional wet electrodes. An independent validation of dry vs. wet electrodes was conducted; in general, the results confirm that the data collected by the new system is comparable to conventional wet technology.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Matthews, R; Turner, PJ; McDonald, NJ; Ermolaev, K; Manus, T Mc; Shelby, RA; Steindorf, M
Physiological Sensor Suite Using Zero Preparation Hybrid Electrodes for Real Time Workload Classification Journal Article
In: The International Test and Evaluation Association, vol. 30, pp. 13–17, 2009.
@article{matthews2009physiological,
title = {Physiological Sensor Suite Using Zero Preparation Hybrid Electrodes for Real Time Workload Classification},
author = {R Matthews and PJ Turner and NJ McDonald and K Ermolaev and T Mc Manus and RA Shelby and M Steindorf},
url = {http://www.quasarusa.com/pdf/Matthews_ITEA_2009_Physiological%20Sensor%20Suite%20Using%20Zero%20Preparation%20Hybrid%20Electrodes%20for%20Real%20Time%20Workload%20Classification.pdf},
year = {2009},
date = {2009-01-01},
journal = {The International Test and Evaluation Association},
volume = {30},
pages = {13--17},
abstract = {Quantum Applied Science and Research is working closely with the Aberdeen Test Center to develop an integrated system to monitor warfighter physiology. This need has been recognized by two recent major programs: the Defense Advanced Research Projects Agency’s Augmented Cognition program and the U.S. Army’s Warfighter Physiological Status Monitor program. However, these programs were limited by inadequate development of fully deployable noninvasive sensors and in the number of physiological variables they could simultaneously measure. Warfighters need to rapidly perceive, comprehend, and translate combat information into action. To aid them, robust gauges have been developed for classification of cognitive workload, engagement, and fatigue, which simplify complex physiological data into onedimensional parameters that can be used to identify a subject’s cognitive state during the varied tasks carried out in a training environment. This article describes the two main hardware modules that form part of an integrated Physiological Sensor Suite (PSS): a Physiological Status Monitor (PSM) and a module for the measurement of electroencephalograms (EEGs). The PSS is based on revolutionary noninvasive bioelectric sensor technologies. No modification of the skin’s outer layer is required for the operation of this sensor technology, unlike conventional electrode technology that requires the use of conductive pastes or gels, often with abrasive skin preparation of the electrode site. The PSS was designed to be wearable and unobtrusive, with an emphasis on the capability of long-term monitoring of physiological signals. These factors are of considerable importance in operational settings where high end-user compliance is required. The PSM is a simple belt that is worn around the chest. The EEG system has already been incorporated into a soldier’s Kevlar helmet and tested successfully during combat training. Data are acquired using a miniature, ultralowpower, microprocessor-controlled multichannel data acquisition (DAQ) unit that transmits data wirelessly to a base station/data logger worn by the subject. The DAQ unit is worn on the body close to the measurement point, reducing the amount of cable clutter and minimizing the impact on subject mobility without introducing motion artifacts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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