@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}

}

@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}

}

@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}

}

@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}

}

@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}

}