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.
Mills, Caitlin; Fridman, Igor; Soussou, Walid; Waghray, Disha; Olney, Andrew M; D'Mello, Sidney K
Put your thinking cap on: detecting cognitive load using EEG during learning Conference
Proceedings of the Seventh International Learning Analytics & Knowledge Conference, 2017.
@conference{mills2017put,
title = {Put your thinking cap on: detecting cognitive load using EEG during learning},
author = {Caitlin Mills and Igor Fridman and Walid Soussou and Disha Waghray and Andrew M Olney and Sidney K D'Mello},
doi = {https://doi.org/10.1145/3027385.3027431},
year = {2017},
date = {2017-03-01},
booktitle = {Proceedings of the Seventh International Learning Analytics & Knowledge Conference},
pages = {80--89},
abstract = {Current learning technologies have no direct way to assess students' mental effort: are they in deep thought, struggling to overcome an impasse, or are they zoned out? To address this challenge, we propose the use of EEG-based cognitive load detectors during learning. Despite its potential, EEG has not yet been utilized as a way to optimize instructional strategies. We take an initial step towards this goal by assessing how experimentally manipulated (easy and difficult) sections of an intelligent tutoring system (ITS) influenced EEG-based estimates of students' cognitive load. We found a main effect of task difficulty on EEG-based cognitive load estimates, which were also correlated with learning performance. Our results show that EEG can be a viable source of data to model learners' mental states across a 90-minute session.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Halford, Jonathan J; Schalkoff, Robert J; Satterfield, Kevin E; Martz, Gabriel U; Kutluay, Ekrem; Waters, Chad G; Dean, Brian C
Comparison of a Novel Dry Electrode Headset to Standard Routine EEG in Veterans Journal Article
In: Journal of Clinical Neurophysiology, vol. 33, no. 6, pp. 530–537, 2016.
@article{halford2016comparison,
title = {Comparison of a Novel Dry Electrode Headset to Standard Routine EEG in Veterans},
author = {Jonathan J Halford and Robert J Schalkoff and Kevin E Satterfield and Gabriel U Martz and Ekrem Kutluay and Chad G Waters and Brian C Dean},
doi = {10.1097/WNP.0000000000000284},
year = {2016},
date = {2016-12-01},
journal = {Journal of Clinical Neurophysiology},
volume = {33},
number = {6},
pages = {530--537},
publisher = {LWW},
abstract = {Objective:
This purpose of this study was to evaluate the usefulness of a prototype battery-powered dry electrode system (DES) EEG recording headset in Veteran patients by comparing it with standard EEG.
Methods:
Twenty-one Veterans had both a standard electrode system recording and DES recording in nine different patient states at the same encounter. Setup time, patient comfort, and subject preference were measured. Three experts performed technical quality rating of each EEG recording in a blinded fashion using the web-based EEGnet system. Power spectra were compared between DES and standard electrode system recordings.
Results:
The average time for DES setup was 5.7 minutes versus 21.1 minutes for standard electrode system. Subjects reported that the DES was more comfortable during setup. Most subjects (15 of 21) preferred the DES. On a five-point scale (1—best quality to 5—worst quality), the technical quality of the standard electrode system recordings was significantly better than for the DES recordings, at 1.25 versus 2.41 (P < 0.0001). But experts found that 87% of the DES EEG segments were of sufficient technical quality to be interpretable.
Conclusions:
This DES offers quick and easy setup and is well tolerated by subjects. Although the technical quality of DES recordings was less than standard EEG, most of the DES recordings were rated as interpretable by experts.
Significance:
This DES, if improved, could be useful for a telemedicine approach to outpatient routine EEG recording within the Veterans Administration or other health system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Fridman, Igor; Cordeiro, Malaika; Rais-Bahrami, Khodayar; McDonald, Neil J; Jr, James J Reese; Massaro, An N; Conry, Joan A; Chang, Taeun; Soussou, Walid; Tsuchida, Tammy N
Evaluation of dry sensors for neonatal EEG recordings Journal Article
In: Journal of clinical neurophysiology: official publication of the American Electroencephalographic Society, vol. 33, no. 2, pp. 149, 2016.
@article{fridman2016evaluation,
title = {Evaluation of dry sensors for neonatal EEG recordings},
author = {Igor Fridman and Malaika Cordeiro and Khodayar Rais-Bahrami and Neil J McDonald and James J Reese Jr and An N Massaro and Joan A Conry and Taeun Chang and Walid Soussou and Tammy N Tsuchida},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4818163/},
year = {2016},
date = {2016-04-01},
journal = {Journal of clinical neurophysiology: official publication of the American Electroencephalographic Society},
volume = {33},
number = {2},
pages = {149},
publisher = {NIH Public Access},
abstract = {Introduction
Neonatal seizures are a common neurologic diagnosis in Neonatal Intensive Care Units (NICUs), occurring in approximately 14,000 newborns annually in the US. While the only reliable means of detecting and treating neonatal seizures is with an EEG recording, many neonates do not get an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include: 1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, 2) poor signal quality due to improper skin preparation and artifact, 3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not been previously evaluated on neonates.
Methods
Sequential and simultaneous recordings with wet and dry sensors were performed for one hour on 27 neonates from 35-42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude, and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined.
Results
Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8) given the non-superimposed sensor positions, and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically-relevant EEG background and seizure patterns. There was no skin injury after 1 hr of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix.
Conclusions
Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Arakaki, Xianghong; Shoga, Michael; Li, Lianyang; Zouridakis, George; Rostami, Ramona; Goldweber, Robert; Harrington, Michael
Exploring neuroplasticity in acute mild traumatic brain injury Journal Article
In: The FASEB Journal, vol. 30, pp. 992–4, 2016.
@article{arakaki2016exploring,
title = {Exploring neuroplasticity in acute mild traumatic brain injury},
author = {Xianghong Arakaki and Michael Shoga and Lianyang Li and George Zouridakis and Ramona Rostami and Robert Goldweber and Michael Harrington},
url = {https://faseb.onlinelibrary.wiley.com/doi/abs/10.1096/fasebj.30.1_supplement.992.4},
year = {2016},
date = {2016-04-01},
journal = {The FASEB Journal},
volume = {30},
pages = {992--4},
publisher = {The Federation of American Societies for Experimental Biology},
abstract = {Objectives
To explore neuroplasticity in a longitudinal study of acute mild traumatic brain injury (mTBI).
Methods
We are using quantitative electroencephalography (qEEG) and magnetoencephalography (MEG) during the resting state and during cognitive brain stress to explore neuroplasticity in an ongoing acute mild traumatic brain injury research. Acute mTBI patients are recruited from the emergency department of Huntington Memorial Hospital in Pasadena, CA, and controls are non‐head‐trauma patients. Brain stress includes the N‐back (0‐back and 2‐back) working memory test and Color‐Word Interference Test (CWIT), administered using E‐prime software. Data were collected at three time points: within 1 week of injury, 14 days, and 30 days after injury. Behavioral as well as MEG and qEEG analysis are performed to compare the two groups.
Results
Resting MEG detected low frequency activity in the mTBI group, consistent with previous publications. N‐back, in particular during 2‐back trials, and CWIT, in particular during incongruent trials, both show initial executive function impairment that improved on later visits. Time frequency analysis suggested corresponding compromised brain activity.
Conclusions
The EEG/MEG recordings during rest and brain stress are objective and sensitive to neuroplasticity in acute mTBI, and could be potential objective mTBI markers.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kang, Dayoon; Kim, Jinsoo; Jang, Dong-Pyo; Cho, Yang Seok; Kim, Sung-Phil
Investigation of engagement of viewers in movie trailers using electroencephalography Journal Article
In: Brain-Computer Interfaces, vol. 2, no. 4, pp. 193–201, 2015.
@article{kang2015investigation,
title = {Investigation of engagement of viewers in movie trailers using electroencephalography},
author = {Dayoon Kang and Jinsoo Kim and Dong-Pyo Jang and Yang Seok Cho and Sung-Phil Kim},
doi = {https://doi.org/10.1080/2326263X.2015.1103591},
year = {2015},
date = {2015-11-10},
journal = {Brain-Computer Interfaces},
volume = {2},
number = {4},
pages = {193--201},
publisher = {Taylor & Francis},
abstract = {Brain-computer interfaces (BCIs) have been focused on providing direct communications to the disabled. Recently, BCI researchers have expanded BCI applications to non-medical uses and categorized them as active BCI, reactive BCI, and passive BCI. Neurocinematics, a new application of reactive BCIs, aims to understand viewers’ cognitive and affective responses to movies from neural activity, providing more objective information than traditional subjective self-reports. However, studies on analytical indices for neurocinematics have verified their indices by comparisons with self-reports. To overcome this contradictory issue, we proposed using an independent psychophysical index to evaluate a neural engagement index (NEI). We made use of the secondary task reaction time (STRT), which measures participants’ engagement in a primary task by their reaction time to a secondary task; here, responding to a tactile stimulus was the secondary task and watching a movie trailer was the primary task. NEI was developed as changes in the difference between frontal beta and alpha activity of EEG. We evaluated movie trailers using NEI, STRT, and self-reports and found a significant correlation between STRT and NEI across trailers but no correlation between any of the self-report results and STRT or NEI. Our results suggest that NEI developed for neurocinematics may conform well with more objective psychophysical assessments but not with subjective self-reports.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Li, Lianyang; Pagnotta, Mattia F; Arakaki, Xianghong; Tran, Thao; Strickland, David; Harrington, Michael; Zouridakis, George
Brain activation profiles in mTBI: Evidence from combined resting-state EEG and MEG activity Conference
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE IEEE, Milan, Italy, 2015, ISSN: 1558-4615.
@conference{li2015brain,
title = {Brain activation profiles in mTBI: Evidence from combined resting-state EEG and MEG activity},
author = {Lianyang Li and Mattia F Pagnotta and Xianghong Arakaki and Thao Tran and David Strickland and Michael Harrington and George Zouridakis},
doi = {10.1109/EMBC.2015.7319994},
issn = {1558-4615},
year = {2015},
date = {2015-11-05},
booktitle = {2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
pages = {6963--6966},
publisher = {IEEE},
address = {Milan, Italy},
organization = {IEEE},
abstract = {In this study, we compared the brain activation profiles obtained from resting state Electroencephalographic (EEG) and Magnetoencephalographic (MEG) activity in six mild traumatic brain injury (mTBI) patients and five orthopedic controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar EEG/MEG sources on a dense grid on the cortical surface and then projected these sources on a standardized atlas with 68 regions of interest (ROIs). Averaging the PSD values of all sources in each ROI across all control subjects resulted in a normative database that was used to convert the PSD values of mTBI patients into z-scores in eight distinct frequency bands. We found that mTBI patients exhibited statistically significant overactivation in the delta, theta, and low alpha bands. Additionally, the MEG modality seemed to better characterize the group of individual subjects. These findings suggest that resting-state EEG/MEG activation maps may be used as specific biomarkers that can help with the diagnosis of and assess the efficacy of intervention in mTBI patients.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Kohli, Siddharth; Casson, Alexander J
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE Milan, Italy, 2015, ISSN: 1558-4615.
@conference{kohli2015towards,
title = {Towards out-of-the-lab EEG in uncontrolled environments: feasibility study of dry EEG recordings during exercise bike riding},
author = {Siddharth Kohli and Alexander J Casson},
doi = {10.1109/EMBC.2015.7318539},
issn = {1558-4615},
year = {2015},
date = {2015-11-05},
booktitle = {2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
pages = {1025--1028},
address = {Milan, Italy},
organization = {IEEE},
abstract = {Conventional EEG (electroencephalography) has relied on wet electrodes which require conductive gel to help the electrodes make contact with the scalp. In recent years many dry electrode EEG systems have become available that do not require this gel. As a result they are quicker and easier to set up, with the potential to record the the EEG in situations and environments where it has not previously been possible. This paper investigates the practicality of using dry EEG in new non-conventional recording situations. In particular it uses a dry EEG recording system to monitor the EEG while a subject is riding an exercise bike. The results show that good-quality EEG, free from high-amplitude motion artefacts, can be collected in this challenging motion rich environment. In the frequency domain a peak of activity is seen over the motor cortex (C4) at 23 Hz starting five minutes after the start of the exercise task, giving initial insights into the on-going operation of the brain during exercise},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
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}
}
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