Zeto's wireless EEG machine

Blog

How Digital EEG Filters Impact EEG Signal Morphology

Filters are commonly used during clinical assessment of EEG brainwaves. They are recommended in the ACNS guidelines¹ to reduce electrical noise and improve EEG data quality. The basics of filter theory are part of the training curriculum for physicians and EEG techs² alike, yet the impact of filters on interpreting data is not always apparent to everyone in the day to day clinical operations. This blog summarizes the issues, explains what filters exist, and what effects they can have on the morphology of the EEG waveforms. Selecting the right filter settings can help improve readability and reduce misinterpretations.

Why We Filter and Why It’s Appropriate

A considerable amount of raw data in EEGs are contaminated by noise and artifacts. This noise originates from various sources such as the environment, recording instruments, or from within the body that are not of interest to analyzing the EEG (i.e. “physiological noise”). The problem arises when these noise sources mask the target EEG signal or interfere with its assessment. Oftentimes, however, the artifact noise and target EEG signal occupy different spectral regions, and selectively filtering out specific frequencies may improve the overall signal-to-noise ratio (SNR).

For example, a direct current (DC) or baseline offset of the amplifier system or slow fluctuations induced by sweat artifacts may be removed with a high-pass filter. Electrical power line noise in the recording environment can be attenuated by using a notch filter at 50 or 60 Hz. And, unwanted high-frequency components from muscle artifacts can be removed by “smoothing” the data with a low-pass filter. The advantages of filters are that they can help increase the SNR of target signals especially in situations in which the target EEG signals are in a limited band.

Filters are applied selectively to exclude frequencies from further evaluation. Three main types of filters used to accomplish this for EEG are i) high-pass filters (also called low-cut-off filters), ii) low-pass filter (also called high-cut-off filters), or iii) band-reject filters (or also called notch filters) – See Figure 1. Most EEGs evaluated in clinical day to day operations have a combination of these filter types applied before a reviewer assess clinical characteristics for triaging or diagnosis.³

Figure 1: A Low pass filter is a filter that passes low frequency components and blocks high frequency signals. A High pass filter is a filter that passes high frequency signals and blocks low frequency signals. Bandpass filter is a filter that passes a certain range of frequencies and blocks both lower and higher regions. A Band Reject filter is a filter that passes most of the frequency except a very narrow range of the frequencies.³

Because of their useful properties, filters are found at all stages during the EEG recording and review process. EEG amplifiers often contain an analog low-pass filter ahead of the analog-to-digital (AD) converter to address aliasing artifacts that are otherwise introduced due to the discrete sampling rate. However, most filters in EEG processing are digital and take place after the AD conversion. That makes filters omnipresent when working with EEG data and their settings will affect the look and shape of the EEG tracings on a reader’s screen. More in-depth analysis of filter times and filter theory.⁴

Wanted and Unwanted Effects of Filters on EEG Morphology 

The way that many filters operate is to apply a weighted average of consecutive data points of the raw signal to obtain a smoothed, output (filtered) waveform. Depending on the type and width of this averaging window, specific frequency components disappear from the output waveform. The filtered signal may not show excluded frequencies anymore, but this was made possible after having created a causal relationship with the surrounding data segments. Figure 2 illustrates this principle.

Every sample of the output depends on multiple samples of the input, as illustrated.

Figure 2. Every sample of the output depends on multiple samples of the input, as illustrated in Figure 2 (top).  Conversely, each sample of the input impacts several samples of the output (Figure 2, bottom). As a result, the signal that is being filtered is smeared along the temporal axis, and temporal relations between filtered and original waveforms are blurred.

Top: each sample of the output y is the sum of samples of the input x weighted by the impulse response h. For a causal filter, only past or present samples of the input make a contribution (black). For an acausal filter, future samples too can contribute (gray). Bottom: another way of describing this process is that each sample of the input x affects multiple samples of the output y, with a weight determined by the impulse response h.⁴

Filters that lead to this kind of temporal smearing are called causal filters and are frequently used in EEG assessments. However, causal filters are known to create ripples in the EEG data that will show up as slow waves in the EEG data. These causal filters create a phase shift but have the advantage that they can be applied in real-time to ongoing EEG data streams.

To avoid phase shifts and to get outputs much closer to the true biological signal, so-called forward/backward filters (or zero phase) filters are another option. Zero phase shift filters first run the filter in one direction and again in the other direction. As a result, any phase shift is mitigated and no temporal smearing occurs. However, the disadvantage of these zero-phase filters is that they can only be applied in real-time recordings with a significant delay because they have to wait for data to be recorded before they can run backwards.

Figure 3 illustrates the output of a causal (blue) or zero phase filter (green) when applied to a test signal (black). The output of the causal filter (blue) creates a well visible phase shift and relevant filter ripple along with a long overshoot. In contrast, the zero phase shift filter keeps the integrity of the main signal peak intact and only creates minor symmetrical ripples around the peak.

Temporal Response Function Estimated from Simulated Stimulus-Response Data

Figure 3. Temporal Response Function Estimated from Simulated Stimulus-Response Data. Black: “true” TRF. Thick blue: TRF estimated using response data that has been filtered by a causal filter (Butterworth band pass 1–10 Hz, order 4+4). Green: same with acausal filter (MATLAB’s filtfilt).⁴

Examples of Causal and Zero Phase Filters in EEG 

The most noticeable difference between causal and zero phase shift filters on actual EEG data occurs for high pass filters in the delta range (<1.5Hz) because they can visibly alter the appearance of commonly occurring biological signal components of the EEG such as vertical or horizontal eye movements (i.e., blinks and saccades), sweat artifacts, and even specific epileptiform discharges (e.g. absence seizures). For an overview, see Figure 4.

Effects of causal filters in higher frequencies (>50Hz) certainly exist as well but these are much less noticeable due to much faster oscillations that have smaller amplitude and are harder to pick out visually.

Effects of causal filters in higher frequencies (>50Hz) certainly exist.

Figure 4 – Here an example of two channels (FP1, FP2) filtered with a 1Hz causal filter (black tracings) or zero-phase filter (gray tracings) – causal filters introduce relevant slow wave filter ripples.

Implementation of Causal and Zero Phase Filters on the Zeto Cloud Platform

Most clinical EEG hardware or software manufacturers have filter master-settings that pre-determine the exact type and properties of the filters available in their products. That can result in situations in which the same biological signal may appear slightly differently depending on the manufacturer’s default digital filter settings. Zeto is improving the tradition by introducing features that enable users to easily switch between different filter types and settings to optimally control the use of filters while reviewing EEG data.

As a result, users can configure their filter preferences to match their individual viewing and training history, resulting in filter outputs that match their expectations. Instead of retraining themselves on a new system’s filter settings, they can now adjust filter attributes and reduce the time to a confident read significantly.

With Zeto, EEG data is saved in raw unfiltered (DC) formats that do not distort the original signal attributes. Subsequent digital filtering can then be used to match desired filter attributes. For example, Zeto can display data after running causal or zero phase shift filters and switch between these filter settings more easily, making it possible to compare which setting is preferred on the spot.

Figure 5 illustrates this filter switch approach on different data samples. The tiles on the left are filtered using zero phase filters and tiles on the right show the same data using causal filters of the same cut-off frequency. Switching between these filters reveals signal ripples, most noticeable for the blinks but also in other signal components.

1Hz Filter – left: zero phase; right: causal filters.

With Zeto, EEG data is saved in raw unfiltered (DC) formats that do not distort the original signal attributes. Subsequent digital filtering can then be used to match desired filter attributes.
With Zeto, EEG data is saved in raw unfiltered (DC) formats that do not distort the original signal attributes. Subsequent digital filtering can then be used to match desired filter attributes.
With Zeto, EEG data is saved in raw unfiltered (DC) formats that do not distort the original signal attributes. Subsequent digital filtering can then be used to match desired filter attributes

The benefits that filters provide are crucial to enable a confident clinical read that is not skewed by unwanted signals. However, filters can introduce artifacts on their own. The well trained EEG reader will need to be vigilant about possible filter artifacts in EEG signals and how these may affect the clinical assessment of the patient’s brain states. As Zeto, we encourage our users to match the available filter settings to their preferences to ensure a fast and efficient diagnostic process. For questions about how to best match your Zeto filter settings and establish adequate default settings, please contact our customer success team at support@zetoinc.com.

References:

  1. Sinha, S. R., Sullivan, L., Sabau, D., et al. (2016). American Clinical Neurophysiology Society Guideline 1: Minimum Technical Requirements for Performing Clinical Electroencephalography. Journal of Clinical Neurophysiology, 33(4), 303-307. DOI: 10.1097/WNP.0000000000000308
  1. ASET Board of Trustees. (2021, March 20). National competency skill standards for performing electroencephalography (EEG). ASET Website. Retrieved from https://www.aset.org/wp-content/uploads/2022/11/EEG_Competencies_FINAL.pdf (Page 4, Section 2.3)
  1. ShareTechnote. (n.d.). RF – Filter. Retrieved from https://sharetechnote.com/html/RF_Filter.bak
  1. De Cheveigné, A., Nelken, I. (2019). Filters: When, Why, and How (Not) to Use Them. Neuron. DOI: 10.1016/j.neuron.2019.02.039

EEG Techs Face Challenges: Portable EEG Creates Solutions

EEG Techs continue to be the gold standard for EEG administration, their training and expertise is crucial for meeting the neurodiagnostic needs of hospitals. Unfortunately, there is a massive nationwide shortage of EEG techs in the United States, and this significantly impacts the delivery of essential neurodiagnostic services throughout the country. This shortage not only strains healthcare systems, and causes delays in diagnosis and treatment, but also places an immense burden on EEG techs.


Zeto’s portable full-montage EEG headset offers a solution to this crisis. By simplifying and streamlining the EEG process, Zeto helps hospitals and medical centers to deftly navigate staffing shortages or a lack of availability of EEG techs on nights and weekends.


Zeto offers an EEG solution with seizure detection, video, and remote monitoring services, enabling hospitals and outpatient settings alike to maintain high-quality neurodiagnostic services even in the face of such staffing constraints.

Enhancing Productivity and Hospital Service Capabilities for EEG Techs

There is a massive nationwide shortage of EEG techs in the United States

In hospital settings, where the demand for EEG services is often high and continuous, the presence of a skilled EEG tech is invaluable. However, the current shortage of these professionals creates significant challenges. Zeto’s portable EEG headset is designed to address this gap, providing solutions that significantly enhance the efficiency and effectiveness of EEG services in hospitals.

Efficiency Improvements for EEG Techs:

Zeto’s headset simplifies the EEG setup and operation process. By reducing the time and effort required for placing electrodes and setting up, Zeto enables EEG techs to manage their workload with more ease.

EEG Techs can Delegate:

One of the key advantages of Zeto’s system is its ease of use, allowing EEG techs to quickly train other healthcare staff, such as nurses or other types of techs, such as respiratory therapists. If EEG tech is not available, support staff can step in. This capability is crucial for providing EEG services, especially during off-hours such as nights and weekends, or in the critical care and emergency departments.

Techs can Focus on Higher Level Duties:

With Zeto’s user-friendly system, EEG techs can dedicate more time to monitoring and annotating EEG readings, which are vital for accurate diagnoses. This shift in focus from setup to analysis enables EEG techs to apply their expertise where it matters most.

Upskilling for the Future:

As the healthcare industry evolves, there is a growing need for EEG techs to adapt and upskill. Technologies like Zeto not only provide immediate solutions to current challenges but also pave the way for techs to enhance their skills in areas like data analysis, remote monitoring, and advanced neurodiagnostic techniques.

Remote Validation of EEG Studies with Zeto’s Cloud Platform:

Zeto’s cloud platform enables EEG techs to remotely monitor EEG studies when the setup is performed by non-technical personnel. Utilizing live video, EEG techs can oversee EEGs in real-time from anywhere, ensuring the quality of each study. This remote capability is essential for maintaining high standards in EEGs, regardless of who performs the initial setup.

Use of Zeto’s portable EEG headset for hospitals is a significant step forward in managing the current EEG tech shortage. By enhancing efficiency, facilitating skill development, and ensuring continuous high-quality EEG services, Zeto helps hospitals to better manage their challenges, and to deliver excellent healthcare.

Improve Outpatient EEG Services Using Portable EEG 

In outpatient settings, the EEG tech shortage presents unique challenges, particularly in terms of efficiency and patient throughput. Zeto’s wireless EEG headset addresses these challenges head-on, contributing to improvements in how EEG services are delivered in outpatient clinics.

Reduction in Setup and Cleanup Time:

Traditionally, EEG setup and cleanup can take up to an hour, burdening both the EEG tech and the patient. Zeto’s portable EEG system reduces this to just a few minutes.

Minimal Space Requirements and Increased Flexibility:

The need for a sink and extensive setup space, as required for conventional EEG, is eliminated with Zeto’s portable EEG headset. Clinics can conduct EEG tests with just a bed or chair, making better use of available space. This compact setup allows a single tech to manage multiple EEG sessions simultaneously, with EEG data accessible via the cloud.

Enhanced Patient Throughput:

With Zeto, the primary limit to conducting EEGs is the number of headsets available. This capability to run multiple sessions concurrently significantly increases patient throughput, a vital factor in busy outpatient settings.

Streamlined Data Management:

Zeto’s cloud-based system means that data transfer concerns are a thing of the past. EEG techs no longer need to spend time ensuring data is properly transferred and stored, as it’s automatically synced to the cloud and accessible for whomever needs it, instantaneously.

Focus on Value-Added Patient Care:

Freed from time-consuming setup and data management tasks, techs can focus more on direct patient care, education, and comfort. This shift not only enhances the patient experience but also provides more job satisfaction for techs.

Patient Satisfaction and Comfort:

Zeto offers a more comfortable, shorter, and cleaner experience for patients. The use of no-residue electrodes that do not use gels or pastes, means there’s no need for a patient to wash their hair afterwards. It works perfectly with different hair types, including kinky, coil, and braided hair.

Expanding EEG Setup Skills Across Your Team with Zeto:

In outpatient settings where EEG techs might not always be available, Zeto’s system offers a practical solution. Any staff member, such as a medical assistant, can be trained to do the EEG setup. This flexibility allows clinics to utilize their resources more efficiently, ensuring that EEG services are readily available when needed. With Zeto, clinics can schedule patients for EEGs swiftly, enhancing patient care and operational efficiency even with limited staffing.

Zeto’s portable EEG headset addresses the critical challenges posed by the EEG tech shortage. By enabling more efficient use of time and resources, reducing the need for extensive physical infrastructure, and enhancing the quality of patient care, Zeto is setting a new standard in outpatient neurodiagnostic services.

To learn more about Zeto’s wireless, dry-electrode, full-montage EEG headset with real-time remote monitoring and seizure detection, please contact us to schedule a chat and a demo.

7 Core Benefits of Portable EEG for Growing Hospitals

In critical care, every second counts. Zeto’s portable EEG system cuts through complexity, offering a seamless solution that far out-delivers the competitors. Is it cumbersome? Far from it. Is it fast? Absolutely. Is it complete? With full-montage capabilities versus other portable EEG systems’ limited channels, it redefines thoroughness in EEG technology.

Zeto’s portable EEG has everything required for on-the-spot, point-of-care service without added demands on facility resources. For critical care monitoring, this is the only full-montage portable EEG that offers bedside monitoring with seizure detection. Unlike traditional systems, Zeto’s portable EEG is rapid, cloud-based, and real-time with video. Zeto also offers 24/7 remote monitoring and interpretation services — these can be ordered directly from the platform. 

Read on to discover the seven core benefits that Zeto’s portable EEG technology brings to growing hospitals, enhancing patient care and operational efficiency. 

Benefit #1) Signal Quality: Clarity in Every Reading

Zeto's dry-electrode portable EEG provides high quality results.Reliable EEG data is the backbone of neurodiagnostic accuracy. Zeto ensures that signal quality is never compromised. With full-montage 10-20 placement and advanced technology that shields and removes noise, the data captured is non-inferior to traditional EEG. This precision is what sets Zeto apart, allowing for confident clinical decision-making.

Data is streamed to a secure cloud platform that provides live viewing with video. Physicians access this high-quality data in real-time from anywhere, directly impacting patient care efficiency. Zeto’s commitment to signal integrity means that every reading is rapid and reliable.

For an in-depth look at how Zeto maintains superior signal quality, refer to our article, “Comparison of Dry Electrode EEG System with Conventional EEG System.” You can also review our published abstract on this topic at the American Epilepsy Society.

Benefit #2) Portable EEG Offers Ease of Use and Rapid Setup

Zeto’s EEG technology redefines hospital efficiency with its plug-and-play design.

Any member of your staff can be trained to administer Zeto EEG. If an EEG technician is not available, a health care professional can be trained to use Zeto EEG.

Setup is swift, taking less than five minutes from its case to your patient’s bedside and the dry electrodes eliminate the need for a time-consuming messy setup and clean-up. This simplicity accelerates patient throughput, enabling technologists and clinicians to focus on diagnostics rather than device preparation. With Zeto’s system, hospitals can reduce downtime and streamline their EEG operations.

Visit our device page to learn more and to see the EEG headset in action, and watch our usage videos to witness firsthand the ease of setup that Zeto offers.

Benefit #3) Patient Comfort: A Top Priority with Portable EEG

Comfort during EEG tests is a patient’s right, not a luxury. Zeto’s portable EEG headsets are designed with this principle in mind. The lightweight (1.4lb or 650 g) and adjustable design minimizes the strain on patients, making the experience as stress-free as possible. By using dry electrodes and eliminating the need for gels and pastes, our headsets also do away with the discomfort of traditional systems.

This patient-centered approach not only improves the EEG experience but also facilitates better compliance and quality of results. When patients are at ease, EEG recordings are done faster, providing clinicians clinical-grade EEG data for diagnosis and treatment planning.

For a closer look at how Zeto prioritizes patient comfort and its impact on care, view our patient page. 

Benefit #4) Zeto Offers Versatility in Patient Care

Zeto’s EEG headset is suitable for both adult and pediatric patients. This adaptability ensures that hospitals can provide high-quality EEG services across a diverse patient demographic. The headset’s adjustable nature allows for a comfortable fit for various head sizes, reflecting the device’s broad utility in a clinical environment.

For additional information on the headset’s versatile applications, please visit our FAQ page.

Benefit #5) Bedside Notifications and Ease of Monitoring

Efficient monitoring is key in critical care. Zeto’s EEG technology brings this efficiency directly to the patient’s bedside. Zeto offers near real-time notification of ongoing seizures by using reliable FDA-cleared seizure detection software. Seizures are automatically identified and highlighted in the EEG for review. Near real-time detection promptly informs medical staff about patients experiencing ongoing clinical seizures. With laptop-based monitoring, an ICU nurse becomes a vital link, swiftly alerting physicians to significant findings.

These bedside notifications are designed to enhance vigilance without overwhelming the staff, streamlining the observation process. They serve as an extension of the care team’s capabilities, ensuring that attention is drawn when it matters most.

For detailed information on how Zeto’s bedside alerts improve patient monitoring, read our recent article about EEG in the ICU.

Benefit #6) 24/7 Real-Time Remote Monitoring with Expert Oversight

Access to immediate EEG data and expert analysis is critical for any hospital. Zeto portable EEG systems offer real-time remote monitoring, with registered EEG technicians available to review and flag critical issues in EEG reports. When Zeto customers need EEG specialists, they can simply click on a service request button in the Zeto software, which notifies the monitoring service. With Zeto portable EEG, abnormalities are promptly identified, facilitating quick intervention.

Hospitals utilizing Zeto’s advanced EEG solutions can also benefit from expedited interpretation and clinical guidance. We partner with qualified reading and monitoring services that stand ready to provide expert analysis and recommendations. Patient care decisions are informed by specialist insights, anytime they’re needed.

For a comprehensive view of how Zeto’s remote monitoring services enhance patient care, refer to our article on the topic by clicking here.

Benefit #7) Reduced Costs to Hospitals

Zeto’s EEG system seamlessly integrates with standard billing practices, enabling billing as with a similar full montage EEG.

Incorporating a portable EEG device into a hospital’s diagnostic arsenal can potentially lead to:

  • Reduced Overhead Costs: Portable devices often require less setup and maintenance, decreasing operational costs.
  • Increased Patient Throughput: Faster setup times can lead to more tests conducted per day, enhancing service capacity.
  • Expanded Service Offering: The ability to perform EEGs in various settings, including at the patient’s bedside, attracts patients seeking convenience and comfort.
  • Optimized Utilization of Staff: Simplified operation allows a broader range of staff to conduct EEG tests, potentially reducing the need for specialized technicians.
  • Reduce Patient Transfer Cost: Diagnose patients on-site instead of sending them away.

With the Zeto portable EEG’s swift, dry electrode, full-montage capabilities, Zeto simplifies neurodiagnostic procedures, offering a seamless and efficient solution for growing hospitals. From ensuring top-notch signal quality to providing patient comfort and 24/7 remote monitoring, Zeto delivers on all fronts—without necessitating specialized operators be on-site and available at all times, easing their workload without compromising care.

The integration of Zeto’s EEG technology not only elevates the standard of patient care but also reduces operational costs and enhances your hospital’s services. Its versatility extends from adult to pediatric care, embodying the essence of adaptability in modern healthcare.

Contact us to learn more and to schedule a demo or consultation. You’ll discover how our technology can advance your hospital’s neurodiagnostic capabilities. Join us in leading the change towards better, more efficient patient care.

EEG after Cardiac Arrest is Vital, Says American Heart Association

The American Heart Association (AHA) recommends prompt electroencephalography (EEG) neuroprognostication for post-cardiac arrest patients in their 2020 guidelines on cardiopulmonary resuscitation (CPR) and emergency cardiovascular care (ECC). The prompt use of EEG in post-cardiac arrest patients is important because it allows for early identification of brain injury and can guide decisions about the continuation of life-sustaining treatment.

Hypoxic-ischemic brain injury is a leading cause of morbidity and mortality in survivors of hospital cardiac arrest.1 Sadly, most of the post-resuscitation deaths are caused by the active withdrawal of life-sustaining treatment. The decision to actively remove life-sustaining treatment is made when a poor neurological outcome is expected. For this reason, it is critical to perform accurate neuroprognostication, as recommended by the American Heart Association (AHA) in their 2020 guidelines on cardiopulmonary resuscitation (CPR) and emergency cardiovascular care (ECC).2

Proper post-cardiac arrest neuroprognostication, or EEG after cardiac arrest, is essential to distinguish those who may achieve a meaningful neurological recovery from those who will inevitably have a poor neurological outcome.2,3

Who Should Receive Neuroprognostication After Cardiac Arrest?

The AHA recommends multimodal neuroprognostication on all patients who remain comatose after cardiac arrest (Level 1 recommendation).2 Multimodal neuroprognostication includes EEG, MRI, quantitative pupillometry, and serum neuron-specific enolase, among others. In addition to neuroprognostication, EEG testing is recommended to identify seizures and, if necessary, provide treatment.

Nonconvulsive seizures, for example, are common after cardiac arrest, and cannot be reliably detected without EEG.4 The American Academy of Neurology also provides data on its importance. Also, EEG after cardiac arrest should be used to rule out underlying ictal activity in cardiac arrest survivors with status myoclonus. The 2020 Emergency Cardiovascular Care Science with Treatment Recommendations (CoSTR) advises seizures to be treated when diagnosed in cardiac arrest patients with return of spontaneous circulation (ROSC).5

When Should Neuroprognostication After Cardiac Arrest Start?

Importantly, prognostic assessments should not be started too early. If they are administered too soon after the cardiac arrest and during initial post-resuscitation care, the results may appear worse than they actually are because of medications, or acute post-injury changes.6 Perhaps surprisingly, clinical prognostic testing such as pupillary light reflex should not be used for neuroprognostication until at least 5 days after ROSC (return of spontaneous circulation) in patients treated with targeted temperature management (TTM), in order for such testing to have prognostic significance.

Testing should not begin until the patient has been normothermic for at least 72 hours.6-8 Imaging or EEG to detect status myoclonus may begin as early as 24 hours after ROSC; two studies including 347 patients, showed the presence of status myoclonus within 72 hours of ROSC predicted poor neurological outcome with specificity of 97% to 100%.9,10 However, postanoxic status epilepticus may not manifest until 72 hours or more after ROSC and sedative drug dosages have been reduced, so waiting for neurological prognosis assessment is necessary.

How to Use EEG for Neuroprognostication After ROSC

The 2020 American Heart Association (AHA) Guidelines for Cardiopulmonary Resuscitation (CPR) and Emergency Cardiovascular Care (ECC) recommend the use of EEG after cardiac arrest in patients who remain in a coma after ROSC for the purposes of neuroprognostication.2

Findings that are consistent with poor outcomes include postanoxic status epilepticus and/or burst suppression 72 hours or more after ROSC.2 Another potentially useful electrodiagnostic test is the somatosensory evoked potential (SSEP).

SSEP testing is conducted by stimulating the median nerve and looking for a resulting cortical N20 wave. N20 SSEP waves that are absent bilaterally correlate with poor prognosis.2 Likewise, rhythmic periodic discharges on EEG are also consistent with poor prognosis.

Importantly, the AHA notes that the absence of EEG reactivity within 72 hours after cardiac arrest should not be used as the sole determinant of poor neurological outcomes. A lack of EEG reactivity during this time does not necessarily predict a poor neurological outcome.

Obtaining EEG after ROSC

Conventional EEG in the Intensive Care Unit is Critical Care and Cumbersome

While conventional EEG is an acceptable means to obtain EEG in the ICU, it is impractical. Post-cardiac arrest patients who need post-cardiac arrest care in the ICU will, as standard care, be intubated, and have central venous and possibly arterial lines, and intracardiac devices.

Conventional EEG after cardiac arrest is challenging. Attempting to obtain EEG signals through a dozen wires in a critical care setting without quality-limiting artifacts is challenging. Indeed, providing continuous conventional EEG in the ICU is a literal barrier to care for ICU or neurocritical care nurses and staff.

Zeto EEG – Wireless Full-Montage Monitoring For Use on Coma Patients After ROSC

According to the AHA, proper neuroprognostication could prevent withdrawal of life support as it will indicate the accurate neurologic prognosis of a patient who has a chance at successful neurological recovery. Thus, the AHA recommends performing multimodal neurologic prognostication including EEG in all patients who remain in a coma after ROSC following cardiac arrest.

Zeto has developed a full montage, 19-channel (10-20 system) wireless headset with dry electrodes for rapid EEG monitoring. The benefits of Zeto’s electrodes include no skin preparation, no cleanup, and no gel or paste residue. The electrodes are single-use and soft.

The Zeto EEG device collects high-quality EEG recordings and transmits them wirelessly to the cloud for remote viewing and interpretation. ZETO’s EEG platform also offers an FDA-cleared seizure detection and trending algorithm developed by Encevis.

The Zeto EEG headset can be placed after a short training, and the setup takes only 5 minutes – which is crucial for patients in a coma. Once placed, the Zeto headset provides continuous EEG monitoring for up to 5-6 hours.

Overall, prompt EEG for post-cardiac arrest patients is a vital aspect of proper neuroprognostication and plays an important role in determining prognosis in patients and guiding treatment decisions. It is important for healthcare providers, especially intensive care medical providers to be aware of the AHA guidelines and incorporate EEG into their standard care management of post-cardiac arrest patients.

When called upon to perform the difficult and highly consequential task of neuroprognostication, choose Zeto for EEG in the ICU.

References

  1. Witten L, Gardner R, Holmberg MJ, et al. Reasons for death in patients successfully resuscitated from out-of-hospital and in-hospital cardiac arrest. Resuscitation. 2019;136:93-99. PMID:30710595 doi:10.1016/j.resuscitation.2019.01.031
  2. Panchal AR, Bartos JA, Cabanas JG, et al. Part 3: Adult Basic and Advanced Life Support: 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2020;142(16_suppl_2):S366-S468. PMID:33081529 doi:10.1161/CIR.0000000000000916
  3. Geocadin RG, Callaway CW, Fink EL, et al. Standards for Studies of Neurological Prognostication in Comatose Survivors of Cardiac Arrest: A Scientific Statement From the American Heart Association. Circulation. 2019;140(9):e517-e542. PMID:31291775 doi:10.1161/CIR.0000000000000702
  4. Freund B, Kaplan PW. Myoclonus After Cardiac Arrest: Where Do We Go From Here? Epilepsy Curr. 2017 Sep-Oct;17(5):265-272. doi: 10.5698/1535-7597.17.5.265. PMID: 29225535; PMCID: PMC5716491.
  5. Ryoo SM, Jeon SB, Sohn CH, et al. Predicting Outcome With Diffusion-Weighted Imaging in Cardiac Arrest Patients Receiving Hypothermia Therapy: Multicenter Retrospective Cohort Study. Crit Care Med. 2015;43(11):2370-2377. PMID:26284621 doi:10.1097/CCM.0000000000001263
  6. Samaniego EA, Mlynash M, Caulfield AF, Eyngorn I, Wijman CA. Sedation confounds outcome prediction in cardiac arrest survivors treated with hypothermia. Neurocrit Care. 2011;15(1):113-119. PMID:20680517 doi:10.1007/s12028-010-9412-8
  7. Berg KM, Soar J, Andersen LW, et al. Adult Advanced Life Support: International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. Resuscitation. 2020. PMID:33098922 doi:10.1016/j.resuscitation.2020.09.012
  8. Callaway CW, Donnino MW, Fink EL, et al. Part 8: Post-Cardiac Arrest Care: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2015;132(18 Suppl 2):S465-482. PMID:26472996 doi:10.1161/CIR.0000000000000262
  9. Ruknuddeen MI, Ramadoss R, Rajajee V, Grzeskowiak LE, Rajagopalan RE. Early clinical prediction of neurological outcome following out of hospital cardiac arrest managed with therapeutic hypothermia. Indian J Crit Care Med. 2015;19(6):304-310. PMID:26195855 doi:10.4103/0972-5229.158256
  10. Zhou SE, Maciel CB, Ormseth CH, Beekman R, Gilmore EJ, Greer DM. Distinct predictive values of current neuroprognostic guidelines in post-cardiac arrest patients. Resuscitation. 2019;139:343-350. PMID:30951843 doi:10.1016/j.resuscitation.2019.03.035

Enhancing Diagnostic Precision: Exploring the Role of Video EEG

Video EEG is an important tool in diagnosing and monitoring patients with epilepsy or other neurological conditions. It helps distinguish physiologic or external artifacts from epileptic seizures or epileptiform discharges associated with seizures. Video EEG also helps to differentiate epileptic seizures from psychogenic nonepileptic spells that are mistaken for seizures and other episodic abnormal movements associated with other conditions, such as tic disorders, tremor, or periodic limb movements of sleep. Simultaneous video and EEG recordings enable the establishment of correlations between abnormal movements and abnormal wave activity.1,2,3,4

For awake patients, video can identify sources of noise such as muscle artifacts, blinking, chewing, forehead wrinkling, and even ear wiggling. For unconscious patients, video can identify external sources of artifact, such as electronic devices in the ICU (for example, an artificial respiration device). The inclusion of video in the EEG improves the ability to accurately diagnose a patient. Additionally, video can confirm correct electrode placement and headset positioning.

In this blog, we discuss the benefits of using video integration in EEG and what Zeto EEG can offer.

Different noise sources in EEG

EEG recordings can be impacted by various sources of noise and interference, including physiological noise, environmental noise, EEG electrode placement, electrical artifacts from EEG electrode malfunctions or from external electrical devices, and motion artifacts. These artifacts can make it difficult to distinguish genuine brain activity from noise, compromising the ability to accurately interpret EEG recordings.

Physiological noise arises from the body’s internal processes like muscle contractions, heartbeats, and eye movements, generating electrical signals that can interfere with the EEG recording. Environmental noise, on the other hand, encompasses external disturbances like electrical noise from equipment, electromagnetic interference, or ambient noise, which can introduce unwanted signals into the EEG data. Electrical artifacts can also be produced by the EEG equipment itself, resulting from issues like poor grounding, incorrect amplifier settings, or malfunctioning electrodes. Lastly, motion artifacts arise from bodily movements such as head motions, jaw opening and closing, or eye blinks, leading to distortions in the EEG signal and complicating accurate data interpretation.

To account for artifacts and enhance the interpretation of EEG recordings, video recording is often used in conjunction with EEG to identify and exclude sources of noise from the data.

Video EEG: Complement or Necessity?

Video is particularly useful for identifying artifacts related to movements or other physical activities that may produce electrical signals in the EEG recording. For example, if a patient moves their arm during an EEG recording, this movement can cause changes in the electrical activity picked up by the electrodes, which is recorded in the EEG. By observing the video recording, it is possible to identify the movement as an artifact and avoid misinterpreting the EEG data. This helps ensure that EEG signals identified as epileptiform activity represent genuine brain activity, rather than artifacts from other sources. Epileptiform waves can sometimes be difficult to distinguish from artifacts, as they can have similar characteristics in the EEG recording.

Video can also help diagnose and classify epileptic seizures and distinguish them from psychogenic nonepileptic spells and episodic abnormal movements due to other medical conditions that are not epileptic seizures.1,2,3,4,5 For example, if a patient experiences an epileptic seizure during an EEG recording, the video can help correlate the EEG signal with the visible movements and behaviors of the seizure. A psychogenic nonepileptic spell will show motion artifacts on the EEG but will not show underlying abnormal brain wave activity. Furthermore, certain behaviors such as squeezing the eyes shut while shaking, awareness during the seizure, and returning to baseline mental status right after the event can suggest a psychogenic cause.5

Sometimes tics, tremors, muscle twitching, and other abnormal movements in the tongue or a limb or digit can be mistaken for epileptic seizures, particularly in the ICU setting where subclinical seizures occur more frequently.  Subclinical seizures are epileptic seizures that are not associated with characteristic abnormal movements usually associated with seizures.  Video EEG can determine if the suspicious subtle abnormal movements are in fact due to epileptic seizures in most cases.  If the abnormal movements represent subclinical epileptic seizures, they would be expected to correlate with epileptic seizure brain wave activity on the EEG.

Video recording provides additional information about the patient’s behavior or movements at the time of a seizure or seizure-like event, which is called a seizure’s semiology.1,3,5 Gaze deviation and arm stretching right before the seizure or at seizure onset can point to the seizure origin in the brain and inform localization of seizure foci relative to brain hemispheres or specific areas such as the motor cortex, supplementary motor areas, and frontal and parietal eye fields. Seizure semiology also includes the subjective sensations and experiences immediately preceding and during a seizure.  It is critical to the diagnosis and classification of seizure disorders, which in turn affects the treatment plan. A video EEG is critical to presurgical evaluation prior to epilepsy surgery to diagnose and classify epileptic seizures when present and avoid unnecessary surgery due to psychogenic nonepileptic spells or other episodic abnormal movements not due to epileptic seizures.1

Zeto EEG: Seamless Compatibility with Any Camera, Reimbursable, Supports Up to Four Cameras

Zeto’s video integration feature reshapes the users expectations of what is possible with modern technology. The Zeto system enables simple camera controls (zooming and panning) through the cloud, ensuring simple usability.

One of the most appreciated features by users of the Zeto platform is its compatibility with any integrated or USB enabled camera. That eliminates the need for additional camera purchases and helps operators to use Zeto EEG more easily across a wide range of settings and recording locations. The Zeto Cloud Platform supports the use of up to four cameras simultaneously, providing medical professionals with the flexibility to monitor patients from multiple angles.

In addition to its compatibility with integrated and external USB cameras, Zeto offers the simple integration of IP cameras, whether they are wired or wireless. This capability is particularly beneficial when medical personnel already have pre-installed IP cameras in the room, as they can add these cameras to the Zeto Cloud Platform for a seamless integration. IP camera integration often depends on existing local IT infrastructure and cybersecurity guidelines which can result in longer integration timelines compared to integrated or USB – based camera solutions. But with the added configuration time come additional conveniences and features (such as lowlight or night vision capabilities) which often make this extended setup more than worth it.

Setup Time Price Ability to Point
Toward Patient
Optical Zoom Low Light /
Night Vision
Integrated Cameras Near
instantaneous
Integrated in most devices Static angles – requires adjusting recording device Mostly
Unavailable
Mostly unavailable in built-in devices
External
USB
Cameras
Fast – plug-in
and use
< $200 for most, <$400 for high-end Manually able to point in any direction Manual zoom in some devices Available for additional cost
IP
Cameras
Often requires IT support and additional setup < $1,500 for most Manually able to point or use of remote pan/tilt features Automatic or manual zoom options available Available in most devices

With any of these camera options, maximum image resolution depends on the utilized camera hardware, but integrated, USB, or IP camera options are available with Ultra 4k resolutions or higher. The consideration then becomes data storage size and related storage costs more than the technical ability – providers may still choose to save data in lower resolution settings simply to save storage costs.

Another powerful tool of the Zeto Cloud platform is the ability for the clinician to remotely access the recording through any device connected to the internet. Allowing for real time analysis when the provider is not present in the recording environment.

Medical practitioners will find the real-time monitoring capability invaluable, enabling them to observe patients with precision. Additionally, Zeto’s video EEGs, utilizing the integrated cameras, are eligible for reimbursement through CPT codes, specifically for EEGs lasting 24 hours or longer.

By utilizing video, Zeto ensures accurate positioning of the headset and proper electrode placement. This attention to detail guarantees the collection of reliable and precise EEG data.

In conclusion, video recording is an important complement to EEG recordings. It helps identify and exclude sources of artifact in EEG and confirms the presence of epileptic seizure activity and epileptiform discharges important for the diagnosis and classification of epileptic seizures. Video EEG also helps to identify psychogenic nonepileptic events and episodic abnormal movements from other medical conditions mistaken for epileptic seizures. By using video in conjunction with EEG, clinicians can improve the interpretation of EEG recordings, leading to more accurate diagnoses and better treatment outcomes for patients with neurological conditions.

Zeto’s video integration feature enhances convenience and accuracy, ultimately resulting in better diagnosis and treatment outcomes for patients.

Sources:

  1. https://onlinelibrary.wiley.com/doi/10.1111/j.1528-1167.2006.00656.x
  2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9259997/
  3. https://researchopenworld.com/wp-content/uploads/2020/06/AWHC-3-3-315.pdf
  4. https://www.sciencedirect.com/science/article/abs/pii/0887899495000217
  5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4206377/

ZETO – ERP EVENT MARKER INTEGRATION

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/

Zeto’s Reliable EEG Headset: Built to Withstand the Daily Grind

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:

Don’t Sweat It: Managing Sweating Artifact During EEG Recordings

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

Bringing EEG to Rural Areas with Remote EEG Monitoring

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

Billing for Zeto: Zeto EEG Billing CPT Codes

It is important to use the appropriate CPT codes when seeking reimbursement by payers for covered outpatient procedures, including routine and long-term EEG studies.  This article aims to provide guidance on potentially applicable CPT procedure codes for EEG while using Zeto EEG. The details we provide here are informational only, and you should consult your own billing advisors for what is required by your payors. Following this guidance is not a guarantee of coverage or reimbursement.

A graphic depiction of an EEG

Billing for Routine EEG

For many reasons, a routine EEG is the most commonly performed EEG study.  Choosing the correct CPT Code for routine EEG depends on two factors: how long the EEG is recorded and the patient’s state of consciousness. The EEG billing codes for the applicable time-period are set forth in Table 1. 

While procedures with a length of 20-40 minutes require a different code depending on the patient’s level of consciousness, there is a single code for EEGs lasting 41 to 60 minutes, and another single EEG billing CPT code for EEGs lasting greater than 60 minutes, but not in excess of 2 hours. The codes for the longer sessions apply whether the patient is awake, drowsy, asleep, or comatose.

The CPT Code for a 41 to 60-minute routine EEG is 95813 and the code for a routine EEG more than 60 minutes in duration is 95812 (Table 1).

Table 1. CPT Codes for Routine EEG

EEG LengthClinical StatusCPT Code
Awake and drowsy95816
20-40 minutesAwake and asleep95819
Coma or asleep95822
41-60 minutesAwake, drowsy, asleep, or in a coma95812
>60 minutesAwake, drowsy, asleep, or in a coma95813

Other EEG Billing Codes Applicable to Zeto EEG > 2 Hour Recordings

EEG recordings that last longer than 2 hours (“long-term EEG studies”) have their own set of CPT codes.  EEGs greater than 2 hours, but less than 12 hours, are billed using the CPT Codes listed in Table 2.  Additional CPT codes for EEGs greater than 12 hours are also available but are less applicable for Zeto’s current use case and we have not included them here.

The fact that these EEG billing codes are predicated on the time that the procedure takes makes it imperative that the clinician properly documents the reasons that the particular duration is medically necessary.

Another variable that affects the selection of the correct code for billing the professional component of a  long-term EEG monitoring study is whether the EEG is video-recorded. Two EEG “professional component” CPT Codes are available for studies lasting 2 to 12 hours:  95717 is the CPT Code without video, and 95718 is the code with video.

There are also technical component CPT Codes for long-term EEG studies. The CPT Codes for long-term EEG technical components vary based on whether they are unmonitored, monitored intermittently, or monitored continuously.

Importantly, Zeto’s functionality enables providers to render remote EEG reading services and intermittently and continuously monitored EEGs that can be used to render the professional services associated with the EEG billing CPT Codes listed in Table 2. Also, Zeto offers several options to record synchronized video EEG, integrating up to four video streams.

Table 2. CPT Codes for Long-Term EEG from 2 to 12 hours

VideoMonitoring*CPT Code Technical ComponentCPT Code Professional Component **
Unmonitored95705
Without VideoIntermittent9570695717
Continuous95707
Unmonitored95711
With VideoIntermittent9571295718
Continuous95713
* Zeto EEG enables providers to schedule intermittent or continuous EEG monitoring services via third party monitoring providers
** Zeto enables providers to obtain professional EEG reads via third party reading service providers

For individualized guidance on EEG billing, several third-party consulting service providers are active in the market – for questions or an introduction to a consultant familiar with Zeto, complete the form below.