Long-term EEG in adults: Sleep-deprived EEG (SDE), ambulatory EEG (Amb-EEG) and long-term video-EEG recording (LTVER)

A Complementary Dual-Mode Ion-Electron Conductive Hydrogel Enables Sustained Conductivity for Prolonged Electroencephalogram Recording

Conductive gel interface materials are widely employed as reliable agents for electroencephalogram (EEG) recording. However, prolonged EEG recording poses challenges in maintaining stable and efficient capture due to inevitable evaporation in hydrogels, which restricts sustained high conductivity. This study introduces a novel ion-electron dual-mode conductive hydrogel synthesized through a cost-effective and streamlined process. By embedding graphite nanoparticles into ionic hyaluronic acid (HAGN), the hydrogel maintains higher conductivity for over 72 h, outperforming commercial gels. Additionally, it exhibits superior low skin contact impedance, considerable electrochemical capability, and excellent tensile and adhesion performance in both dry and wet conditions. The biocompatibility of the HAGN hydrogel, verified through in vitro cell viability assays and in vivo skin irritation tests, underscores its suitability for prolonged skin contact without eliciting adverse reactions. Furthermore, in vivo EEG tests confirm the HAGN hydrogel's capability to provide high-fidelity signal acquisition across multiple EEG protocols. The HAGN hydrogel proves to be an effective interface for prolonged high-quality EEG recording, facilitating high-performance capture and classification of evoked potentials, thereby providing a reliable conductive medium for EEG-based systems.

Stroke-related epilepsy in the rehabilitation setting: Insights from the inpatient post-stroke rehabilitation study - RIPS

In stroke survivors, persistent seizure activity could be associated with poor functional outcomes. At the same time, antiepileptic over-treatment could hamper post-stroke recovery. We systematically investigated the occurrence of seizures, the prevalence of epileptic discharges, and delta slow waves on electroencephalogram (EEG) and anti-seizure medication (ASM) management in relation to clinical manifestations and EEG abnormalities. This was a multi-centre prospective study involving two intensive rehabilitation units (IRUs). Clinical and EEG data were acquired at admission to the IRU, discharge (T1), and six-month follow-up (T2). A total of 163 patients underwent EEG recording upon admission to the IRU, while 149 were available for analysis at discharge from the IRU. Eighteen patients were treated with ASMs upon IRU admission despite only five of these patients having early seizures. Among the 145 patients not treated upon admission to the IRU, eight had late seizures, of which six were during the IRU stay, while two were after discharge from the IRU. During IRU stay, ASMs were generally discontinued in patients with no early seizures reported and were started in patients with late seizures. Among the 18 patients treated with ASMs at admission to the IRU, only six maintained the therapy also at T2. Our results suggest that post-acute inpatient rehabilitation is a proper setting to observe patients treated with ASMs after stroke and provide personalized post-stroke epilepsy management.

A 0.67 μV-IIRN super-T Ω-Z IN 17.5 μW/Ch Active Electrode With In-Channel Boosted CMRR for Distributed EEG Monitoring

We present the design, development, and experimental characterization of an active electrode (AE) IC for wearable ambulatory EEG recording. The proposed architecture features in-AE double common-mode (CM) rejection, making the recording's CMRR independent of typically-significant AE-to-AE gain variations. Thanks to being DC coupled and needless of chopper stabilization for flicker noise suppression, the architecture yields a super-T Ω input impedance. Such a large input impedance makes the AE's CMRR practically immune to electrode-skin interface impedance variations across different recording channels, a critical feature for dry-electrode ambulatory systems. Signal quantization and serialization are also performed in-AE, which enables a distributed system in which all AEs use a single data bus for data/command communication to the backend module, thus significantly improving the system's scalability. Additionally, the presented AE hosts auxiliary modules for (i) detection of an unstable electrode-skin connection through continuous interface impedance monitoring, (ii) dynamic measurement and adjustment of input DC level, and (iii) a CM feedback loop for further CMRR enhancement. The article also presents the development of printed (extrusion) tattoo electrodes and their experimental characterization results with the proposed AE architecture. Besides bio-compatibility, low-cost, pattern flexibility, and quick fabrication process, the printed electrodes offer a very stable electrode-skin connection, conform to scalp shape, and exhibit consistent performance under various bending curvatures. Analog circuit blocks of the presented AE architecture are designed and fabricated using a standard 180 nm CMOS technology, and the [Formula: see text] IC is integrated with off-chip low-power digital modules on a PCB to form the AE. Our measurement results show a CMRR of 82.2 dB (at 60 Hz), amplification voltage gain of 52.8 dB, a bandwidth of 0.2-400 Hz, ±500 mV input DC offset tolerance, An input impedance [Formula: see text], and 0.67 μV RMS integrated input referred noise (0.5-100 Hz), while consuming 17.5 μW per channel. All auxiliary modules are tested experimentally, and the entire system is validated in-vivo, for both ECG and EEG recording.

Predictive value of the neutrophil-to-lymphocyte ratio for treatment response in patients diagnosed with definite or probable autoimmune encephalitis/encephalopathy

Introduction

Autoimmune encephalitis/encephalopathy (AE) is a complex and heterogeneous disease, making it difficult to predict the prognosis. The neutrophil-to-lymphocyte ratio (NLR) has emerged as a potential prognostic tool, but its usefulness remains a matter of debate. This study aimed to explore prognostic factors in cases of clinically definite or probable AE, including those with autoantibody-negative, or unknown status.

Methods

Data on patients diagnosed with definite or probable AE, including those with autoantibody-negative, or unknown status, were retrospectively collected from the admission records of our department between January 2013 and December 2022. These patients were then categorized into either a good- or poor-response group, based on their short-term treatment response. Clinical characteristics, auxiliary examinations, and treatments were compared between the two groups. A multivariable logistic regression model was constructed to identify independent predictors of poor short-term treatment response by Akaike information criterion backward stepwise method.

Results

A total of 31 patients were included in the final analysis, with 18 of them included in the poor-response group. In the univariable analysis, the poor-response group had a higher proportion of patients with a modified Rankin Scale (mRS) high score upon admission, female, epileptic seizures, or NLRs of 3.93 or higher than the good-response group (all p < 0.10). Furthermore, the multivariable logistic regression analysis revealed that the mRS score upon admission [OR: 5.51, 95% confidence intervals (CI): 1.29-23.50, p = 0.02], epileptic seizures (OR: 10.01, 95% CI: 1.16-86.66, p = 0.04), and NLRs of 3.93 or higher (OR: 11.37, 95% CI: 1.12-114.68, p = 0.04) were significantly associated with poor short-term treatment response.

Conclusion

The NLR may play a supplementary role in predicting the short-term treatment response in patients diagnosed with definite or probable AE, including those with autoantibody-negative, or unknown status.

Assessing 72 h vs. 24 h of long-term video-EEG monitoring to confirm the diagnosis of epilepsy: a retrospective observational study

Introduction

Paroxysmal seizure-like events can be a diagnostic challenge. Inpatient video-electroencephalography (EEG) monitoring (VEM) can be a valuable diagnostic tool, but recommendations for the minimal duration of VEM to confirm or rule out epilepsy are inconsistent. In this study, we aim to determine whether VEM of 48 or 72 h was superior to 24 h.

Methods

In this monocentric, retrospective study, we included 111 patients with paroxysmal, seizure-like events who underwent at least 72 h of VEM. Inclusion criteria were as follows: (1) Preliminary workup was inconclusive; (2) VEM admission occurred to confirm a diagnosis; (3) At discharge, the diagnosis of epilepsy was conclusively established. We analyzed the VEM recordings to determine the exact time point of the first occurrence of epileptic abnormalities (EAs; defined as interictal epileptiform discharges or electrographic seizures). Subgroup analyses were performed for epilepsy types and treatment status.

Results

In our study population, 69.4% (77/111) of patients displayed EAs during VEM. In this group, the first occurrence of EAs was observed within 24 h in 92.2% (71/77) of patients and within 24-72 h in 7.8% (6/77). There was no statistically significant difference in the incidence of EA between medicated and non-medicated patients or between focal, generalized epilepsies and epilepsies of unknown type. Of the 19 recorded spontaneous electroclinical seizures, 6 (31.6%) occurred after 24 h.

Discussion

A VEM of 24 h may be sufficient in the diagnostic workup of paroxysmal seizure-like events under most circumstances. Considering the few cases of first EA in the timeframe between 24 and 72 h, a prolonged VEM may be useful in cases with a high probability of epilepsy or where other strategies like sleep-EEG or ambulatory EEG show inconclusive results. Prolonged VEM increases the chance of recording spontaneous seizures. Our study also highlights a high share of subjects with epilepsy that do not exhibit EAs during 72 h of VEM.

Advances in Electrode Materials for Scalp, Forehead, and Ear EEG: A Mini-Review

Electroencephalogram (EEG) records the electrical activity of neurons in the cerebral cortex and is used extensively to diagnose, treat, and monitor psychiatric and neurological conditions. Reliable contact between the skin and the electrodes is essential for achieving consistency and for obtaining electroencephalographic information. There has been an increasing demand for effective equipment and electrodes to overcome the time-consuming and cumbersome application of traditional systems. Recently, ear-centered EEG has met with growing interest since it can provide good signal quality due to the proximity of the ear to the brain. In addition, it can facilitate mobile and unobtrusive usage due to its smaller size and ease of use, since it can be used without interfering with the patient's daily activities. The purpose of this mini-review is to first introduce the broad range of electrodes used in conventional (scalp) EEG and subsequently discuss the state-of-the-art literature about around- and in-the-ear EEG.

Recent Progress in Long-Term Sleep Monitoring Technology

Sleep is an essential physiological activity, accounting for about one-third of our lives, which significantly impacts our memory, mood, health, and children's growth. Especially after the COVID-19 epidemic, sleep health issues have attracted more attention. In recent years, with the development of wearable electronic devices, there have been more and more studies, products, or solutions related to sleep monitoring. Many mature technologies, such as polysomnography, have been applied to clinical practice. However, it is urgent to develop wearable or non-contacting electronic devices suitable for household continuous sleep monitoring. This paper first introduces the basic knowledge of sleep and the significance of sleep monitoring. Then, according to the types of physiological signals monitored, this paper describes the research progress of bioelectrical signals, biomechanical signals, and biochemical signals used for sleep monitoring. However, it is not ideal to monitor the sleep quality for the whole night based on only one signal. Therefore, this paper reviews the research on multi-signal monitoring and introduces systematic sleep monitoring schemes. Finally, a conclusion and discussion of sleep monitoring are presented to propose potential future directions and prospects for sleep monitoring.

Interictal epileptiform discharges as a predictive biomarker for recurrence of poststroke epilepsy

Poststroke epilepsy is a major ischaemic/haemorrhagic stroke complication. Seizure recurrence risk estimation and early therapeutic intervention are critical, given the association of poststroke epilepsy with worse functional outcomes, quality of life and greater mortality. Several studies have reported risk factors for seizure recurrence; however, in poststroke epilepsy, the role of EEG in predicting the risk of seizures remains unclear. This multicentre observational study aimed to clarify whether EEG findings constitute a risk factor for seizure recurrence in patients with poststroke epilepsy. Patients with poststroke epilepsy were recruited from the PROgnosis of POst-Stroke Epilepsy study, an observational multicentre cohort study. The enrolled patients with poststroke epilepsy were those admitted at selected hospitals between November 2014 and June 2017. All patients underwent EEG during the interictal period during admission to each hospital and were monitored for seizure recurrence over 1 year. Board-certified neurologists or epileptologists evaluated all EEG findings. We investigated the relationship between EEG findings and seizure recurrence. Among 187 patients with poststroke epilepsy (65 were women with a median age of 75 years) admitted to the lead hospital, 48 (25.7%) had interictal epileptiform discharges on EEG. During the follow-up period (median, 397 days; interquartile range, 337-450 days), interictal epileptiform discharges were positively correlated with seizure recurrence (hazard ratio, 3.82; 95% confidence interval, 2.09-6.97; P < 0.01). The correlation remained significant even after adjusting for age, sex, severity of stroke, type of stroke and generation of antiseizure medications. We detected periodic discharges in 39 patients (20.9%), and spiky/sharp periodic discharges were marginally associated with seizure recurrence (hazard ratio, 1.85; 95% confidence interval, 0.93-3.69; P = 0.08). Analysis of a validation cohort comprising 187 patients with poststroke epilepsy from seven other hospitals corroborated the association between interictal epileptiform discharges and seizure recurrence. We verified that interictal epileptiform discharges are a risk factor for seizure recurrence in patients with poststroke epilepsy. Routine EEG may facilitate the estimation of seizure recurrence risk and the development of therapeutic regimens for poststroke epilepsy.

The Yield of Ambulatory EEG-Video Monitoring

INTRODUCTION

The availability of ambulatory EEG-video monitoring gives an alternative to traditional inpatient EEG-video, but its yield and diagnostic value are not well known. This study evaluates the yield of ambulatory EEG-video for the diagnosis of epilepsy.

METHODS

We retrospectively reviewed the ambulatory EEG-video monitoring data from 200 consecutive and unselected patients aged 12 years and older performed by a single company (RSC Diagnostic Services) between January 2018 and May 2018. Studies were processed by two senior certified long-term monitoring EEG technologists and interpreted by neurologists.

RESULTS

Of the 200 patients, 130 (65%) were women, mean age was 45 years. Mean duration of studies were 76.6 hours (range 23-175 hours). There were 110 studies (55%) with events recorded and 101 (92%) were captured on video. Epileptic events accounted for 17.8% (18/101) of the events captured and 9% (18/200) of our total cohort. Nonepileptic diagnosis accounted for 38% of the total number of patients in study (76/200).

CONCLUSION

Ambulatory EEG-video monitoring may be a useful alternative to inpatient epilepsy monitoring unit, particularly with high clinical suspicion for nonepileptic events.

Framework for selecting and benchmarking mobile devices in psychophysiological research

Commercially available consumer electronics in (smartwatches and wearable biosensors) are increasingly enabling acquisition of peripheral physiological and physical activity data inside and outside of laboratory settings. However, there is scant literature available for selecting and assessing the suitability of these novel devices for scientific use. To overcome this limitation, the current paper offers a framework to aid researchers in choosing and evaluating wearable technologies for use in empirical research. Our seven-step framework includes: (1) identifying signals of interest; (2) characterizing intended use cases; (3) identifying study-specific pragmatic needs; (4) selecting devices for evaluation; (5) establishing an assessment procedure; (6) performing qualitative and quantitative analyses on resulting data; and, if desired, (7) conducting power analyses to determine sample size needed to more rigorously compare performance across devices. We illustrate the application of the framework by comparing electrodermal, cardiovascular, and accelerometry data from a variety of commercial wireless sensors (Affectiva Q, Empatica E3, Empatica E4, Actiwave Cardio, Shimmer) relative to a well-validated, wired MindWare laboratory system. Our evaluations are performed in two studies (N = 10, N = 11) involving psychometrically sound, standardized tasks that include physical activity and affect induction. After applying our framework to this data, we conclude that only some commercially available consumer devices for physiological measurement are capable of wirelessly measuring peripheral physiological and physical activity data of sufficient quality for scientific use cases. Thus, the framework appears to be beneficial at suggesting steps for conducting more systematic, transparent, and rigorous evaluations of mobile physiological devices prior to deployment in studies.

Ambulatory EEG Usefulness in Epilepsy Management

SUMMARY

Long-term video-EEG monitoring has been the gold standard for diagnosis of epileptic and nonepileptic events. Medication changes, safety, and a lack of recording EEG in one's habitual environment may interfere with diagnostic representation and subsequently affect management. Some spells defy standard EEG because of ultradian and circadian times of occurrence, manifest nocturnal expression of epileptiform activity, and require classification for clarifying diagnostic input to identify optimal treatment. Some patients may be unaware of seizures, have frequent events, or subclinical seizures that require quantification before optimal management. The influence on antiseizure drug management and clinical drug research can be enlightened by long-term outpatient ambulatory EEG monitoring. With recent governmental shifts to focus on mobile health, ambulatory EEG monitoring has grown beyond diagnostic capabilities to target the dynamic effects of medical and nonmedical treatment for patients with epilepsy in their natural environment. Furthermore, newer applications in ambulatory monitoring include additional physiologic parameters (e.g., sleep, detection of myogenic signals, etc.) and extend treatment relevance to patients beyond seizure reduction alone addressing comorbid conditions. It is with this focus in mind that we direct our discussion on the present and future aspects of using ambulatory EEG monitoring in the treatment of patients with epilepsy.

Long-term Home Video EEG for Recording Clinical Events

SUMMARY

Around 50 years after the first EEG acquisition by Hans Berger, its use in ambulatory setting was demonstrated. Ever since, ambulatory EEG has been widely available and routinely used in the United States (and to a lesser extent in Europe) for diagnosis and management of patients with epilepsy. This technology alone cannot help with semiological characterization, and absence of video is one of its main drawbacks. Addition of video to ambulatory EEG potentially improves diagnostic yield and opens new aspects of utility for better characterization of patient's events, including differential diagnosis, classification, and quantification of seizure burden. Studies evaluating quality of ambulatory video EEG (aVEEG) suggest good quality recordings are feasible. In the utilization of aVEEG, to maximize yield, it is important to consider pretest probability. Having clear pretest questions and a strong index of suspicion for focal, generalized convulsive or non-epileptic seizures further increases the usefulness of aVEEG. In this article, which is part of the topical issue "Ambulatory EEG," the authors compare long-term home aVEEG to inpatient video EEG monitoring, discuss aVEEG's use in diagnosis and follow-up of patients, and present the authors' own experience of the utility of aVEEG in a teaching hospital setting.

When should we obtain a routine EEG while managing people with epilepsy?

More than eight decades after its discovery, routine electroencephalogram (EEG) remains a safe, noninvasive, inexpensive, bedside test of neurological function. Knowing when a routine EEG should be obtained while managing people with epilepsy is a critical aspect of optimal care. Despite advances in neuroimaging techniques that aid diagnosis of structural lesions in the central nervous system, EEG continues to provide critical diagnostic evidence with implications on treatment. A routine EEG performed after a first unprovoked seizure can support a clinical diagnosis of epilepsy and differentiate those without epilepsy, classify an epilepsy syndrome to impart prognosis, and characterize seizures for antiseizure management. Despite a current viral pandemic, EEG services continue, and the value of routine EEG is unchanged.

Is Brain Dynamics Preserved in the EEG After Automated Artifact Removal? A Validation of the Fingerprint Method and the Automatic Removal of Cardiac Interference Approach Based on Microstate Analysis

The assessment of a method for removing artifacts from electroencephalography (EEG) datasets often disregard verifying that global brain dynamics is preserved. In this study, we verified that the recently introduced optimized fingerprint method and the automatic removal of cardiac interference (ARCI) approach not only remove physiological artifacts from EEG recordings but also preserve global brain dynamics, as assessed with a new approach based on microstate analysis. We recorded EEG activity with a high-resolution EEG system during two resting-state conditions (eyes open, 25 volunteers, and eyes closed, 26 volunteers) known to exhibit different brain dynamics. After signal decomposition by independent component analysis (ICA), the independent components (ICs) related to eyeblinks, eye movements, myogenic interference, and cardiac electromechanical activity were identified with the optimized fingerprint method and ARCI approach and statistically compared with the outcome of the expert classification of the ICs by visual inspection. Brain dynamics in two different groups of denoised EEG signals, reconstructed after having removed the artifactual ICs identified by either visual inspection or the automated methods, was assessed by calculating microstate topographies, microstate metrics (duration, occurrence, and coverage), and directional predominance (based on transition probabilities). No statistically significant differences between the expert and the automated classification of the artifactual ICs were found (p > 0.05). Cronbach’s α values assessed the high test–retest reliability of microstate parameters for EEG datasets denoised by the automated procedure. The total EEG signal variance explained by the sets of global microstate templates was about 80% for all denoised EEG datasets, with no significant differences between groups. For the differently denoised EEG datasets in the two recording conditions, we found that the global microstate templates and the sequences of global microstates were very similar (p < 0.01). Descriptive statistics and Cronbach’s α of microstate metrics highlighted no significant differences and excellent consistency between groups (p > 0.5). These results confirm the ability of the optimized fingerprint method and the ARCI approach to effectively remove physiological artifacts from EEG recordings while preserving global brain dynamics. They also suggest that microstate analysis could represent a novel approach for assessing the ability of an EEG denoising method to remove artifacts without altering brain dynamics.

Diagnostic yield of seizure recordings and neuroimaging in patients with focal epilepsy without interictal epileptiform discharges

OBJECTIVE

Repeated routine electroencephalography (EEG) or even long-term video-EEG monitoring (VEM) does not always record interictal epileptiform discharges (IEDs) in some patients with epilepsy. The present study investigated whether focal seizures detected by VEM and focal abnormalities on neuroimaging are useful for the diagnosis of patients with focal epilepsy without IEDs.

METHODS

We retrospectively reviewed 409 consecutive patients with focal epilepsy (207 men, aged 9 to 76 years) who underwent 4- or 5-day VEM, magnetic resonance imaging (MRI), and fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) for diagnosis to identify patients without IEDs. The occurrence of focal seizures during VEM and the presence of focal abnormalities on neuroimaging were investigated in those patients. The occurrence rate of seizures during VEM was investigated in patients with daily, weekly, monthly, and yearly seizure frequency based on history-taking.

RESULTS

Ninety-five (23.2%) of 409 patients with focal epilepsy did not have IEDs. Fifty-five (57.9%) of the 95 patients had focal seizures during VEM. Fifty-four patients (56.8%) showed focal abnormalities compatible with seizure semiology on neuroimaging investigations. Neither seizure recordings nor neuroimaging abnormalities were seen in 16 (16.8%) of the 95 patients. The occurrence rate of seizures during VEM depended on the seizure frequency at history-taking. However, 28 (45.9%) of 61 patients with monthly and yearly seizure frequency had focal seizures during 4- or 5-day VEM with seizure induction.

CONCLUSIONS

Video-EEG monitoring can detect focal seizures in patients with focal epilepsy but no IEDs. Comprehensive assessment including VEM and neuroimaging study is important for the diagnosis.

Review of semi-dry electrodes for EEG recording

Developing reliable and user-friendly electroencephalography (EEG) electrodes remains a challenge for emerging real-world EEG applications. Classic wet electrodes are the gold standard for recording EEG; however, they are difficult to implement and make users uncomfortable, thus severely restricting their widespread application in real-life scenarios. An alternative is dry electrodes, which do not require conductive gels or skin preparation. Despite their quick setup and improved user-friendliness, dry electrodes still have some inherent problems (invasive, relatively poor signal quality, or sensitivity to motion artifacts), which limit their practical utilization. In recent years, semi-dry electrodes, which require only a small amount of electrolyte fluid, have been successfully developed, combining the advantages of both wet and dry electrodes while addressing their respective drawbacks. Semi-dry electrodes can collect reliable EEG signals comparable to wet electrodes. Moreover, their setup is as fast and convenient similar to that of dry electrodes. Hence, semi-dry electrodes have shown tremendous application prospects for real-world EEG acquisition. Herein, we systematically summarize the development, evaluation methods, and practical design considerations of semi-dry electrodes. Some feasible suggestions and new ideas for the development of semi-dry electrodes have been presented. This review provides valuable technical support for the development of semi-dry electrodes toward emerging practical applications.

An investigation into the diagnostic accuracy, reliability, acceptability and safety of a novel device for Continuous Ambulatory Vestibular Assessment (CAVA)

Dizziness is a common condition that is responsible for a significant degree of material morbidity and burden on health services. It is usually episodic and short-lived, so when a patient presents to their clinician, examination is normal. The CAVA (Continuous Ambulatory Vestibular Assessment) device has been developed to provide continuous monitoring of eye-movements, allowing insight into the physiological parameters present during a dizziness attack. This article describes the first clinical investigation into the medical and technical aspects of this new diagnostic system. Seventeen healthy subjects wore the device near continuously for up to thirty days, artificially inducing nystagmus on eight occasions. 405 days' worth of data was captured, comprising around four billion data points. A computer algorithm developed to detect nystagmus demonstrated a sensitivity of 99.1% (95% CI: 95.13% to 99.98%) and a specificity of 98.6% (95% CI: 96.54% to 99.63%). Eighty-two percent of participants wore the device for a minimum of eighty percent of each day. Adverse events were self-limiting and mostly the consequence of skin stripping from the daily replacement of the electrodes. The device was shown to operate effectively as an ambulatory monitor, allowing the reliable detection of artificially induced nystagmus.

Contact Pressure and Flexibility of Multipin Dry EEG Electrodes

In state-of-the-art electroencephalography (EEG) Silver/Silver-Chloride electrodes are applied together with electrolyte gels or pastes. Their application requires extensive preparation, trained medical staff and limits measurement time and mobility. We recently proposed a novel multichannel cap system for dry EEG electrodes for mobile and out-of-the-lab EEG acquisition. During the tests with these novel polymer-based multipin dry electrodes, we observed that the quality of the recording depends on the applied normal force and resulting contact pressure. Consequently, in this paper we systematically investigate the influence of electrode-skin contact pressure and electrode substrate flexibility on interfacial impedance and perceived wearing comfort in a study on 12 volunteers. The normal force applied to the electrode was varied between the minimum required force to achieve impedances and a maximum of 4 N, using a new force measurement applicator. We found that for a polymer shore hardness A98, with increasing normal force, the impedance decreases from and to and at frontal hairless and temporal hairy positions, respectively. Similar results were obtained for shore A90, A80, and A70. The best compromise of low and stable impedances as well as a good wearing comfort was determined for applied normal forces between 2 and 3 N using electrodes with shore A98 or A90. Our results provide the basis for improved EEG cap designs with optimal wearing comfort and recording quality for dry multipin electrodes, which will enable new fields of application for EEG.

Multiphasic Side-Switching Seizures Are Easily Misdiagnosed as Unilateral Seizures During a Single EEG Monitoring Session: A Specific Subtype of Bitemporal Epilepsy

BACKGROUND

Bitemporal epilepsy (BTLE) is a specific anatomoelectroclinical phenotype in the spectrum of temporal lobe epilepsy. The diagnosis of BTLE and the evaluation of the degree of seizure lateralization in BTLE patients are greatly influenced by the duration of EEG recording and the number of recorded habitual seizures.

CASE DESCRIPTION

A 25-year-old woman had a 5-year history of seizures. Her habitual seizures were described as sudden behavioral arrest, staring, unresponsiveness, and oral automatisms, with auras of fear and palpitation. Intermittent scalp electroencephalography (EEG) and intracranial EEG monitoring over 3 years showed multiphasic side-switching seizures. The seizures were limited to 1 temporal lobe within 1 phase and switched sides between phases. Despite antiepileptic drugs and vagus nerve stimulation, her seizures remained uncontrolled. The patient finally underwent unilateral anteromedial temporal lobectomy, mainly based on >60% of seizures recorded originating from the left side. The patient has been seizure free for more than 1 year at last follow-up.

CONCLUSIONS

This patient presented 1 specific subtype of BTLE that is prone to be misdiagnosed as unilateral temporal lobe epilepsy if the patient is recorded for a relatively short term, e.g., over a common EEG monitoring duration of 1 to 2 weeks.

Wearable brain imaging with multimodal physiological monitoring

The brain is a central component of cognitive and physical human performance. Measures, including functional brain activation, cerebral perfusion, cerebral oxygenation, evoked electrical responses, and resting hemodynamic and electrical activity are all related to, or can predict, health status or performance decrements. However, measuring brain physiology typically requires large, stationary machines that are not suitable for mobile or self-monitoring. Moreover, when individuals are ambulatory, systemic physiological fluctuations—e.g., in heart rate, blood pressure, skin perfusion, and more—can interfere with noninvasive brain measurements. In efforts to address the physiological monitoring and performance assessment needs for astronauts during spaceflight, we have developed easy-to-use, wearable prototypes, such as NINscan, for near-infrared scanning, which can collect synchronized multimodal physiology data, including hemodynamic deep-tissue imaging (including brain and muscles), electroencephalography, electrocardiography, electromyography, electrooculography, accelerometry, gyroscopy, pressure, respiration, and temperature measurements. Given their self-contained and portable nature, these devices can be deployed in a much broader range of settings—including austere environments—thereby, enabling a wider range of novel medical and research physiology applications. We review these, including high-altitude assessments, self-deployable multimodal e.g., (polysomnographic) recordings in remote or low-resource environments, fluid shifts in variable-gravity, or spaceflight analog environments, intracranial brain motion during high-impact sports, and long-duration monitoring for clinical symptom-capture in various clinical conditions. In addition to further enhancing sensitivity and miniaturization, advanced computational algorithms could help support real-time feedback and alerts regarding performance and health.

A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings

Background

EEG may be affected by artefacts hindering the analysis of brain signals. Data-driven methods like independent component analysis (ICA) are successful approaches to remove artefacts from the EEG. However, the ICA-based methods developed so far are often affected by limitations, such as: the need for visual inspection of the separated independent components (subjectivity problem) and, in some cases, for the independent and simultaneous recording of the inspected artefacts to identify the artefactual independent components; a potentially heavy manipulation of the EEG signals; the use of linear classification methods; the use of simulated artefacts to validate the methods; no testing in dry electrode or high-density EEG datasets; applications limited to specific conditions and electrode layouts.

Methods

Our fingerprint method automatically identifies EEG ICs containing eyeblinks, eye movements, myogenic artefacts and cardiac interference by evaluating 14 temporal, spatial, spectral, and statistical features composing the IC fingerprint. Sixty-two real EEG datasets containing cued artefacts are recorded with wet and dry electrodes (128 wet and 97 dry channels). For each artefact, 10 nonlinear SVM classifiers are trained on fingerprints of expert-classified ICs. Training groups include randomly chosen wet and dry datasets decomposed in 80 ICs. The classifiers are tested on the IC-fingerprints of different datasets decomposed into 20, 50, or 80 ICs. The SVM performance is assessed in terms of accuracy, False Omission Rate (FOR), Hit Rate (HR), False Alarm Rate (FAR), and sensitivity (p). For each artefact, the quality of the artefact-free EEG reconstructed using the classification of the best SVM is assessed by visual inspection and SNR.

Results

The best SVM classifier for each artefact type achieved average accuracy of 1 (eyeblink), 0.98 (cardiac interference), and 0.97 (eye movement and myogenic artefact). Average classification sensitivity (p) was 1 (eyeblink), 0.997 (myogenic artefact), 0.98 (eye movement), and 0.48 (cardiac interference). Average artefact reduction ranged from a maximum of 82% for eyeblinks to a minimum of 33% for cardiac interference, depending on the effectiveness of the proposed method and the amplitude of the removed artefact. The performance of the SVM classifiers did not depend on the electrode type, whereas it was better for lower decomposition levels (50 and 20 ICs).

Discussion

Apart from cardiac interference, SVM performance and average artefact reduction indicate that the fingerprint method has an excellent overall performance in the automatic detection of eyeblinks, eye movements and myogenic artefacts, which is comparable to that of existing methods. Being also independent from simultaneous artefact recording, electrode number, type and layout, and decomposition level, the proposed fingerprint method can have useful applications in clinical and experimental EEG settings.

Modular multipin electrodes for comfortable dry EEG

Electrode and cap concepts for continuous and ubiquitous monitoring of brain activity will open up new fields of application and contribute to increased use of electroencephalography (EEG) in clinical routine, neurosciences, brain-computer-interfacing and out-of-the-lab monitoring. However, mobile and unobtrusive applications are currently hindered by the lack of applicable convenient and reliable electrode and cap systems. We propose a novel modular electrode concept based on a flexible polymer substrate, coated with electrically conductive metallic films. The overall concept enables design adaptation to different head regions and cap designs. We describe the single modules of the system and investigate the influence of electrode pin number, coating material and adduction force on electrode-skin impedance and perceived wearing comfort. Our results contribute to rapid and comfortable multichannel dry EEG.

Understanding the self-management skills of persons with epilepsy

PURPOSE

To determine whether the self-management skills of persons with epilepsy (PWE) vary across the different domains of the Epilepsy Self-Management Scale (ESMS).

METHODS

172 PWE completed a survey questionnaire as well as the ESMS.

RESULTS

Using ANOVA with pairwise comparison, the mean item scores of the medication, seizure, and safety management subscales of the ESMS were significantly higher than the lifestyle and information management subscales (p<0.01). The mean item score for the lifestyle management subscale was significantly higher than the information management subscale (p<0.01).

CONCLUSION

PWE in our population performed differently across the various domains of the ESMS and did worse on the lifestyle and information management subscales. We discuss the implications of this on patient counseling and education.

The role of outpatient ambulatory electroencephalography in the diagnosis and management of adults with epilepsy or nonepileptic attack disorder: A systematic literature review

Electroencephalography (EEG) is an established diagnostic tool with important implications for the clinical management of patients with epilepsy or nonepileptic attack disorder. Different types of long-term EEG recording strategies have been developed over the last decades, including the widespread use of ambulatory electroencephalography (AEEG), which holds great potential in terms of both clinical usefulness and cost-effectiveness. In this paper, we present the results of a systematic review of the scientific literature on the use of AEEG in the diagnosis of epilepsy and nonepileptic attacks in adult patients. Taken together, our findings confirmed that AEEG is a useful diagnostic tool in patients with equivocal findings on routine EEG studies and influences management decisions in the majority of studies. There is evidence that AEEG is also more likely to capture events than sleep-deprived EEG; however, there are currently insufficient data available to compare the diagnostic utility of modern AEEG technology with inpatient video-telemetry. Further research on the combined use of AEEG and home-video recording is, therefore, warranted.