@article{mahdid2020assessing,

title = {Assessing the Quality of Wearable EEG Systems Using Functional Connectivity},

author = {Yacine Mahdid and Uncheol Lee and Stefanie Blain-Moraes},

doi = {10.1109/ACCESS.2020.3033472},

issn = {2169-3536},

year  = {2020},

date = {2020-01-01},

journal = {IEEE Access},

volume = {8},

pages = {193214--193225},

publisher = {IEEE},

abstract = {Assessing the data quality of wearable electroencephalogram (EEG) systems is critical to collecting reliable neurophysiological data in non-laboratory environments. To date, measures of signal quality and spectral characteristics have been used to characterize wearable EEG systems. We demonstrate that these traditional measures do not provide fine-grained differentiation between the performance of four popular wearable EEG systems (the Epoc+, OpenBCI, DSI-24 and Quick-30 Dry EEG). Using two computationally inexpensive metrics of undirected functional connectivity (phase lag index) and directed functional connectivity (directed phase lag index), we compare the integrity of the phase relationships captured by wearable systems to those recorded from a high-density research-grade EEG system (Electrical Geodesics Inc). Our results demonstrate that functional connectivity analyses provide additional discriminatory information about wearable EEG systems, with clear differentiation of the cosine similarity between research-grade functional connectivity patterns and those generated by each wearable system. We provide a freely available Matlab toolbox containing all metrics described in this paper such that researchers and non-experts interested in wearable EEG systems can easily assess the quality of systems not characterized in this study, thus advancing the translation of EEG research into non-laboratory settings.},

keywords = {Comparisons, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@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 = {Comparisons, DSI-7},

pubstate = {published},

tppubtype = {article}

}

@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 = {Comparisons, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@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 = {Comparisons, qEEG},

pubstate = {published},

tppubtype = {article}

}

@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 = {Comparisons, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@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 = {Comparisons},

pubstate = {published},

tppubtype = {article}

}

@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 = {Cognitive-Algorithm, Comparisons, DSI-24},

pubstate = {published},

tppubtype = {article}

}