zetoadmin, Author at Zeto EEG

The Role of EEG for Epilepsy Diagnosis, Management and Classification

People with epilepsy typically experience recurrent seizures. Despite the diverse causes of seizures, the common mechanism linking many types of epilepsy is the disruption of the brain’s normal electrical activity, which temporarily halts communication between neurons.

About 60% of epilepsy cases have a cause, a lesion, or abnormality in the brain, detectable by neuroimaging methods [1,2]. Another class of pathogenesis of numerous epileptic symptoms is an abnormal expression of specific receptors in the brain, which leads to increased excitation and decreased inhibition resulting in enhanced neural activity.

Because epilepsy can only be diagnosed based on electrophysiological evidence (detection of two independent epileptic events by EEG tests) the use of EEG is mandatory for epilepsy diagnosis and management. Furthermore, based on the EEG evidence a trained epileptologist can determine the type of seizure and diagnose the type of epilepsy syndrome of the patients. The exact diagnosis can help to provide effective antiepileptic medication and prognosis.

Let’s find out the role of EEG in diagnosis, classification, and management in more detail. But first, let’s discuss what an EEG is.

What is EEG?

Electroencephalogram (EEG) is non-invasive research and diagnostic tool used to measure the changes of the brain’s electric potential over time, commonly called brain waves. This electric potential is generated by the discharges of millions of neurons. Although EEG does not have the spatial resolution of detecting the discharges of individual neurons, it can discern levels of activity associated with the major lobes of the human cerebral cortex. In other words, the EEG is a test that helps to detect electrical activity and abnormalities in a patients’ brain and localize them with a certain precision sufficient to make a diagnosis. An EEG equipment uses small sensors (electrodes) made of a conductive material attached to the scalp or they contact the skin. Often these electrodes are preconfigured inside an EEG headset to speed up the positioning.

Typically, specialists, clinical neurophysiologists, neurologists, and researchers carry out an EEG recording. Traditionally it has been done in clinics or academic laboratories and also has been adapted for home monitoring. While EEG has numerous research applications from basic research to Brain-Computer-Interface (BCI), in the field of clinical neurology it is mainly used to diagnose and monitor epilepsy and sleep disorders.

Diagnosis, Classification, and Patient Management

Diagnosis and treatment of epilepsy are often challenging. However, modern therapy provides many patients with multiple treatment options and often complete control of the seizure. After the first two seizures, evaluation should concentrate on:
1. Ruling out any non-epileptic medical or neurological condition that may generate seizures (e.g., psychogenic seizures)
2. Determine the type and location of seizures (e.g., focal, generalized, convulsive, non-convulsive)
3. Evaluating the relative risk of a seizure episode
4. Evaluating treatment options (e.g., diet, pharmacological treatment, surgical intervention, implanted control device)

The Use of EEG in Diagnosis of Epilepsy

Regardless of technological advancements, the first seizure episode typically is not captured in EEG. Numerous paroxysmal events can be confused with epileptic seizures, such as movement disorders, syncope, psychogenic seizures, etc. Probably, the most common event confused with epileptic seizures is syncope. To rule out non-epileptic seizures one needs to record abnormal activity from the brain as primary evidence. This is done by EEG equipment because all other methods to record brain activity are more expensive. At the same time, it is generally recommended to carry out a brain imaging study, such as magnetic resonance imaging (MRI). The MRI can reveal underlying cerebral lesions such as a tumor, stroke, vascular malformation, that could explain the seizure and also help localize it. However, not all epileptic seizures are associated with morphological differences in the brain that can be resolved by MRI. The class of epilepsy associated with electrographic seizures without visually observed MRI evidence is called non-lesional epilepsy.

The Vital Role of EEG in Epilepsy Diagnosis

Why does EEG play a central role in epilepsy diagnosis and treatment? Because EEG can:

● detect epileptiform activity,
● strengthen the putative diagnosis,
● identify the focal cerebral abnormalities, which may indicate a focal structural anomaly such as brain tumor, hemorrhage, vascular malformation and
● document particular epileptiform activity patterns linked to specific epilepsy syndromes

Trained clinicians can recognize a particular type of epilepsy based on their signature waveforms and distribution using an EEG device. Each type of epilepsy diagnosis entails specific treatment strategies. Typical EEG results provide a multiaxial diagnosis of epilepsy describing whether the seizure disorder is generalized or focal, symptomatic or idiopathic (unknown cause), or part of a particular epilepsy syndrome. Because no two epilepsy cases are identical, providing a detailed description of the type of epileptic waveforms, the topography (location in the brain), the frequency of occurrences, the triggering stimulus if there is any, and the effect of seizure on the cognitive and motor functions are all important aspects shaping the treatment strategy.

One critical aspect of epileptic seizures that can be captured by an EEG study is whether it is generalized or focal. The two require completely different medication and treatment strategies. In the case of generalized seizures, abnormal synchronized discharges quickly spread to both cerebral hemispheres, while in focal seizures the abnormal discharges remain localized to a certain area or areas. To capture these events, one needs to spend hours or days with a continuously recording EEG because these events are rare unless it is triggered by a known stimulus (light, sound, touch, anxiety, hyperventilation, etc.).

Because of the scarcity and unpredictable nature of epileptic seizures, these events may not be captured in the clinic during the EEG. However, the description of a seizure by a witness combined with the patient’s self-report can complement the information available from EEG. Abnormal EEG activity patterns that indicate the potential for seizures are called inter-ictal events (sharp waves and spike and waves). These events play an important role in localizing and seizures. Today, a lot of attention is paid to interictal events as potential biomarkers of an impending seizure. One of the biggest machine learning challenges in medicine is to predict seizures based on the types and occurrences of these interictal events.

The role of EEG in Classification of Epilepsy

The classification of epilepsy and the recognition of diagnostic categories based on EEG is an ongoing, evolving process. The categories we use today are not the same as the ones we used 30 years ago, and they change as we understand the disease better. We tend to overclassify epilepsy syndromes as each is associated with particular EEG features. Therefore, it is the task of an internationally elected committee of experts ”International League Against Epilepsy (ILAE” to update the classification systems from time to time, based on consensus and published empirical evidence [3]. Because the classification is evidence-based, and evidence is subject to technological advances, the EEG and other methods, such as neuroimaging, molecular biology, and genomics have a great impact on the classification progress. And will be informed as times go on by developments in imaging, molecular biology, and genetics.

The role of EEG in Management of Epilepsy

The main objective for treating epilepsy patients is to control seizures entirely without causing undesirable side effects. Therefore, besides EEG being an indispensable part of diagnosis, it is also necessary for epilepsy management. Until today the primary measure of the efficacy of epileptic drugs was the extent it reduces seizure frequency. This assessment was often based on self-reports, diary, and caretakers’ notes. With the widespread availability of EEG, this is expected to change and EEG could be utilized for quantifying the efficacy of any treatment, from drug therapy to special diets.

Conclusions

Patients diagnosed with epilepsy have more therapeutic options available to them today than yesterday. To maximize the benefit of these options, clinicians must make an accurate diagnosis of epilepsy syndrome, select and use medications effectively, and promptly refer patients where necessary.

Among the broad range of available diagnostic methods, EEG is still the most versatile and affordable research and diagnostic tool that helps study the brain’s electrical activity and recognize patterns associated with epilepsy. Most importantly EEG provides detailed information about the type and localization of epilepsy.

While it has a very limited spatial resolution and is prone to misinterpretation, EEG remains the gold standard of epilepsy diagnosis. It is and it will remain in the equation to provide better care for patients and to feed our curiosity about the inner workings and communications of brain tissue.

References:

1. Nguyen DK, Mbacfou MT, Nguyen DB, Lassonde M. Prevalence of nonlesional focal epilepsy in an adult epilepsy clinic. Can J Neurol Sci. 2013 Mar;40(2):198-202. doi: 10.1017/s0317167100013731. PMID: 23419568.
2. Téllez-Zenteno JF, Hernández Ronquillo L, Moien-Afshari F, Wiebe S. Surgical outcomes in lesional and non-lesional epilepsy: a systematic review and meta-analysis. Epilepsy Res. 2010 May;89(2-3):310-8. doi: 10.1016/j.eplepsyres.2010.02.007. Epub 2010 Mar 15. PMID: 20227852.
3. https://www.ilae.org/guidelines/definition-and-classification/proposed-classification-and-definition-of-epilepsy-syndromes

Active And Passive Electrodes – What Are They, Pros & Cons

When the British physician Richard Caton first recorded the brain’s electrical activity on a rabbit in the late 19th century he didn’t know his groundbreaking experiment would inspire the invention of a line of revolutionary technologies that turned out to be indispensable assets of neuroscience. One of those inventions is Hans Berger’s electroencephalography (EEG), which transformed the diagnosis of neurological conditions. Since then EEG has gone through several advancements, of which a key one is active EEG electrodes.

Because every innovation comes with certain pluses and minuses, it is of primary importance to clarify them for users. The guiding principle of any EEG innovation is to improve the quality of signals recorded from the brain while balancing usability and user comfort. Only after fully understanding these pros and cons could one make the right choices for their use case be it clinical, research, or other.

What are Active and Passive Electrodes?

The brain’s electrical activity (brain potential) is a sum of the myriad discharges generated from neuronal action potentials. Although a single action potential is detectable in the millivolt (mV) range, the combined effect of a large population of neurons on the voltage of the brain tissue relative to a neutral point is the sum of all action potentials. Because of the inherent stochasticity of these action potentials, the simultaneous positive and negative fluctuations cancel each other. Therefore, the net voltage fluctuation in the brain tissue is a fraction of that of the neuron, yielding to a fluctuation in the microvolt (uV) range. Fortunately, neurons often act in concert to achieve effective control of target tissues. When they do so, the millions of action potentials synchronize in oscillatory patterns like flocking birds synchronize their flying. Those oscillations form traveling waves over the surface of the cerebral cortex penetrating the skull and yielding to discernable voltage fluctuation over the scalp, a signal known as EEG.

To noninvasively capture the brain’s electric potential fluctuations over the skull, two different EEG electrode technology options are available. One is passive electrodes and the other is active electrode technology. Passive electrodes are traditional EEG electrodes that simply transmit the voltage fluctuation to the amplifier through a conductive wire. To attain a low-impedance contact we use Silver-Silver Chloride (Ag/AgCl), or gold electrodes. However, the need for skin preparation to achieve a low enough impedance (under 10Kohm), the cost of the electrodes (~$10/electrode), the labor-intensive gluing method, the inconvenience to the patient, and most importantly the increasing cases of skin breakdown encouraged innovation in EEG electrode technology. A well glued gold-cup EEG electrode on a clean exposed skin surface with an adequate amount of electrode paste on a relaxed motionless subject in an electromagnetically shielded room, with the amplifier a few feet (1-2 m) distance from the subject, can provide a relatively clean EEG, that shows discernible delta, theta, alpha, beta oscillations in the EEG. These oscillations originate from the brain, hence passive electrode technology was for a while the ultimate low-cost, noninvasive brain activity monitoring modality for extensive clinical and research purposes.

Active electrode technology was developed partly in response to not needing skin preparation. The second factor was to prevent the weak EEG signal from being contaminated by noise while traveling through the long wire. The solution to handle both was moving a part of the amplifier as close as possible to the electrode thereby buffering the signal close to the scalp (Fig. 1). Because in the case of active electrode implementation the cables carry a signal driven strongly by the pre-amplifier which makes it less susceptible to electromagnetic interference thereby improving the signal to noise ratio. A high input impedance pre-amplifier also mitigates the need for abrading skin or using conductive paste in order to drop skin impedance.

Figure 1. The graphical scheme of conventional EEG with an instrumentation amplifier before the backend (a) versus the active electrode solution where the amplifiers are placed proximal to the electrodes (From Xu et al., 2017).

The Active electrode has two components, the electrode, and the preamplifier circuit. The electrode materials need to be carefully chosen so as to not have polarization effects and are typically silver/silver chloride (Ag-AgCl). The performance of such a dry-active electrode array was first demonstrated at the University of California, Davis, by Babak Taheri in the 1990s.

Passive electrodes, in contrast, are generally plated with Ag-AgCl or gold and need electrolytic paste or gel (they are frequently called wet electrodes for this reason). However, the scalp is first prepared to minimize electrode-scalp impedance which is recommended to be under 10Kohm.

A report of the construction, performance, and results of the first dry-active electrode appeared in a 1994 scientific publication. One of the initial observations made was the fact that the arrayed active electrodes outperformed the passive electrodes.

To understand how active electrodes could achieve such a good performance we need to compare the underlying signal transmissions implemented by these two types of EEG electrodes.

Pros And Cons of Active and Passive EEG Electrodes

Active and Passive Electrodes Pros

Active electrodes allow pre-amplification modules close to the electrode. Hence, these EEG electrodes enable signal amplification before any extra noise attacks the EEG signal.

Active electrodes can make a big difference in a multitude of scenarios. First and most important, they enable the use of dry electrodes. Dry electrodes, in general, are associated with higher noise levels because they are not glued to the skin surface nor do they use a conductive gel that creates a low impedance bridge between the skin and the EEG electrodes.

Likewise, active electrodes do great when the measurement occurs in areas with fair amounts of electromagnetic noise and when there will be a considerable distance between the system and the electrodes used for EEG.

For passive electrodes, a conductive gel is a must to minimize impedance, so as to enable the signal to travel reliably through the wire. Moreover, during extended usage of wet passive electrodes, the gel may dry up leading to poor quality of the recording.

Active and Passive Electrodes Cons

On the other hand, passive electrodes are simpler to manufacture, and they cost and weigh less as they lack the pre-amplification modules that active electrodes have. Active electrodes also require more wires (additional power and ground) to enable the functioning of the pre-amplifier. Passive electrodes can achieve very good performance when the electrode has a stable low impedance.

Comparing Active and Passive EEG Electrodes in Amplification System Test

A growing number of studies demonstrated a superior signal quality of active electrodes over passive electrodes. When the active electrode technology is applied to dry electrodes, it can compensate for the higher impedance of the dry electrodes and achieve equivalence with the gel-loaded passive electrodes with all the benefits deriving from the active electrodes.

The illustration below was taken from a study involving 8 participants after recording EEG reading following the emission of auditory stimuli.

Source | INMHC

The reading produced by the active electrodes was instantaneous in response to the Event-Related Potentials (ERPs) recorded after the emission of the auditory stimulus. Furthermore, there was a significantly reduced error in the voltage difference between the EEG electrodes’ recorded measurement and the reference signal.

Another study compared the active and passive electrodes in an ERP during cognitive tasks (Laszlo et al., 2014). The study involved two experiments. In the first experiment, researchers manipulated interelectrode impedance in an electrically quiet setting to check if active electrodes produced better results under such recording conditions. In the second experiment, they studied active electrodes’ ability to record when limited by natural skin impedance. The investigation also explored the relationship between voltage stability and active amplification circuitry in EOG. Results from both experiments showed complicated connections between voltage stability, electrode types, and impedance. Ultimately, the study indicated that active electrodes outperformed passive electrodes at different impedance levels except for very low ones. To be specific, passive electrodes obtained higher quality data only when impedance was less than 2 kΩ. That said, it’s worth noting that passive ones also were better at accurately following the EEG than active ones in the event of rapid voltage fluctuations.

Conclusion

The quality of EEG recordings depends on several factors. Whether you prefer to use an active electrode EEG system or not, it is vital to know the pluses and minuses. Active electrode technology when used with high-quality electrodes (e.g., gold-plated) with conductive paste provides the best of both worlds, i.e., low skin impedance and a well-driven signal that is less susceptible to noise. However, in such cases when these electrode wires need to be disposed of due to wear and tear along with the pre-amplifier assembly, the cost could become prohibitively expensive. Hence active electrodes most commonly enable the use of dry electrode EEG systems, which allows you to reuse the EEG cap and dispose of just the electrodes. Such wireless EEG systems also enable the fast and easy setup of EEG without elaborate prep work. Signal quality in such cases has shown to be as good or in some cases better than just conventional passive electrodes. In summary, active electrode technology always makes the EEG signal quality better. They cost more because of the additional circuitry and wires needed. If disposed of with the electrode wires, they could be too expensive; however, if reused with a cap-like system, the cost is not a concern. With costs dropping fast for such commodity parts, there is adequate reason to believe active electrodes will replace passive ones in the next few years.

REFERENCES:

1) Xu J, Mitra S, Van Hoof C, Yazicioglu RF, Makinwa KAA. Active Electrodes for Wearable EEG Acquisition: Review and Electronics Design Methodology. IEEE Reviews in Biomedical Engineering. 2017 ;10:187-198. DOI: 10.1109/rbme.2017.2656388.

2) Kelly, J. W., Siewiorek, D. P., Smailagic, A., & Wang, W. (2013). Automated filtering of common-mode artifacts in multichannel physiological recordings. IEEE transactions on bio-medical engineering, 60(10), 2760-2770. https://doi.org/10.1109/TBME.2013.2264722

3) Laszlo S, Ruiz-Blondet M, Khalifian N, Chu F, Jin Z, A direct comparison of active and passive amplification electrodes in the same amplifier system, Journal of Neuroscience Methods, 2014, Volume 235, 298-307, https://doi.org/10.1016/j.jneumeth.2014.05.012.

Comparison of Dry Electrode EEG System with Conventional EEG System

The dry electrode EEG system is a new development in the field of diagnostic science, offering an alternative to the conventional wet electrode EEG system.

To replace the wet EEG setup in clinical settings, dry electrode headsets must convey high-quality signals and give accurate results in terms of latency and amplitude. The dry electrode systems must also be able to separate biological signals from background noise.

Before comparing these two approaches, it is important to understand how each one of them works.

A brief overview of the wet EEG device

The traditional EEG system consists of small metal discs (electrodes), covered with a silver/silver-chloride coating, which are placed on the scalp. Some recording systems use elastic head caps, which have electrodes built-in in preset positions, expediting the correct electrode placement according to the 10-20 international standard, assuming a proportional expansion and distribution of electrodes over different head sizes.

Other, more traditional approaches, place single leads on the scalp one at a time using glue, gauze, and tape. An electrode gel is applied to the skin under the electrode to improve the skin-electrode conductivity and to reduce impedance. It also decreases the artifacts produced by the movements of electrode cables.

Once the electrodes are positioned, it often requires scraping the surface of the skin using various tools to remove the upper layer of skin to improve the conductivity between the skin and the gel.

Then the electrode is ready for recording the brain’s electrical activity and analyzing the data for diagnostic purposes.

A brief overview of the dry EEG device

In contrast to traditional electrodes, dry EEG systems make contact directly with the scalp and do not require conductive gel to be applied between the skin and electrode. That is made possible because of additional system components that increase the EEG signal strength right at the scalp.

Since they do not require any skin preparation, dry electrodes make the EEG headset suitable for rapid EEG tests, eventually, beyond healthcare facilities. The dry electrodes are easy to place without the help of any additional instruments like syringes or gel cans.

Moreover, after use, there is no need to clean the head as dry electrodes leave no residue on the skin or on the hair. Because dry electrodes are often made of plastic, they are affordable and can be made disposable, hence their use is a lot more hygienic and safer to be transferred between patients than traditional multiple-use electrodes.

Comparison of the dry and wet EEG system

The main purpose of introducing dry electrodes to be used in EEG systems was to improve the comfort of patients and experimental subjects while reducing the time of preparation. The dry electrodes are cleaner, more comfortable, quicker to set up and quicker to remove. In short, they are more practical.

In addition to convenience and comfort, there are additional requirements a good clinical electrode has to meet.

An ideal dry EEG headset should stay on the patient’s head for hours to days or even weeks or more to ensure uninterrupted monitoring of the brain’s electrical activity.

To achieve this in clinical practice, EEG technicians glue the electrodes one by one to the skin with a collodion adhesive, apply the gel and cover the electrodes with a gauze bandage. The drawback of this method is that the gel dries quickly and needs to be replaced every few hours, which requires a trained EEG technologist to do as the head bandage needs to be replaced too.

Therefore, while this type of traditional wet electrode system is acceptable in the clinical settings where EEG technologists are available around the clock, this dependency on skilled labor makes EEG underutilized in many clinical areas, such as ICU, ED, NICU, and stroke centers, to name a few.

In contrast, dry electrode systems do not require an EEG technologist’s assistance to replace the electrodes. Introducing dry electrodes to clinical EEG monitoring, including long-term EEG, would not only free up the time of EEG technologists for EEG monitoring and allow them to complete more EEG studies but would also expand the use of EEG in clinical areas and clinics lacking EEG specialists on site.

Acceptance of the dry electrode systems in the clinical EEG market

Although dry electrode EEG headset systems have multiple advantages over gel-based electrodes, there is a barrier to widespread acceptance.

According to conventional wisdom, the lower the impedance of electrodes the better the quality of the recording is. However, recent technological advances have brought about a new generation of amplifiers capable of amplifying the signal orders of magnitude better than conventional systems and overcoming the impedance-gap of dry electrodes.

In addition, the introduction of active electrode technology, i.e. giving the EEG signal more strength by pre-amplifying the signal close to the electrode, ensures that the biological signal will not be affected by external electromagnetic noise before reaching the second amplifier stage. Conventional EEGs use passive electrodes, which makes the few micro-volt magnitude signals traveling in long cables from the electrode to the amplifier susceptible to electromagnetic noise especially upon movement of the cables.

Moreover, the active electrodes technology applies a driven current to each electrode that is being modulated by the brain’s electrical activity. The modulated signal will be detected by the electrodes and transferred to the amplifiers where the driven current will be subtracted from the signal to recover the brain’s original signal.

In addition to active electrode technology, dry electrode systems need good noise shielding and noise cancellation. As the biosignal travels through ‘unprepared’, high impedance skin layer, it becomes vulnerable to external noise such as 60Hz lines noise or other electrical interference in the room. Hence excellent shielding mechanisms are needed to protect the electrodes.

Moreover, the system needs to incorporate dynamic common mode noise rejection circuitry to improve CMRR (Common Mode Rejection Ratio) above 130dB which allows signal quality to be on par with traditional wet EEG systems.

The Benefits of Dry EEG Headsets

The combination of these technologies makes dry electrodes not only on a par with conventional electrode recording quality but able to exceed that.

As of today, many well-controlled and peer-reviewed studies have proven that dry electrode EEG headset systems are non-inferior to the conventional EEG and they are rapidly improving (Guger, Krausz, Allison, & Edlinger, 2012) (Di Flumeri et al., 2019; Fiedler et al., 2014; Hinrichs et al., 2020; Kam et al., 2019; Leach, Chung, Tüshaus, Huber, & Karlen, 2020; Li, Wu, Xia, He, & Jin, 2020; Mathewson, Harrison, & Kizuk, 2017; Schwarz, Escolano, Montesano, & Müller-Putz, 2020; Shad, Molinas, & Ytterdal, 2020; Zander et al., 2011).

The complicated nature of wet EEGs means they’re limited in the number of people they can reach. Extensive prep is needed, and this requires EEG technologists on hand at every step of the way. This limitation means EEGs can’t be rolled out in many settings where they can be most useful (ICU, ED, NICU, stroke centers, etc).

Dry EEG headsets solve this problem by making the setup simple. The average prep time is just five minutes, and the headset is comfortable for the patient, with gentle support pads making the process much more pleasant.

Of course, this wouldn’t be useful unless the results were accurate, and this is where the hard work has gone on behind the scenes. With technological improvements, studies are showing that results from EEG headsets are on par with conventional EEGs.

By combining accurate results with much-improved convenience, dry EEG headsets represent a great step forward in the way we can study the brain.

Zeto Wireless EEG Headset

The Zeto wireless EEG headset is the first FDA-approved true dry electrode EEG system.

Traditional EEG systems have clear drawbacks, and many hospitals and clinics have been eagerly awaiting a better EEG testing option. That options arrived in 2020, as Zeto’s EEG headset brought new levels of convenience combined with exceptionally accurate results.

The headset offers:

Wireless, battery-powered
No skin-prep, no cleanup
Comfortable, no residue, soft tip electrodes
Adjustable headset for child to adult sizes
Precision placement as per 10-20 system
Easy to learn for anyone familiar with EEG

Live remote viewing of video EEG can be accessed through the cloud allowing for seamless data management, and a mobile EEG system.

Don’t be limited by a shortage of EEG technologists, discover the Zeto wireless EEG headset.

Infographic – Comparison of Dry Electrode EEG System with Conventional System

References

Di Flumeri, G., Aricò, P., Borghini, G., Sciaraffa, N., Di Florio, A., & Babiloni, F. (2019). The Dry Revolution: Evaluation of Three Different EEG Dry Electrode Types in Terms of Signal Spectral Features, Mental States Classification and Usability. Sensors (Basel, Switzerland), 19(6), 1365. https://doi.org/10.3390/s19061365

Fiedler, P., Haueisen, J., Jannek, D., Griebel, S., Zentner, L., Vaz, F., & Fonseca, C. (2014). Comparison of three types of dry electrodes for electroencephalography. In Acta IMEKO. https://doi.org/10.21014/acta_imeko.v3i3.94

Guger, C., Krausz, G., Allison, B., & Edlinger, G. (2012). Comparison of Dry and Gel Based Electrodes for P300 Brain–Computer Interfaces. Frontiers in Neuroscience, 6, 60. https://doi.org/10.3389/fnins.2012.00060

Hinrichs, H., Scholz, M., Baum, A. K., Kam, J. W. Y., Knight, R. T., & Heinze, H. J. (2020). Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications. Scientific Reports. https://doi.org/10.1038/s41598-020-62154-0

Kam, J. W. Y., Griffin, S., Shen, A., Patel, S., Hinrichs, H., Heinze, H.-J., … Knight, R. T. (2019). Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes. NeuroImage, 184, 119–129. https://doi.org/10.1016/j.neuroimage.2018.09.012

Leach, S., Chung, K., Tüshaus, L., Huber, R., & Karlen, W. (2020). A Protocol for Comparing Dry and Wet EEG Electrodes During Sleep. Frontiers in Neuroscience, 14, 586. https://doi.org/10.3389/fnins.2020.00586

Li, G.-L., Wu, J.-T., Xia, Y.-H., He, Q.-G., & Jin, H.-G. (2020). Review of semi-dry electrodes for EEG recording. Journal of Neural Engineering, 17(5), 51004. https://doi.org/10.1088/1741-2552/abbd50

Mathewson, K. E., Harrison, T. J. L., & Kizuk, S. A. D. (2017). High and dry? Comparing active dry EEG electrodes to active and passive wet electrodes. Psychophysiology, 54(1), 74–82. https://doi.org/10.1111/psyp.12536

Schwarz, A., Escolano, C., Montesano, L., & Müller-Putz, G. R. (2020). Analyzing and Decoding Natural Reach-and-Grasp Actions Using Gel, Water and Dry EEG Systems. Frontiers in Neuroscience, 14, 849. https://doi.org/10.3389/fnins.2020.00849

Shad, E. H. T., Molinas, M., & Ytterdal, T. (2020). Impedance and Noise of Passive and Active Dry EEG Electrodes: A Review. IEEE Sensors Journal, 20(24), 14565–14577. https://doi.org/10.1109/JSEN.2020.3012394

Zander, T., Lehne, M., Ihme, K., Jatzev, S., Correia, J., Kothe, C., … Nijboer, F. (2011). A Dry EEG-System for Scientific Research and Brain–Computer Interfaces. Frontiers in Neuroscience, 5, 53. https://doi.org/10.3389/fnins.2011.00053

A Guide to EEG Basics (Electroencephalography) & Devices Used

Every machine requires some circuitry or motherboard that controls the machine’s functions and operations. Likewise, humans also possess a complex computing system inside the body: the brain. The brain’s inner workings and connections are mysterious. An intricate system of neurons link together to form the brain’s jelly-like morphology.

Advancements in medical science and inventions have improved our understanding of how the brain works. One such invention was electroencephalography, a method and device used to record and analyze the electrical activity occurring inside the brain.

While the first EEG was performed in 1924, the technology is constantly evolving. Today, modern portable EEG devices are changing the way we look at the brain.

In this EEG guide, you’ll learn what an EEG machine is, what an electroencephalography is, how the EEG system operates, and what the various devices are used for.

What is Electroencephalography (EEG)?

Electroencephalography 1, or EEG, is a procedure used to measure and record the electrical activity of the brain in the form of waves. One can monitor the neurophysiological function of the brain while the subject is performing different tasks. Various electrical abnormalities can also be detected with precision.

As we understand the brain better, our EEG technology and the way we interpret the signals of the brain continue to improve. This has led to new ways of performing EEGs, such as wireless EEG systems that allow us to continue to learn the secrets of the brain.

What is an EEG?

Our brain is composed of billions of interconnected neurons. These neurons work by generating electrical potentials in the form of neuronal impulses which travel through the brain. EEG works on the principle of measuring these electrical potentials/voltages generated inside the brain.

What is an EEG Machine?

An EEG machine measures these electrical potentials by recording the differences in voltage between various points using a pair of electrodes. Then, the recorded data is sent to an amplifier.

The amplified data is eventually digitized and displayed on the monitor of the EEG machine as a sequence of voltage values that fluctuate in time. The resulting EEG waveforms from the EEG machine are interpreted to detect signs of abnormality inside the brain.

Parts of an EEG Machine

Essentially, an EEG machine is made up of the following primary device(s):

Electrodes: The electrodes pick up small electrical brainwaves produced by neurons. These are attached to the scalp with a special paste. Modern EEG machines possess a wearable cap with electrodes pre-installed inside the cap.
Amplifiers: As the signals travel from the electrodes through the machine, they run through an amplifier that boosts the incoming signal enough to be displayed on the screen.
Computer Control Module: The amplified signals are processed by a computer.
Display Device: The processed signals are displayed on the screen to be analyzed by the operator. Before the digital monitoring methods became prevalent, waveforms were plotted with a moving pen on rolls of graph paper.3

How is an EEG performed?

An EEG test may be performed either as an outpatient study or as part of your stay in the hospital. Various EEG technology and techniques are used depending on your health condition. Generally, an EEG procedure utilizing EEG technology is done in the following way:

The patient is asked to relax by lying on a bed or sitting in a chair.
Various electrodes (between 16, 20, or more) are attached to the scalp using a special electrolyte paste, or the patient is fitted with a cap containing the electrodes.
The patient is then asked to close their eyes and remain still.
Generally, an EEG technologist performs this procedure, which may take from 20 minutes to 2 hours, not including the electrode prepping.
Longer brain monitoring requires the patient to be admitted to the hospital.4

Modern technology has helped make this process easier in recent years. Today, portable EEG devices offer maximum convenience without compromising the quality of the results.

For the EEG operator, this brings down prep times (it’s easy to put on and adjust, and there’s no messy glue or wires to clean up), and for the patient, this offers increased comfort (the soft support pads are gentle on the skin).

Also known as rapid EEGs, these devices make EEG technology much more accessible, allowing more people to benefit from it. The portable EEG machine sends results to the Zeto app, allowing practitioners to access live results from anywhere.

We’re still working hard to understand the human brain, and many mysteries remain, but with each technological improvement in EEG machines, we take a step closer to solving the puzzle of the human brain. Portable EEG machines allow us to study the brain more efficiently, offering benefits to researchers, practitioners, and patients.

What Does an EEG Measure?

At its most basic, an EEG measures brainwaves. Electrical signals generated by the brain are displayed on the screen in the form of waves that vary in amplitude, phase, and frequency.

Fast Fourier Transform (FFT) and other signal processing techniques convert the incoming signals measured by the EEG into useful information that can aid diagnosis. Brainwaves are categorized into four main types based on frequency: Infra-low, Delta, Theta, Alpha, Beta, and Gamma.

Each brainwave is associated with particular functions of the brain. The following paragraphs discuss the various important functions of the brain in correlation with the types of brainwaves.

Delta Waves (frequency ranging from 0.5 Hz to 3 Hz)

Delta waves are slow but loud brainwaves (like the deeply penetrating waves of a drum beat). They are generated during dreamless sleep. Delta waves are intermittent with sleep spindles and sharp waves. When delta waves synchronize between distant cortical areas, they often trigger sharp waves that are considered to be relevant for memory consolidation. 6

Theta Waves (frequency ranging from 3 Hz to 7 Hz)

Theta waves mostly occur during REM sleep. They derive from deep subcortical sources, making them mostly undetectable with an EEG machine. The predominant occurrence of theta is pathological. Normal theta waves are known to be involved in learning and memory. In theta state, we experience dreams comprising vivid imageries and intuitions. 7

Alpha Waves (frequency ranging from 7 Hz to 13 Hz)

Alpha waves occur when the person is in a relaxed, lucid, or calm state. These are mostly found in the occipital and posterior regions of the brain. Whenever someone is asked to close his/her eyes and then relax, the brain is disengaged from any complex cognitive tasks or thinking, and alpha waves are induced. 8

Beta Waves (frequency ranging from 14 Hz to about 38 Hz)

Beta waves refer to the alert, attentive, and conscious state of mind. These are of low amplitude and are also associated with motor decisions. Beta waves are further subdivided into:

Low-Beta Waves (Beta1, 12-15 Hz): occur while musing
Mid-Beta Waves (Beta2, 15-22 Hz): occur while engaging intensely in something or actively figuring something out.
High-Beta Waves (Beta3, 22-38 Hz): occur during complex thoughts and integration of new experiences. Also related to severe anxiety or excitement. 9

Gamma Waves (frequency ranging from 38 Hz to 120 Hz)

These are the fastest of all the brainwaves with the highest frequency and smallest amplitude. Because of the small amplitude and high frequency, they are often contaminated by electrical noise or muscle artifacts.

If gamma waves are captured and measured by EEG, they inform us about information processing in the brain.10 The synchrony of gamma waves between different parts of the brain reflects information exchange between those areas. Gamma waves still remain a mystery as these waves orchestrate the synchronized activity of neurons.

Low-Gamma Waves (38-60 Hz): Active attentive behavior and cognitive tasks
High-Gamma Waves (60-120 Hz): Their function is not quite clear, but the predominant occurrence is regarded as diagnostic of epilepsy.

What Does an EEG Test Diagnose?

EEG technology is currently used to diagnose and help treat brain-related disorders.

EEG is the most powerful and preferred diagnostic procedure for epilepsy.13
EEG is very helpful in diagnosing sleep disorders such as insomnias, parasomnias, etc.14
EEG has valuable diagnostic potential for other neurological conditions such as Stroke, Autism, Depression, and ADHD, to name a few.
EEG is turning out to be the tool for the next generation of Brain-Computer Interfaces and Neural Prosthetics
EEG can be used to track attention during several activities, to help design strategies to reduce stress and improve focus.15
EEG has been introduced as a new tool for Neuromarketing studies to help objectively identify participants’ responses.

And the list is growing…

The Bottom Line

The invention of the EEG system opened a new window of learning about the brain. With the EEG system to guide them, neurologists have been able to successfully treat seizures, epilepsy, sleep disorders, and other neurological issues.

As EEG becomes simpler, easier to acquire and interpret, and wireless, even more can be achieved. With new advancements in electronics, cloud computing, and machine learning, it is just a question of how soon.

The future of EEG is bright. Consequently, the advancements in our understanding of the brain cannot be more exciting. Learn more about wet vs. dry EEG tests here.

References

1. Electroencephalogram (EEG) | Johns Hopkins Medicine. https://www.hopkinsmedicine.org/health/treatment-tests-and-therapies/electroencephalogram-eeg.

2. Introduction – Electroencephalography (EEG): An Introductory Text and Atlas of Normal and Abnormal Findings in Adults, Children, and Infants – NCBI Bookshelf. https://www.ncbi.nlm.nih.gov/books/NBK390346/.

3. Wang, C. S. Design of a 32-channel EEG system for brain control interface applications. J. Biomed. Biotechnol. 2012, (2012).

4. Light, G. A. et al. Electroencephalography (EEG) and event-related potentials (ERPs) with human participants. Current Protocols in Neuroscience vol. CHAPTER Unit (2010).

5. Watson, B. O. Cognitive and physiologic impacts of the infraslow oscillation. Frontiers in Systems Neuroscience vol. 12 44 (2018).

6. Harmony, T. The functional significance of delta oscillations in cognitive processing. Frontiers in Integrative Neuroscience vol. 7 (2013).

7. Zhang, H. & Jacobs, J. Traveling theta waves in the human hippocampus. J. Neurosci. 35, 12477-12487 (2015).

8. Klimesch, W. Alpha-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences vol. 16 606-617 (2012).

9. Beta Wave – an overview | ScienceDirect Topics. https://www.sciencedirect.com/topics/medicine-and-dentistry/beta-wave.

10. Gamma Wave – an overview | ScienceDirect Topics. https://www.sciencedirect.com/topics/neuroscience/gamma-wave.

11. Michal T. Kucewicz, Brent M. Berry, Vaclav Kremen, Benjamin H. Brinkmann, Michael R. Sperling, Barbara C. Jobst, Robert E. Gross, Bradley Lega, Sameer A. Sheth, Joel M. Stein, Sandthitsu R. Das, Richard Gorniak, S. Matthew Stead, Daniel S. Rizzuto, Michael J. Kahana, Gregory A. Worrell, Dissecting gamma frequency activity during human memory processing, Brain , Volume 140, Issue 5, May 2017, Pages 1337-1350, https://doi.org/10.1093/brain/awx043

12. Ren, L., Kucewicz, M. T., Cimbalnik, J., Matsumoto, J. Y., Brinkmann, B. H., Hu, W., Marsh, W. R., Meyer, F. B., Stead, S. M., & Worrell, G. A. (2015). Gamma oscillations precede interictal epileptiform spikes in the seizure onset zone. Neurology , 84 (6), 602-608. https://doi.org/10.1212/WNL.0000000000001234

13. Smith, S. J. M. EEG in the diagnosis, classification, and management of patients with epilepsy. Neurology in Practice vol. 76 2-7 (2005).

14. Tan, D. E. B., Tung, R. S., Leong, W. Y. & Than, J. C. M. Sleep disorder detection and identification. in Procedia Engineering vol. 41 289-295 (Elsevier Ltd, 2012).

15. Thompson, T., Steffert, T., Ros, T., Leach, J. & Gruzelier, J. EEG applications for sport and performance. Methods 45 , 279-288 (2008).

Wireless EEG for Fast Prep and Easy Use: Q&A with Aswin Gunasekar, CEO of Zeto

Electroencephalography (EEG) devices are incredibly helpful in diagnosing and monitoring certain brain disorders, such as epilepsy and strokes. However, they are not particularly user-friendly or convenient, with specialized technicians performing time consuming procedures, such as skin preparation, to get patients ready to undergo the procedure. A combination of messy gels and wires also makes for an uncomfortable and inconvenient experience for patients.

Woman wearing Zeto's wireless EEG machine

In response, Zeto Inc., a medtech startup based in California, has developed a new EEG device that sits on the head like a bicycle helmet. The headset does not require gels or pastes to function, and can transmit data wirelessly. The company claims that the new system can reduce setup times from the current 20-30 minutes required with conventional systems to just five minutes, potentially making the Zeto device very useful in emergency situations. Best of all, the headset does not require a specialized technician for setup and use, and so could be quickly applied by nursing staff or other clinicians.

The device is currently being trialed at Methodist Le Bonheur Healthcare in Memphis, Tennessee, to see how it compares with traditional EEG equipment in a clinical setting.

Here’s a video intro from Zeto Inc. about the company’s technology:

Medgadget had the opportunity to talk to Aswin Gunasekar, Founder and CEO of Zeto Inc., about the technology:

Conn Hastings, Medgadget: Please give us an overview of conventional EEG devices, and their limitations.

Aswin Gunasekar, Zeto: Conventional EEG devices require a trained EEG technologist to measure the head, mark electrode locations, abrade the skin, and apply paste and electrodes to the scalp, eventually tethering the patient to a box with wires. This procedure consumes time, requires technologists who need to be perpetually on-call, and puts the patients through a needlessly poor experience. The scarcity of EEG technologists makes the problem worse, and even unfeasible in many hospitals, emergency rooms and other outpatient settings. Essential features such as easy data access and remote interpretation remain unavailable for conventional EEG devices.

Medgadget: How does the new device developed by Zeto compare with conventional EEG in terms of speed and ease of use?

Aswin Gunasekar: Zeto’s Instant EEG Platform (zEEG) provides the first FDA cleared zero-prep, wireless, dry electrode headset that can be used to perform a routine or urgent EEG anywhere without the need for a trained expert. The device is quickly and easily placed on the patient’s head much like a bicycle helmet. Data are streamed via a HIPAA compliant cloud platform that provides live viewing, tools for analysis and optional remote interpretation by neurologists. Time to interpretable EEG is typically 5 minutes with built-in positioning as per the international 10-20 EEG system. Total overhead time for set up and patient clean up with the Zeto headset is typically under 10 mins compared to over 45 minutes with conventional EEG.

Medgadget: Given the current pandemic, how does the Zeto EEG device help with reducing the potential for viral transmission?

Aswin Gunasekar: Due to the convenience and simplicity of Zeto’s EEG technology, PPE and exposure time for healthcare workers is reduced significantly. The headset utilizes single-use, disposable electrodes and an optional liner which reduces contact between the patient and the reusable headset, reducing the risk of contamination. Zeto has not yet performed studies on reducing viral transmission. However, the faster setup, zero patient clean up and the ability to monitor the recording with live video from outside the room helps reduce exposure of staff.

Medgadget: What types of mobile devices are compatible with the Zeto EEG device? Is the mobile interface easy to use?

Aswin Gunasekar: Most laptops, desktops and mobile devices capable of running the latest version of Google Chrome web-browser are compatible with the Zeto EEG device. Users of zEEG devices are provided with web-based access, an EEG study manager, video review, annotation features, time-frequency analysis, report generator, analytics and automated software upgrades. The mobile interface – as well as that of laptops and desktops – is simple, intuitive and easy-to-navigate.

Medgadget: How are data transmitted and how do you deal with data security?

Aswin Gunasekar: The security of our customer and patient data is of foremost importance to us. Zeto employs Design, Technical, Physical and Compliance controls to ensure the integrity and availability of the data on our platform. Data are transmitted with industry-standard AES encryption on the move and at rest. Data access is controlled through strict authentication and authorization protocols. The Zeto Cloud Platform is compliant to HIPAA rules, FDA 21CFR820 cybersecurity requirements and NIST SP800-53 Cybersecurity controls, and all Zeto personnel are HIPAA trained.

Medgadget: Please give us an overview of the current trial of the device at Methodist Le Bonheur Healthcare in Memphis, Tennessee.

Aswin Gunasekar: Methodist Le Bonheur Healthcare is the very first hospital system globally to participate in the ongoing trial that compares the capabilities and benefits of Zeto’s EEG technology against traditional EEGs. The trial conducts 3 phases, namely 1) Inpatient (ICU) EEG for detecting subclinical seizures and status epilepticus, 2) Outpatient EEG with trained EEG technologists and 3) Outpatient EEG with staff who are not certified technologists. The current trial could result in a clinical breakthrough that transforms how we approach EEGs in the future.

Source – https://www.medgadget.com/2020/09/wireless-eeg-for-reduced-prep-time-and-non-specialist-use-interview-with-aswin-gunasekar-ceo-of-zeto.html

HealthTech Arkansas names five early-stage companies for latest cohort

HealthTech Arkansas announced the five early-stage companies selected for the 2020 HealthTech Arkansas healthcare accelerator.

The accelerator is supported by 11 Arkansas healthcare organizations, including Arkansas Children’s Hospital, Arkansas Heart Hospital, Arkansas Urology, Baptist Health, CHI St. Vincent, Conway Regional Health System, Mercy, OrthoArkansas, St. Bernards Healthcare, University of Arkansas for Medical Sciences, and Washington Regional Medical Center.

Representatives from each of the 11 healthcare providers interviewed applicants and selected companies with technologies that have the potential to advance innovation at their respective organizations. The five companies were selected from hundreds of applicants across 14 different countries and are headquartered across the country in California, Utah, and Pennsylvania.

The five companies are:

Astarte Medical, Yardly, Pa.
Astarte Medical is a precision nutrition company using software and predictive analytics to improve outcomes during the first 1,000 days of life. With an initial focus on preterm infants, Astarte Medical supports feeding protocols, practice, and decision-making in the neonatal ICU with a suite of digital tools and diagnostics designed to standardize feeding, optimize nutrition and quantify gut health.

nView Medical, Salt Lake City, Utah
The nView_s1 is an imaging system that provides instant 3D images in the OR with minimal radiation. Like a C-arm, the nView_s1 images from a stationary single position. Unlike a C-arm, novel AI reconstruction techniques allow it to provide 3D images.

Raydiant Oximetr y, San Ramon, Calif.
Raydiant Oximetry has developed a non-invasive fetal pulse oximeter to directly monitor a fetus’s blood oxygen saturation during labor and delivery and provide the key missing vital sign that clinicians need to more accurately assess the baby’s health during childbirth.

Vena Vitals, Irvine, Calif.
Vena Vitals, Inc. is re-innovating the way blood pressure is monitored by using soft stretchable sensors that can conform to the body and accurately measure arterial pulse. Their technology provides the benefits of continuous, beat-to-beat blood pressure measurements, but in a non-invasive way.

Zeto, Santa Clara, Calif.
Zeto has taken a significant step towards simplifying EEG. The Zeto product is the first and only dry electrode EEG headset and cloud platform cleared by the FDA for clinical use.

“Our provider partners around the state are excited to introduce the new cohort companies to their teams and launch pilot programs that can make a difference in patient care,” said Jeff Stinson, director of HealthTech Arkansas. “We’ve expanded the applicant pool and the number of providers in our coalition in each of the three years at HealthTech Arkansas. The guaranteed pilot projects and clinical studies from our providers around the state are what differentiates us from any other program in the country.”

The cohort will participate in a program that provides them the opportunity to pilot solutions specifically identified by the 11 participating Arkansas healthcare groups as areas of opportunity within their organizations.

HealthTech Arkansas is a third-year accelerator program focused exclusively on provider engagement with early-stage companies and works with both Arkansas-based and out-of-state companies. The Arkansas Economic Development Commission awarded a grant to HealthTech Arkansas through a program designed to increase acceleration activities in targeted industries in the state.

Source – https://talkbusiness.net/2020/09/healthtech-arkansas-names-five-early-stage-companies-for-latest-cohort/

New study tests “first-of-its-kind” EEG device

A press release states that EEG (electroencephalogram) tests are conducted to detect problems in the brain that may be associated with certain brain disorders such as seizures, tumors or strokes. A typical EEG test consists of multiple electrodes attached to a patient’s scalp with adhesive. Those electrodes have several wires connected to an amplifier which further connects to a computer that measures and records the results.

The setup and removal of a typical EEG test takes between 20–30 minutes. This new US Food and Drug Administration (FDA)-approved product, called zEEG from Zeto, (headquartered in Santa Clara, USA), can be set up in less than five minutes; which offers a more efficient and comfortable experience for the patient.

The patient wears equipment that looks like a high-tech bicycle helmet. The electrodes do not need to be glued to the patient’s scalp, do not leave any residue on the patient and there are no wires connected to an amplifier or computer.

An EEG technician at Methodist University can now be more productive and perform more EEGs in a day. The EEG and video recording are uploaded to the cloud where a specialist can read them at their own convenience.

The ZETO Instant EEG has been beneficial in the midst of the unprecedented COVID-19 pandemic. Due to the convenience of this EEG technology, personal protective equipment (PPE) and exposure time for healthcare workers is reduced significantly. Fast setup and clean up decrease the exposure times for nurses and other care providers. The ZETO Instant EEG uses single-use electrodes which also reduces the risk of contamination.

Source – https://neuronewsinternational.com/new-eeg-device/

Methodist University Hospital Is First In The World To Participate In Groundbreaking EEG Study For Inpatients That Improves Brain Monitoring During the COVID-19 Crisis

MEMPHIS, Tenn., Aug. 4, 2020 /PRNewswire/ — Methodist Le Bonheur Healthcare (MLH) is the first hospital system globally to participate in a landmark study using a first-of-its-kind EEG device.

EEG stands for electroencephalogram. EEG tests are conducted to detect problems in the brain that may be associated with certain brain disorders such as seizures, tumors or strokes. A typical EEG test consists of multiple electrodes attached to a patient’s scalp with adhesive. Those electrodes have several wires connected to an amplifier which further connects to a computer that measures and records the results.

The setup and removal of a typical EEG test takes between 20-30 minutes. This new FDA-approved product, called zEEG from Zeto, Inc., headquartered in Santa Clara, CA, can be set up in less than five minutes; which offers a more efficient and comfortable experience for the patient.

The ZETO Instant EEG has been beneficial in the midst of the unprecedented COVID-19 pandemic. Due to the convenience of this EEG technology, PPE and exposure time for healthcare workers is reduced significantly. Fast setup and clean up decrease the exposure times for nurses and other care providers. The ZETO Instant EEG uses single-use electrodes which also reduces the risk of contamination.

About Methodist Le Bonheur Healthcare

Based in Memphis, Tennessee, Methodist Le Bonheur Healthcare (MLH) has been caring for patients and families regardless of ability to pay for more than 100 years. Guided by roots in the United Methodist Church and founded in 1918 to help meet the growing need for quality healthcare in the greater Memphis area, MLH has grown from one hospital into a comprehensive healthcare system with 13,000 Associates supporting six hospitals, ambulatory surgery centers, outpatient facilities, hospice residence and physician practices serving communities across the Mid-South. From transplants and advanced heart procedures to expert neurology services and compassionate cancer care, MLH offers clinical expertise with a focus on improving every life we touch.

Source – https://www.prnewswire.com/news-releases/methodist-university-hospital-is-first-in-the-world-to-participate-in-groundbreaking-eeg-study-for-inpatients-that-improves-brain-monitoring-during-the-covid-19-crisis-301104852.html

Zeto Raises Series A Funding to Accelerate Commercialization Efforts of its Easy Use Electroencephalography (EEG) Headset and Software Platform

SANTA CLARA, Calif., March 10, 2020 /PRNewswire/ — Zeto, Inc., a privately held medical technology company that is transforming the Electroencephalography (EEG) experience for healthcare, today announced that it has raised $7.3 million in Series A financing led by Seraph Group and joined by Aphelion Capital, SV Tech Ventures and Shangbay Capital. Zeto raised $4 million previously in dilutive and non-dilutive funding. The new capital will be used to accelerate commercialization of its lead product, the zEEG headset and software platform, and develop new products to expand its portfolio. zEEG is the first true dry electrode EEG headset to be approved by the U.S. Food and Drug Administration (FDA) for clinical use.

“Since our commercial launch a few months ago, we added several customers who love the product and are utilizing it at high rates. We are glad to validate the strong product-market fit for zEEG. Inspired by the demand, we are excited to expand our commercial team and production capacity to serve our growing customer base,” said Aswin Gunasekar, MS, MBA, Chief Executive Officer and Founder of Zeto. “Our goal is to provide the most seamless and intelligent EEG experience for any clinical need. Current products are far behind what users need and Zeto is building a suite of convenient and intuitive products to eliminate the most time consuming and labor-intensive activities involved in traditional EEG. As a subsequent step, we plan to utilize artificial intelligence to not only supplement the reading physician with analytics and insight but also expand the diagnostic utility of EEG worldwide in areas of medicine where it has been underutilized.”

Zeto’s customer, Wave Neuroscience, Inc., said, “Our extensive intellectual property portfolio and business operations are built on award winning science and medical innovation. For us to achieve the high level of results we are committed to, we rely on partners that never rest in their quest to achieve the highest standards. Accessing an FDA compliant EEG device that performs at an uncompromising standard, allows for increased throughput and provides a user experience that rivals the latest technology assets, was very attractive to us. Zeto transformed the way we think about EEG capture by advancing technology further in the past two years than the industry had in the prior three or four decades. Zeto provides us the confidence, convenience and data quality that we rely on, day in and day out.”

“We believe a new era is around the corner when researchers can accelerate our understanding of the brain with this breakthrough device and software platform. It not only makes commercial sense, but also can serve as the infrastructure and library for neurological knowledge that leads to better diagnosis and treatment of brain disorders,” said Tuff Yen, CEO of Seraph Group, the lead investor.

“We are passionate about brainwaves, consider it a privilege to serve our customers and are committed to bringing great advancements for neurological care,” adds Aswin Gunasekar.

Source – https://www.prnewswire.com/news-releases/zeto-raises-series-a-funding-to-accelerate-commercialization-efforts-of-its-easy-use-electroencephalography-eeg-headset-and-software-platform-301020172.html

ZETO: Sensing Improvement in Neurological Data Processing

EEG is the gold standard for observing and characterizing neural activity, but patients are subject to lengthy and uncomfortable preparation for scans, and interpretation is subjective to the physician who reads it. Zeto has introduced a device designed for patient comfort and simple setup, which uses “active” dry electrodes capable of picking up cerebral activity with high digital resolution and less noise.

In Greek, the word zeto means “to live.” By that token, neural monitoring start-up Zeto Inc. was brought to life from the seed of a business school idea, with hopes of improving countless lives. Zeto’s CEO Aswin Gunasekar was in business school at the University of Texas, Austin, when he took an interest in epilepsy diagnosis after watching a family member battle the condition. Quickly realizing that the electroencephalogram (EEG), the gold standard for monitoring neural activity, has had few updates since its invention early in the 20^th century, innovation was an immediate priority for Gunasekar.

Current EEG systems are uncomfortable for patients, inefficient due to their lengthy setup, and variably interpretable in their output. Leveraging years of experience as an electrical engineer developing microprocessors, Gunasekar conceived of a business plan for an easy-to-use EEG testing alternative, which helped his MBA team win the venture creation class’ competition in 2013.

Gunasekar continued to develop it as he moved to Silicon Valley to work for PwC. During this period, his idea shifted from a patient-use home monitoring device to a professional, clinical, medical device. As it is today, the Zeto solution incorporates feedback from several hundred patients, neurologists, and EEG technologists to ensure its practicality in addressing the biggest pain points of those who use it most frequently.

Traditional EEG is used to observe seizures and diagnose epilepsy, sleep disorders, autism, stroke, concussion, and more. Testing involves the placement of 20 electrodes on the scalp, abrading the surface of the skin to lower impedance and using viscous gel to improve conductivity in order to boost the signal detected. The process requires a specially trained technologist and can take up to two hours to yield just 30 minutes’ worth of test results, the rest of the time lost to preparation, adjustment and clean up. The signal, once recorded, is highly intricate with many discrete elements that are challenging to translate into useful information.

Current EEG systems are inherently expensive to operate and maintain with such cost drivers as the time consumed, labor, equipment, consumables, maintaining the digital infrastructure to allow remote access for physicians as well as storage and archiving of patient recordings. Consequently, additional expenditure is incurred for IT personnel, third-party software, and data retrieval. According to Gunasekar, the broken EEG value chain has led to underutilization of EEGs in most US hospitals and unavailability in many rural, emergency, and international settings.

Finally, there is also a high degree of subjectivity between readers of EEG output. Signals are often manually annotated in various formats, with the data largely unstructured and not machine learnable.

“Today, the burden of obtaining a good signal is completely on the EEG technologist,” Gunasekar says. The placement of the sensors, as well as the mitigation of peripheral electrical activity that clouds the brain signal

with noise, requires training and experience to perfect. Precision placement is also a priority, as the goal is to capture neuronal activity at precise regions of the brain.

With Zeto’s device, a headset that resembles a bicycle helmet, much of the finessing required with traditional

EEG systems is eliminated. The sensors, designed for patient comfort, are mounted on a semi-rigid but adjustable frame, positionableto precise locations and calibrated to work dry (sans coupling gel), with no skin preparation, through all types of hair. In addition to EEG, Zeto’s patent pending hardware contains an added ECG sensor as well as video and auxiliary inputs for comprehensive monitoringcapability. Three clinical evaluations across 50 patients and the FDA clearance have so far validated that the device is at least

as effective as standard EEG systems with a more patient-friendly design and proprietary techniques for signal enhancement. The latter includes

Active Electrode Technology, which preamplifies and conditions the neural signal at the source, and Dynamic

Noise Cancellation, which detects and removes noise in real time, as audio headphones with a similar purpose do. Zeto’s revolutionary hardware connects to its intuitive cloud software that enables a secure, evolving AI engine with machine learning capability (currently in development), which will allow it to improve continuously through use as it gains experience. First, the data are standardized into a functional, searchable format, then are processed by the software to generate autonomous reports and assistance to give new insights to the attending doctor. By bringing to market arguably the most significant advancement to EEG technology since its inception, Gunasekar is aiming to not only disrupt the market, but lead it.

“We want to aid physicians tremendously with the EEG diagnostic for the future,” says Gunasekar. In line with this pursuit, Zeto is offering EEG interpretation services by board-certified neurologists to bridge any gap in knowledge when examining a particular scan. The combination of human expertise and tireless machine assistance will maximize the potential for meaningful analysis, overcoming the complexity and subtlety of neural signals. This new approach, for example, can guide attention to an area of the brain with particularly relevant activity, and search for similar patterns and connectedness to other regions across extended periods. That may lead to a more thorough understanding of neurological interaction and afflictions.

Zeto is introducing the first EEG headset backed by a cloud system to be cleared by the FDA for clinical use,

according to Gunasekar, who notes that the company is currently preparing for a CE mark. Zeto’s revenues will come from a capital equipment or subscription model, considering the pay-as-you-go nature for cloud connection and support. All of the company’s manufacturing is completed in-house, with production capacity capable of exceeding a few hundred units per month.

Gunasekar notes that both thought leaders and marketing partners will be engaged to help push Zeto to the forefront of the conversation among hospitals and clinics. The ease of its use allows for a demonstration that proves the product’s effectiveness in minutes, underscoring the intuitiveness of the headset, and serving as an instant visual representation of its increased efficiency and comfort over traditional EEG solutions.

With over 20 million clinical EEG procedures performed each year globally, Zeto’s initial target application of

short-term routine scans represents a $1.5 billion market, while follow-on products will address a $4 billion longterm EEG sector, and eventually a $10 billion future market that can positively impact autism, stroke, and concussion.

By Gunasekar’s assessment, Zeto’s 19-person close-knit team is its engine of innovation. “We have an incredibly passionate team that is locked in on transforming this space,” he says, “but we will really be smiling once our product has made this important medical test available to millions of people in

the world who need it.” The company is currently in an A round of financing, seeking $12 million, to fund its imminent commercial launch with an oversubscribed order pipeline for 2019.

Source – MedTech Strategist