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.
Rice, Merrill G; Snider, Dallas; Drollinger, Sabrina; Greil, Chris; Bogni, Frank; Phillips, Jeffrey; Raj, Anil; Marco, Katherine; Linnville, Steven
Gender Differences in Dry-EEG Manifestations During Acute and Insidious Normobaric Hypoxia Journal Article
In: Aerospace Medicine and Human Performance, vol. 90, no. 4, pp. 369–377, 2019.
@article{rice2019gender,
title = {Gender Differences in Dry-EEG Manifestations During Acute and Insidious Normobaric Hypoxia},
author = {Merrill G Rice and Dallas Snider and Sabrina Drollinger and Chris Greil and Frank Bogni and Jeffrey Phillips and Anil Raj and Katherine Marco and Steven Linnville},
doi = { https://doi.org/10.3357/AMHP.5227.2019},
year = {2019},
date = {2019-04-01},
journal = {Aerospace Medicine and Human Performance},
volume = {90},
number = {4},
pages = {369--377},
publisher = {Aerospace Medical Association},
abstract = {INTRODUCTION: Prior research suggests there may be gender differences with regards to hypoxia resilience. Our study was designed to determine whether there were differences between genders in neuronal electrical activity at simulated altitude and whether those changes correlated with cognitive and aviation performance decrements.
METHODS: There were 60 student Naval Aviators or Flight Officers who completed this study (30 women, 30 men). Participants were exposed to increasing levels of normobaric hypoxia and monitored with dry EEG while flying a fixed-base flight simulation. Gender differences in brainwave frequency power were quantified using MATLAB. Changes in flight and cognitive performance were analyzed via simulation tasks and with a cognitive test validated under hypoxia.
RESULTS: Significant decreases in theta and gamma frequency power occurred for women compared to men with insidious hypoxic exposures to 20K, with an average frequency power decrease for women of 19.4% compared to 9.3% for men in theta, and a 42.2% decrease in gamma for women compared to 21.7% for men. Beta frequency power correlated highest between genders, with an average correlation coefficient of r = 0.95 across seven channels.
DISCUSSION: Results of this study suggest there is identifiable brain wave suppression for both men and women with hypoxic exposure and, moreover, there are significant differences in this suppression between genders. Beta frequency power was most sensitive for both genders and highly correlative compared to other brainwave frequencies. The implications of these findings are important considerations for next-generation aviation helmets, which may employ this technology as an early warning mechanism.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Apthorp, Deborah
The drive to unlock the secrets of Parkinson's disease Online
University of New England 2019, visited: 21.03.2019.
@online{Apthorp2019,
title = {The drive to unlock the secrets of Parkinson's disease},
author = {Deborah Apthorp},
url = {https://www.une.edu.au/connect/news/2019/03/the-drive-to-unlock-the-secrets-of-parkinsons-disease},
year = {2019},
date = {2019-03-21},
urldate = {2019-03-21},
organization = {University of New England },
abstract = {A team at the University of New England is moving closer - literally - to solving the mystery of how Parkinson's disease progresses, and rural Australians will soon play their part.},
keywords = {},
pubstate = {published},
tppubtype = {online}
}
Flumeri, Gianluca Di; Aric`o, Pietro; Borghini, Gianluca; Sciaraffa, Nicolina; Florio, Antonello Di; Babiloni, Fabio
In: Sensors, vol. 19, no. 6, pp. 1365, 2019.
@article{di2019dry,
title = {The Dry Revolution: Evaluation of Three Different EEG Dry Electrode Types in Terms of Signal Spectral Features, Mental States Classification and Usability},
author = {Gianluca Di Flumeri and Pietro Aric{`o} and Gianluca Borghini and Nicolina Sciaraffa and Antonello Di Florio and Fabio Babiloni},
doi = {https://doi.org/10.3390/s19061365},
year = {2019},
date = {2019-03-19},
journal = {Sensors},
volume = {19},
number = {6},
pages = {1365},
publisher = {Multidisciplinary Digital Publishing Institute},
abstract = {One century after the first recording of human electroencephalographic (EEG) signals, EEG has become one of the most used neuroimaging techniques. The medical devices industry is now able to produce small and reliable EEG systems, enabling a wide variety of applications also with no-clinical aims, providing a powerful tool to neuroscientific research. However, these systems still suffer from a critical limitation, consisting in the use of wet electrodes, that are uncomfortable and require expertise to install and time from the user. In this context, dozens of different concepts of EEG dry electrodes have been recently developed, and there is the common opinion that they are reaching traditional wet electrodes quality standards. However, although many papers have tried to validate them in terms of signal quality and usability, a comprehensive comparison of different dry electrode types from multiple points of view is still missing. The present work proposes a comparison of three different dry electrode types, selected among the main solutions at present, against wet electrodes, taking into account several aspects, both in terms of signal quality and usability. In particular, the three types consisted in gold-coated single pin, multiple pins and solid-gel electrodes. The results confirmed the great standards achieved by dry electrode industry, since it was possible to obtain results comparable to wet electrodes in terms of signals spectra and mental states classification, but at the same time drastically reducing the time of montage and enhancing the comfort. In particular, multiple-pins and solid-gel electrodes overcome gold-coated single-pin-based ones in terms of comfort.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rice, Merrill G; Snider, Dallas; Drollinger, Sabrina; Greil, Chris; Bogni, Frank; Phillips, Jeffrey; Raj, Anil; Marco, Katherine; Linnville, Steven
Dry-EEG Manifestations of Acute and Insidious Hypoxia During Simulated Flight Journal Article
In: Aerospace Medicine and Human Performance, vol. 90, no. 2, pp. 92-100, 2019.
@article{rice2019dry,
title = {Dry-EEG Manifestations of Acute and Insidious Hypoxia During Simulated Flight},
author = {Merrill G Rice and Dallas Snider and Sabrina Drollinger and Chris Greil and Frank Bogni and Jeffrey Phillips and Anil Raj and Katherine Marco and Steven Linnville},
doi = {https://doi.org/10.3357/AMHP.5228.2019},
year = {2019},
date = {2019-02-01},
journal = {Aerospace Medicine and Human Performance},
volume = {90},
number = {2},
pages = {92-100},
publisher = {Aerospace Medical Association},
abstract = {INTRODUCTION: Recently, portable dry electroencephalographs (dry-EEGs) have indexed cognitive workload, fatigue, and drowsiness in operational environments. Using this technology this project assessed whether significant changes in brainwave frequency power occurred in response to hypoxic exposures as experienced in military aviation.
METHODS: There were 60 (30 women, 30 men) student Naval Aviators or Flight Officers who were exposed to an intense (acute) high-altitude (25,000 ft) normobaric hypoxic exposure, and 20 min later, more gradual (insidious) normobaric hypoxic exposure up to 20,000 ft while flying a fixed-wing flight simulation and monitored with a dry-EEG system. Using MATLAB, EEG frequencies and power were quantified and analyzed. Cognitive performance was also assessed with a cognitive task validated under hypoxia. Normobaric hypoxia and O2 saturation (Spo 2) were produced and monitored using the Reduced Oxygen Breathing Device (ROBD2).
RESULTS: Significant Spo 2 decreases were recorded at acute 25K and insidious 20K simulated altitudes. Significant power decreases were recorded in all frequencies (alpha, beta, gamma, and theta) and all channels with acute 25K exposures. Gamma, beta, and theta frequency power were significantly decreased with insidious 20K exposures at most of the channels. The frequency power decreases corresponded to significant decreases in cognitive performance and flight performance. Most importantly, frequency power suppressions occurred despite 42% of the volunteers not perceiving they were hypoxic in the acute phase, nor 20% in the insidious phase.
DISCUSSION: Results suggest EEG suppression during acute/insidious hypoxia can index performance decrements. These findings have promising implications in the development of biosensors that mitigate potential in-flight hypoxic physiological episodes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lim, Hyunmi; Ku, Jeonghun
Multiple-command single-frequency SSVEP-based BCI system using flickering action video Journal Article
In: Journal of Neuroscience Methods, vol. 314, pp. 21-27, 2019.
@article{lim2019multiple,
title = {Multiple-command single-frequency SSVEP-based BCI system using flickering action video},
author = {Hyunmi Lim and Jeonghun Ku},
doi = {https://doi.org/10.1016/j.jneumeth.2019.01.005},
year = {2019},
date = {2019-01-16},
journal = {Journal of Neuroscience Methods},
volume = {314},
pages = {21-27},
publisher = {Elsevier},
abstract = {Background
The number of commands in a brain–computer interface (BCI) system is important. This study proposes a new BCI technique to increase the number of commands in a single BCI system without loss of accuracy.
New method
We expected that a flickering action video with left and right elbow movements could simultaneously activate the different pattern of event-related desynchronization (ERD) according to the video contents (e.g., left or right) and steady-state visually evoked potential (SSVEP). The classification accuracy to discriminate left, right, and rest states was compared under the three following feature combinations: SSVEP power (19–21 Hz), Mu power (8–13 Hz), and simultaneous SSVEP and Mu power.
Results
The SSVEP feature could discriminate the stimulus condition, regardless of left or right, from the rest condition, while the Mu feature discriminated left or right, but was relatively poor in discriminating stimulus from rest. However, combining the SSVEP and Mu features, which were evoked by the stimulus with a single frequency, showed superior performance for discriminating all the stimuli among rest, left, or right.
Comparison with the existing method
The video contents could activate the ERD differently, and the flickering component increased its accuracy, such that it revealed a better performance to discriminate when considering together.
Conclusions
This paradigm showed possibility of increasing performance in terms of accuracy and number of commands with a single frequency by applying flickering action video paradigm and applicability to rehabilitation systems used by patients to facilitate their mirror neuron systems while training.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Arakaki, Xianghong; Lee, Ryan; King, Kevin S; Fonteh, Alfred N; Harrington, Michael G
Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals Journal Article
In: PloS one, vol. 14, no. 1, pp. e0208517, 2019.
@article{arakaki2019alpha,
title = {Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals},
author = {Xianghong Arakaki and Ryan Lee and Kevin S King and Alfred N Fonteh and Michael G Harrington},
editor = {Stephen D. Ginsberg, Nathan S Kline Institute},
doi = {https://doi.org/10.1371/journal.pone.0208517},
year = {2019},
date = {2019-01-02},
journal = {PloS one},
volume = {14},
number = {1},
pages = {e0208517},
publisher = {Public Library of Science San Francisco, CA USA},
abstract = {Our aim is to explore if cognitive challenge combined with objective physiology can reveal abnormal frontal alpha event-related desynchronization (ERD), in early Alzheimer’s disease (AD). We used quantitative electroencephalography (qEEG) to investigate brain activities during N-back working memory (WM) processing at two different load conditions (N = 0 or 2) in an aging cohort. We studied 60–100 year old participants, with normal cognition, and who fits one of two subgroups from cerebrospinal fluid (CSF) proteins: cognitively healthy (CH) with normal amyloid/tau ratio (CH-NAT, n = 10) or pathological amyloid/tau ratio (CH-PAT, n = 14). We recorded behavioral performances, and analyzed alpha power and alpha spectral entropy (SE) at three occasions: during the resting state, and at event-related desynchronization (ERD) [250 ~ 750 ms] during 0-back and 2-back. During 0-back WM testing, the behavioral performance was similar between the two groups, however, qEEG notably differentiated CH-PATs from CH-NATs on the simple, 0-back testing: Alpha ERD decreased from baseline only in the parietal region in CH-NATs, while it decreased in all brain regions in CH-PATs. Alpha SE did not change in CH-NATs, but was increased from baseline in the CH-PATs in frontal and left lateral regions (p<0.01), and was higher in the frontal region (p<0.01) of CH-PATs compared to CH-NATs. The alpha ERD and SE analyses suggest there is frontal lobe dysfunction during WM processing in the CH-PAT stage. Additional power and correlations with behavioral performance were also explored. This study provide pilot information to further evaluate whether this biomarker has clinical significance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Pereira, Arnaldo; Padden, Dereck; Jantz, Jay; Lin, Kate; Alcaide-Aguirre, Ramses
Cross-Subject EEG Event-Related Potential Classification for Brain-Computer Interfaces Using Residual Networks Journal Article
In: 2018.
@article{pereira2018cross,
title = {Cross-Subject EEG Event-Related Potential Classification for Brain-Computer Interfaces Using Residual Networks},
author = {Arnaldo Pereira and Dereck Padden and Jay Jantz and Kate Lin and Ramses Alcaide-Aguirre},
doi = {10.13140/RG.2.2.16257.10086},
year = {2018},
date = {2018-09-20},
urldate = {2018-01-01},
abstract = {EEG event-related potentials, and the P300 signal in
particular, are promising modalities for brain-computer interfaces (BCI). But the nonstationarity of EEG signals and
their differences across individuals have made it difficult to
implement classifiers that can determine user intent without having to be retrained or calibrated for each new user
and sometimes even each session. This is a major impediment to the development of consumer BCI. Recently, the
EEG BCI literature has begun to apply convolutional neural
networks (CNNs) for classification, but experiments have
largely been limited to training and testing on single subjects. In this paper, we report a study in which EEG data
were recorded from 66 subjects in a visual oddball task
in virtual reality. Using wide residual networks (WideResNets), we obtain state-of-the-art performance on a test set
composed of data from all 66 subjects together. Additionally, a minimal preprocessing stream to convert EEG data
into square images for CNN input while adding regularization is presented and shown to be viable. This study also
provides some guidance on network architecture parameters based on experiments with different models. Our results show that it may possible with enough data to train
a classifier for EEG-based BCIs that can generalize across
individuals without the need for individual training or calibration.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Camp, Marieke Van; Boeck, Muriel De; Verwulgen, Stijn; Bruyne, Guido De
EEG Technology for UX Evaluation: A Multisensory Perspective Conference
International Conference on Applied Human Factors and Ergonomics, vol. 775, Springer Advances in Intelligent Systems and Computing , 2018.
@conference{van2018eeg,
title = {EEG Technology for UX Evaluation: A Multisensory Perspective},
author = {Marieke Van Camp and Muriel De Boeck and Stijn Verwulgen and Guido De Bruyne},
url = {https://link.springer.com/chapter/10.1007/978-3-319-94866-9_34},
year = {2018},
date = {2018-06-28},
booktitle = {International Conference on Applied Human Factors and Ergonomics},
volume = {775},
pages = {337--343},
publisher = {Advances in Intelligent Systems and Computing },
organization = {Springer},
abstract = {Along with a growing interest in experience-driven design, interest in measuring user experience has progressively increased. This study explores the use of EEG for empirical UX evaluation. A first experimental test was conducted to measure and understand the effect of sensory stimuli on the user experience. A first experimental test was carried out with eight participants. A series of videos, eliciting positive and negative emotional responses, were presented to the participants. Subsequently, auditory stimuli were introduced and the effect on the user experience was evaluated using EEG measurements techniques and analysis software. After the tests the participants were questioned to verify whether the subjective results matched the objective measurements.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Raj, Anil; Roberts, Brooke; Hollingshead, Kristy; McDonald, Neil; Poquette, Melissa; Soussou, Walid
A Wearable Multisensory, Multiagent Approach for Detection and Mitigation of Acute Cognitive Strain Conference
International Conference on Augmented Cognition, Springer 2018.
@conference{raj2018wearable,
title = {A Wearable Multisensory, Multiagent Approach for Detection and Mitigation of Acute Cognitive Strain},
author = {Anil Raj and Brooke Roberts and Kristy Hollingshead and Neil McDonald and Melissa Poquette and Walid Soussou},
url = {https://link.springer.com/chapter/10.1007/978-3-319-91470-1_16},
year = {2018},
date = {2018-06-03},
booktitle = {International Conference on Augmented Cognition},
pages = {180--200},
organization = {Springer},
abstract = {While operators performing tasks with high workload can increase task performance in response to limited increases in cognitive stress, chronic or rapidly accelerating stress can exceed the operator’s ability to compensate, generating acute cognitive strain (ACS). ACS represents a state wherein performance, situation awareness and cooperativity deteriorate markedly, leading to critical errors, mishaps or casualties. Nearly two decades of augmented cognition (AugCog) research has demonstrated the utility of psychophysiologic sensing and analysis for identification and tracking of changes in cognitive state and to modulate human machine interactions for improving system task performance. The proposed approach leveraged prior efforts to modulate cognitive stress using a multiagent approach to acquire and analyze multiple Psychophysiologic sensory channels, including changes in vocalizations, to create a reliable and non-intrusive Detector of Acute Cognitive Strain (DACS). The DACS system provides an integrated wearable multi-modal Research Sensor Suite (RSS) using the open-source Adaptive Multiagent Integration (AMI) architecture, that includes analysis agents for electroencephalograph (EEG), electromyography (EMG), video oculography (VOG), vocalization, and others to identify and correlate physiological signatures with cognitive stress and strain. An online AMI agent-based processing algorithm was developed and applied to audio communications to evaluate for changes in speaker vocalization fundamental frequency (F0) and cadence (utterances per minute). This paper describes initial phase results of aerospace mishap vocalization stress marker detection, a potential element of the proposed DACS system. DACS could use these markers to trigger adaptive automation agents that reduce task load and allow pilots to prevent or recover from ACS episodes.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Vergeer, Mark; Mesik, Juraj; Baek, Yihwa; Wilmerding, Kelton; Engel, Stephen A
Orientation-selective contrast adaptation measured with SSVEP Journal Article
In: Journal of Vision, vol. 18, no. 5, pp. 2–2, 2018.
@article{vergeer2018orientation,
title = {Orientation-selective contrast adaptation measured with SSVEP},
author = {Mark Vergeer and Juraj Mesik and Yihwa Baek and Kelton Wilmerding and Stephen A Engel},
doi = {https://doi.org/10.1167/18.5.2},
year = {2018},
date = {2018-05-01},
journal = {Journal of Vision},
volume = {18},
number = {5},
pages = {2--2},
publisher = {The Association for Research in Vision and Ophthalmology},
abstract = {Exposure to oriented luminance contrast patterns causes a reduction in visual sensitivity specifically for the adapter orientation. This orientation selectivity is probably the most studied aspect of contrast adaptation, but it has rarely been measured with steady-state visually evoked potentials (SSVEPs), despite their becoming one of the more popular methods of human neuroscience. Here, we measured orientation selective adaptation by presenting a plaid stimulus of which the horizontal and vertical grating reversed contrast at different temporal frequencies, while recording EEG signals from occipital visual areas. In three experiments, we compared SSVEP responses to the plaid before and after adaptation. All experiments showed a significant decrease in SSVEP response at the frequency of the adapter orientation, whereas such an effect was absent for the frequency of the orthogonal orientation. Adaptation also led to robust phase delays, selectively for the SSVEP frequency corresponding to the adapter orientation. These results demonstrate the efficiency of SSVEPs for measuring orientation selective adaptation; the method can measure changes in both amplitude and phase, simultaneously for two orientations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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