Event Related Potentials (ERPs) in EEG provide insight into how our brain processes information, reacts to its environment and adapts to challenges. ERPs differ from the traditional clinical tradition of evaluating continuous spontaneous brainwaves in patients. With ERPs, experimenters can examine the brain’s response to succinct events. For a summary on ERPs, see here.

One of the most crucial aspects in capturing clean ERPs is knowing precisely when specific target events occur. So-called event markers are commonly used to timestamp the onset of target events in the continuous EEG tracings to enable further data processing. The target events can have different modalities and can either be initiated or perceived from the person receiving the EEG.

For example, participant initiated movements are known to elicit robust ERPs.^{1 2} However, more commonly, ERPs are recorded from participants perceiving sounds, language, images, or smells.^3,4,5 In principle, ERPs will emerge via subsequent processing as long as experimenters established a reliable method to repeatedly mark the onset of such events in the EEG.

There are two technical aspects that determine the quality of ERP event markers:

• Delay: Time from when an event occurred to when it is marked in the EEG data
• Jitter: Consistency of the delay with which the event is marked in the EEG data

Long delays with large jitter complicate EEG analysis up to the point in which the targeted ERP component becomes unobtainable or requires too many trial repetitions to appear. Short delays with minimal jitter create the ideal technical conditions to obtain ERPs with a minimally possible amount of trial repetitions.

With Zeto’s event marker integration, users benefit from accurate event marker timing and distributed cloud data access and management – see Figure 1.

Figure 1. Schematic diagram of Zeto’s local event marker integration and remote data streaming and management features. Event markers from the presentation computer timing are merged with the EEG data locally via the Zeto Interface Box 2 (ZIB2) and then passed on to the Zeto Cloud.  A simultaneous LSL integration and related multi-model data recording become possible out of the box while maintaining Zeto’s existing cloud streaming, data, and user management features.

ZETO ERP FEATURES

The Zeto EEG platform offers the ability to integrate external markers wirelessly at an 8-bit resolution within a 2 ms delay and less than 1 ms technical jitter. In other words, the user can distinguish between 255 unique event markers that they can repeat as closely as 4 ms from one another. With these features, Zeto EEG is equipped to reveal accurate auditory, visual, and senso-motoric ERPs across a wide range of applications.

Event markers are collected by the system via an 8-bit DB9 connector built into the Zeto Interface Box Version 2 (ZIB2) using Transistor-Transistor-Logic (TTL) signals.⁶ The ZIB2 acts as a data access point for the wireless Zeto WR19 headset. Synchronization between the ZIB2 and Zeto WR19 is handled at a nano-second range, eliminating both the delay and jitter introduced by the wireless data transmission. Incoming event markers are retroactively aligned with the data point at the time of collection.

Users can extract the event marker data from the Zeto system in multiple ways:

1) EDF+ File
Zeto users can export finished EEG recordings in various ways but the most popular is the EDF+ file format that is readable by most common EEG analysis tools. Event markers appear in the EDF+ file as digital I/O channels synchronized with the EEG data. Some EDF readers will also display the embedded event markers in the viewer.

2) Visualization
In the Zeto cloud software, users can visualize the TTL event marker inputs along with the EEG by selecting the “ALL” montage in the montage menu. This view is particularly useful for troubleshooting when setting up the ERP experiment. Offline or in real-time the user will see incoming event marker codes visualized high or low values in separate channels. The event marker channels are simultaneously translated into event marker labels that co-appear at the bottom of the screen (Figure 2).

Figure 2. Close-Up of the “All” Display montage: Output (“A”) or Input (“B”) event marker channels for 8 bits each, translated into up to 8-bit (255) unique event marker labels. The event marker mapping can be freely configured and labeled as desired prior to the recording. In this example, eight input event marker signals are embedded in the data file (pins 1 to 8) and show up as square waves (“C”).  Each input event marker channel is mapped to an annotation, labeled “One” through “Eight” respectively at the bottom of the data screen.

3) Real-time lab streaming layer (LSL) Export
Eight digital input and output channels each are made available via lab streaming layer (LSL) API in real-time, enabling the user to note the stimulus onset directly in the data stream. Event makers and EEG are synchronized and merged prior to providing this data to the LSL streaming socket. As a result, event timing and EEG data remain perfectly synchronized even if there are LSL related streaming delays. Additional LSL API synchronization features remain available to users for additional real-time data integration.

4) Offline Event Marker Files
Users have the option to export marker files after the recording is completed. That marker file contains precise marker timing and label information for all event markers recorded for easy processing in third party analysis tools such as MATLAB, ERPLAB, Python or others. This allows for separate analysis of event data and EEG data found in the exported EDF+ file.

The event file can be exported in “.csv” format (Figure 3), or a comma-delimited format called “.zmrk”. Both are compatible with most common EEG processing tools currently available for research. 

Figure 3. Event Markers listed in .csv format.

ZETO EVENT MARKER TIMING VALIDATION

Zeto validated the event marker timing to establish the delay and jitter attributes under working conditions.
To do this, a testing setup split the incoming TTL trigger voltages via an analog splitter into two exact 8-channel copies. One copy of the event marker signals got connected to the ZIB2 input trigger ports while the second copy got connected to 8 channels of the WR19 headset. As a result, incoming event markers both appeared as digital events in the datastream and voltage changes in the EEG channels (Figure 4). Subsequent processing revealed the real-life delay and jitter between the incoming event marker signals and the EEG recording.

Figure 4. Schematic of the event marker timing test setup. The presentation computer sends 8-bit TTL event markers to an analog splitter box. One copy of the TTL signals arrives at the ZIB2 and gets converted into event labels. The other copy arrives at the headset and feeds into 8 of the EEG channels to show up as signals in the EEG data file.

Using this approach, event marker timing was established as stable, at < 2 ms delay and <1 ms jitter, which is a good basis to reliably capture ERP signals in EEG.

ZETO’S STIMULATION AND SYNCHRONIZATION PLATFORM PARTNERS

It is important to note that the Zeto system provides extremely precise synchronization on the receiving end of the event marker only. In fact, a much more likely source of both delay and jitter in ERP experiments occurs during stimulus presentation and subsequent event marker generation.

To avoid timing complications that occur prior to event markers entering the Zeto system, Zeto has partnered with two stimulus and synchronization platforms – both tested with our products.  These stimulus presentation and synchronization products are designed to eliminate delay and jitter on the event marker onset. In addition, they offer a variety of additional functions, including experiment writing and presentation software, participant response boxes, and photodiodes. 

Both partners have implemented out-of-the-box integrations for Zeto and are ready to service Zeto customers.

Cedrus, Inc.	Psychology Software Tools
Cedrus devices are designed for precise, jitter-free event marking and fit a variety of budgets. SuperLab is an experiment writing application, while software support for their hardware interfaces also includes Matlab, E-Prime, Python, C++, etc.	Psychology Software Tools isa prominent software and hardware company that helps researchers address challenges in human behavioral studies. PST are creators of E-Prime, a market-leading experiment writing platform.
C-POD Sent precise event markers via USB	Chronos Hardware synchronization and delivery system for millisecond-accurate event markers to external devices using various I/O port options.
M-POD Sent precise event markers, plus incorporate a response pad and photodiode	E-Prime Experiment writing platform that integrates stimulus presentation and behavioral software with research equipment
StimTracker Duo Comprehensive audio/visual/response synchronization platform
SuperLab Easy to use experiment writing software that does not require programming

References

1. Hai Li et al. (2018). “Combining Movement-Related Cortical Potentials and Event-Related Desynchronization to Study Movement Preparation and Execution.” Frontiers in Neurology.
   https://www.frontiersin.org/articles/10.3389/fneur.2018.00822/full
2. Fedor Jagla, Vladislav Zikmund, in Studies in Visual Information Processing (1994). “Visual and Oculomotor Functions.” ScienceDirect.
   https://www.sciencedirect.com/topics/neuroscience/movement-related-potential
3. Sean McWeeny, Elizabeth S. Norton. “Understanding Event-Related Potentials (ERPs) in Clinical and Basic Language and Communication Disorders Research: A Tutorial.” PMC.
   https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016705/
4. Shravani Sur, V. K. Sinha (2009). “Event-related potential: An overview.” PMC.
   https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016705/
5. Thomas Hörberg et al. (2020). “Olfactory Influences on Visual Categorization: Behavioral and ERP Evidence.” Cerebral Cortex.
   https://academic.oup.com/cercor/article/30/7/4220/5811850
6. Fiorenzo Artoni et al. (2017). “Effective Synchronization of EEG and EMG for Mobile Brain/Body Imaging in Clinical Settings.” PMC.
   https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5770891/

As a healthcare professional, you know how important it is to have reliable equipment that can withstand the daily grind of a busy medical practice. That’s why we designed Zeto EEG – a rugged, clinical-grade headset that is built to last.

Zeto’s durable EEG headset is made from high-quality, clinical-grade materials that are easy to clean and maintain. It has a light but substantial feel, making it comfortable to wear for extended periods of time. But don’t let its light weight fool you – Zeto’s resistant EEG headset is tough enough to handle collecting EEG data in even the most demanding clinical environments.

To back up our commitment to quality, we offer up to 4 years hardware warranty that covers intended use. Customers have the choice to purchase this warranty at once upfront or extend it annually. This means that you can use Zeto with confidence, knowing that it is built to last. Excluded from that warranty is unintended use such as submerging or washing, sitting on, tearing, or intentionally over-bending the headset.

Our standard Service Level Agreements (SLAs) provide 72 hours replacement assurance. For those who need even faster replacement, our premium SLAs assure that a replacement headset can be with you within 24 hours during weekdays as long as we receive your request by 2 p.m. (ET).

In conclusion, if you’re looking for a quick-to-apply dry EEG system that is built to withstand the rigors of daily clinical use, look no further than Zeto.

Curious about how well our Zeto’s reliable EEG headset can withstand the daily wear and tear of a clinical setting? We put our product to the test with a drop test, simulating the accidental drops and impacts that can occur during everyday use. Watch the video to see just how rugged and durable Zeto truly is:

Sweat artifacts are a common problem in electroencephalography (EEG) recordings. They can noticeably affect the quality of the recorded tracings and make it difficult to read the underlying EEG signals. Sweat artifacts in EEGs occur when the body’s biological sweat response alters the conductivity of the skin in a way that affects the electric signals picked up by the electrodes. Such changes not only occur when sweat is visible on the scalp but also occur when the body heats up and prepares to sweat.

In this blog, we will explore the causes of EEG sweat artifacts, their effects on EEG recordings, and strategies for mitigating their impact.

What Causes Sweating

Sweat is crucial for human thermoregulation and can be caused by a variety of factors, including anxiety, nervousness, or physical exertion. Biological changes during menopause also increase the chance of sweating. Regardless of these and other factors, a warm testing environment is the main driver of sweating.¹ Systematic studies revealed that temperatures above 79°F (~26°C) can have a noticeable effect on the EEG and signal morphology.²

The Biology of Sweat Artifacts in EEG

Sweating is not simply the appearance of sweat on the skin but the result of a cascade of biological changes that lead to the skin’s ability to secrete liquid from the sweat glands, onto the skin (Figure 1).

The filling of the sweat glands with liquid in preparation of sweat excretion increases the electrical conductivity of the skin rapidly which affects the morphology of the EEG signals. These rapid changes in skin conductivity and the uneven distribution of the sweat glands across the skin result in recordings prone to major EEG artifacts, with single channels showing large signal changes at different times and locations.³

Figure 1. Cross section of epidermis and dermis skin layers with embedded hair follicle, eccrine, and apocrine sweat glands. Source: Mayo Clinic

The Physics of Sweat Potentials in EEG

In addition to biological changes in the skin’s conductivity, the composition of the sweat itself is contributing to electrical potentials that EEG amplifiers pick up. Sweat contains high sodium chloride and lactic acid which react with metallic components of the EEG electrodes, generating electrical potentials.⁴ These electrical potentials combine with skin and sweat gland potentials into what is visible in the EEG as sweat artifacts.

Appearance of Sweat Artifacts in EEG

Sweat artifacts in EEG can appear in various morphologies or shapes that are affected by biological factors such as the severity and generality of the sweat response. The sudden onset of sweating across the entire body will appear different from sweating that occurs over time or may be more limited by body part or region. More relevant for the appearance in EEG though, are the analog or digital filter settings of the recording.

Amplifiers with a built-in low-frequency hardware filter will show a more subdued sweat artifact even without any digital filtering. True direct current (DC) amplifiers that do not have any analog low-cut-off filter will show the build-up to a sweat artifact in their raw data much more because small changes over time can be picked up much better.

Most clinical EEGs are viewed at a 1 Hz–70Hz bandpass filter as recommended by ACNS.⁵ EEG Sweat artifacts viewed using a 1 Hz low-cut-off filter generally show up as slow wave components around a 1 Hz–3 Hz frequency in otherwise normal background activity; for an example, see Figure 2. Disabling the low-cut-off filters, however, exposes additional low-frequency drifts related to sweat that are otherwise masked by digital signal processing; for an example, see Figure 3.

Figure 2. Filtered sweat artifact in a full 19-channel clinical EEG viewed in a referential montage. 1 Hz low-frequency forward Butterworth filter applied. The slow meandering signal drifts almost completely disappears after filtering (red frame).

Sharper signal drifts remain visible even after filtering (blue frame). For most clinical recordings, EEG tracings such as this are indicators of the biological changes that are caused by a sweat response. Data was recorded using Zeto’s WR19 headset at 79°F (~26°C).

Figure 3. Unfiltered sweat artifact during the same data segment, as presented in Figure 2. Slow meandering (red frame) and at times sharper signal drifts (blue frame) reflect the biological changes in the skin’s conductivity due to sweating.

How to Get Rid of Sweat Artifacts in EEG

There are two common ways to reduce or avoid sweat artifacts in EEG recordings.

1. EEG operators can reduce the biologically triggered changes that lead to sweating. In preparation for the EEG recording, operators can ask patients to avoid strenuous exercise, caffeine, and alcohol prior to a scheduled EEG session, ideally 24 hours before the test. During EEG recordings, Kappenman and Luck recommend maintaining a cool temperature in the recording environment to minimize the occurrence of EEG sweat artifacts. They recommend a comfortable temperature of 68°F –72°F (20°C –22°C) and using fans or air conditioning to prevent humidity buildup.²
2. During the EEG session, EEG operators should assure the best possible electrode contact with the scalp to reduce skin impedance under the electrode. In traditional amplifier systems with wired electrodes, this can be achieved via additional skin preparation and abrasion. With active quick-apply EEG recording systems, such as Zeto’s headset, operators can assure proper electrode landing with each conductive leg touching the scalp.

Bottom Line – Recommendations

In hectic clinical day-to-day EEG schedules, the easiest way to avoid sweat artifacts in most patients is to avoid sweating in the first place. For that reason, option #1, mentioned previously (reducing sweating), is the most robust way to assure consistent EEG data quality.

• Keep the EEG room temperature at 68°F – 72°F (20°C–22°C), especially when recording unconscious patients who cannot communicate their comfort levels; keeping an optimal temperature reduces the body’s need for sweating.
• Use fans or air conditioning to accommodate individual patient’s temperature requests. Each patient is different; ask to make sure they are not hot.
• If EEG sweat artifacts are detected, consider pausing the study to cool down the room (i.e., opening the door, reducing the room temperature, and/or the use of a fan).
• Relaxation techniques: Encouraging the patient to relax and breathe deeply. This can help to reduce sweat caused by anxiety or nervousness.

By implementing these strategies, EEG operators can help minimize sweat artifacts in EEGs and obtain cleaner results. It is important to work closely with the patient and monitor the EEG tracings for any signs of EEG sweat artifacts during the test to more adequately address issues with data quality.

References

1. Baker, L. B. (2019). Physiology of sweat gland function: The roles of sweating and sweat composition in human health.
   https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773238/


2. Kappenman, E. S., & Luck S. J. (2010). The effects of electrode impedance on data quality and statistical significance in ERP recordings.
   https://static1.squarespace.com/static/5abefa62d274cb16de90e935/t/5ac6962a8a922d0b8b8be6a1/1522964012664/Kappenman+2010+Psychophys+Impedance.pdf


3. Kalevo, L., Miettinen, T., Leino, A., Kainulainen, S., Korkalainen, H., Myllymaa, K., … & Myllymaa, S. (2020). Effect of sweating on electrode-skin contact impedances and artifacts in EEG recordings with various screen-printed Ag/Agcl electrodes.
   https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9017959


4. Siddiqui, F., Osuna, E., Walters, A., Chokroverty, S. (2006). Sweat artifact and respiratory artifact occurring simultaneously in polysomnogram.
   https://pubmed.ncbi.nlm.nih.gov/16461004/


5. ACNS – American Clinical Neurophysiology Society Guidelines and Consensus Statements.
   Guidelines and Consensus Statements | ACNS – American Clinical Neurophysiology Society

The profound lack of access to EEG outside of urban academic centers is a substantial health disparity. Most rural and suburban hospitals do not have the EEG equipment or trained staff available to obtain and read EEG studies. Thus, they must transfer patients who need EEG monitoring to a medical center that can provide these diagnostic services. 

These transfers delay diagnosis and treatment, burden patients and families, and increase healthcare costs and lengths of stay. 

As this article will show, even the smallest rural hospitals can provide their patients with high-quality, cost-effective, sustainable EEG using modern technologies and remote services.

Lack of Staff is an Insurmountable Barrier to EEG Access in Rural Areas

In a lecture presented at the ASET 2022 Annual Conference, Dr. Suzette LaRoche highlighted the disparities in access to neurodiagnostic technology faced by patients in rural areas. As per Dr. LaRoche’s insights, it is no secret that neurologists tend to practice in urban areas. More specifically, they cluster in large academic medical centers. A small community hospital in a rural area likely doesn’t have a neurologist or an EEG technologist on staff. The hospital may not even have EEG equipment. Consequently, every patient who needs EEG either doesn’t get this critical study or must be transferred to another hospital. Medium-sized hospitals may have a general neurologist on staff, but a dearth of techs. Moreover, even if the hospital employs neurologists and EEG techs, they are usually only available from 9 to 5, Monday through Friday. Even large community hospitals with neurologists and perhaps even epileptologists struggle with EEG tech coverage. Hiring more neurologists and EEG techs is not the answer—they are simply not enough of them who choose to work in rural and exurban areas.

Overcoming Barriers to Rural EEG

Dr. LaRoche identifies the following factors as the main obstacles to EEG testing in rural areas:

• No trained technician is available on site to perform the EEG study
• No one to read or interpret the EEG study (i.e., no neurologists or epileptologists)
• No EEG equipment 

If you cannot get neurologists and EEG techs to work in rural areas, how do you adequately care for patients? The solution is to change the way we obtain and read EEGs:

• Use rapid EEG devices that can be correctly placed by any medical staff member in minutes
• Record EEG studies to the cloud so that they can be read remotely by board-certified neurologists
• Use an EEG system that integrates video with EEG recording for remote review
• Use remote EEG and cEEG monitoring and remote EEG reading services

As remote medicine continues to become commonplace, we expect to see a rise in remote EEG monitoring companies, and expanded opportunities for remote EEG techs. 

Zeto Brings EEG to Rural Hospitals

Zeto EEG is a wireless, adjustable EEG headset with integrated dry electrodes. Zeto offers a rapid full montage EEG solution and might be used for cEEG for up to 4 hours and for routine EEG.  

If an EEG technologist is not available, any medical staff can correctly place the EEG headset in minutes (the average setup time is 5 minutes) with minimal training. It’s possible to use cross-trained personnel such as a nurse, medical assistant, or respiratory specialist. The Zeto team trains onsite and offers remote support.   

The Zeto headset wirelessly sends EEG recordings to the cloud so the data can be monitored in real-time by anyone who has access to the HIPAA-compliant cloud platform. In situations where in-house registered EEG technologists are unavailable, Zeto is partnering with accredited EEG remote monitoring services that provide live remote video monitoring at an hourly flat rate. 

Even a family medicine physician who is the closest doctor to the patient can carry out an EEG test using Zeto’s remote video monitoring service after being trained by Zeto,

If the rural hospital has a neurologist on staff, that professional can review the EEG from a medical office or from home. If a neurologist is not available, Zeto offers an EEG reading service staffed by board-certified neurologists. 

Also, Zeto has recently implemented FDA-cleared seizure detection software, a robust tool that provides automatic pattern notification to detect critical events and notify medical staff and neurologists.

Zeto can bring cost-effective remote EEG services to any size hospital even if there are no EEG technologists or neurologists on staff. Indeed, Zeto’s rapid full-montage EEG headset could eliminate a major health disparity that currently plagues rural hospitals. 

Source: The blog is inspired by a lecture by Suzette LaRoche, M.D., FACNS, FAAN
“Disparities in Access to Neurodiagnostic Technology” presented at the ASET 2022 Annual Conference