EEG Montage Research Articles

Electroencephalogram abnormalities in patients with NREM parasomnias

ObjectiveElectroencephalographic (EEG) changes in patients with NREM parasomnias (NRP) occur in sleep architecture as changes in slow wave sleep or cyclic pattern, which are not considered abnormal. However, abnormalities in EEG in these patients have recently been reported, indicating that EEG patterns in NRPs are not definitive. Moreover, most of the polysomnography (PSG) findings in NRP patients were reported in the adult population requiring data from pediatric population to avoid bias in conclusion. MethodsIn sum, 39 patients with a NRP were undergone comprehensive assessments including a PSG with additional EEG montages. EEG recordings were evaluated in patients without a history of epilepsy and further compared between pediatric and adult patients. ResultsTwenty-three (59%) of the patients were pediatric and 77% were male. The mean age was 18.4 (±13.1) years. Of the patients, 19 (49%) had somnambulism, 13 (33%) had confusional arousal and seven (18%) had sleep terrors. Macrostructure of sleep detected by PSG was normal in all patients. After excluding 11 (28%) patients with a positive history of epilepsy, seven (25%) of 28 showed EEG abnormalities within K-complexes in NREM-II stage, six of whom were pediatric patients compared to only one adult (p < 0.05). ConclusionThis study showed that patients with NRP may display EEG abnormalities in NREM-II stage. These abnormalities were more frequent in pediatric patients compared to adults. In NRP patients, utmost care should be taken in EEG evaluations to prevent false diagnosis of epilepsy.

Spatial localization of EEG electrodes using 3D scanning

Objective. A reliable reconstruction of neural activity using high-density electroencephalography (EEG) requires an accurate spatial localization of EEG electrodes aligned to the structural magnetic resonance (MR) image of an individual’s head. Current technologies for electrode positioning, such as electromagnetic digitization, are yet characterized by non-negligible localization and co-registration errors. In this study, we propose an automated method for spatial localization of EEG electrodes using 3D scanning, a non-invasive and easy-to-use technology with potential applications in clinical settings. Approach. Our method consists of three main steps: (1) the 3D scan is ambient light-corrected and spatially aligned to the head surface extracted from the anatomical MR image; (2) electrode positions are identified by segmenting the 3D scan based on predefined colour and topological properties; (3) electrode labelling is performed by aligning an EEG montage template to the electrode positions. The performance of the method was assessed on data collected in eight participants wearing high-density EEG caps with 128 sensors, from three different manufacturers. We estimated the co-registration error using the distance between the MR-based head shape and the closest 3D scan points. Also, we quantified the positioning error using the distance between the detected electrode positions and the corresponding locations manually selected on the 3D scan data. Main results. For all participants and EEG caps, we obtained a median error of co-registration below 3.0 mm and of spatial localization below 1.4 mm. The method based on 3D scanning data was significantly more precise compared to the electromagnetic digitization technique, and the total time required for obtaining electrode positions was reduced by about half. Significance. We have introduced a method to automatically detect EEG electrodes based on 3D scanning information. We believe that our work can contribute to a more effective, reliable and widespread use of high-density EEG as brain imaging tool.

Preliminary experience with point-of-care EEG in post-cardiac arrest patients

ObjectiveAbnormal electroencephalography (EEG) patterns are common after resuscitation from cardiac arrest and have clinical and prognostic importance. Bedside continuous EEGs are not available in many institutions. We tested the feasibility of using a point-of-care system for EEG acquisition. MethodsWe prospectively enrolled a convenience sample of post-cardiac arrest patients between 9/2015–1/2017. Upon hospital arrival, a limited EEG montage was applied. We tested both continuous EEG (cEEG) and this point-of-care EEG (eEEG). A board-certified epileptologist and a board-certified neurointensivist jointly reviewed all EEGs. Cohen’s kappa coefficient evaluated agreement between eEEG and cEEG and Fisher’s exact test evaluated their associations with survival to hospital discharge and proximate cause of death. ResultsWe studied 95 comatose post-cardiac arrest patients. Mean age was 59 (SD17) years. Most (61%) were male, few (N = 22; 23%) demonstrated shockable rhythms, and PCAC IV illness severity was present in 58 (61%). eEEG was interpretable in 57 (60%) subjects. The most common eEEG interpretations were: continuous (21%), generalized suppression (14%), burst-suppression (12%) and burst-suppression with identical bursts (10%). Seizures were detected in 2 eEEG subjects (2%). No patient with seizure or burst-suppression with identical bursts survived. cEEG demonstrated generalized suppression (31%), burst-suppression with identical bursts (27%), continuous (18%) and seizure (4%). The eEEG and cEEG demonstrated fair agreement (kappa = 0.27). Neither eEEG nor cEEG was associated with survival (p = 0.19; p = 0.11) or proximate cause of death (p = 0.14; p = 0.8) ConclusionseEEG is feasible, although artifact often precludes interpretation. eEEG is fairly associated with cEEG and may facilitate post-cardiac arrest care.

Intrinsic network reactivity differentiates levels of consciousness in comatose patients

ObjectiveWe devise a data-driven framework to assess the level of consciousness in etiologically heterogeneous comatose patients using intrinsic dynamical changes of resting-state Electroencephalogram (EEG) signals. MethodsEEG signals were collected from 54 comatose patients (GCS ⩽ 8) and 20 control patients (GCS > 8). We analyzed the EEG signals using a new technique, termed Intrinsic Network Reactivity Index (INRI), that aims to assess the overall lability of brain dynamics without the use of extrinsic stimulation. The proposed technique uses three sigma EEG events as a trigger for ensuing changes to the directional derivative of signals across the EEG montage. ResultsThe INRI had a positive relationship with GCS and was significantly different between various levels of consciousness. In comparison, classical band-limited power analysis did not show any specific patterns correlated to GCS. ConclusionsThese findings suggest that reaching low variance EEG activation patterns becomes progressively harder as the level of consciousness of patients deteriorate, and provide a quantitative index based on passive measurements that characterize this change. SignificanceOur results emphasize the role of intrinsic brain dynamics in assessing the level of consciousness in coma patients and the possibility of employing simple electrophysiological measures to recognize the severity of disorders of consciousness (DOC).

Transferring Shared Responses Across Electrode Montages for Facilitating Calibration in High-Speed Brain Spellers.

Recent studies have shown that using the user's average steady-state visual evoked responses (SSVEPs) as the template to template-matching methods could significantly improve the accuracy and speed of the SSVEP-based brain- computer interface (BCI). However, collecting the pilot data for each individual can be time-consuming. To resolve this practical issue, this study aims to explore the feasibility of leveraging pre- recorded datasets from the same users by transferring common electroencephalogram (EEG) responses across different sessions with the same or different electrode montages. The proposed method employs spatial filtering techniques including response averaging, canonical correlation analysis (CCA), and task- related component analysis (TRCA) to project scalp EEG recordings onto a shared response domain. The transferability was evaluated by using 40-class SSVEPs recorded from eight subjects with nine electrodes on two different days. Three subsets of electrode montages were selected to simulate different scenarios such as identical, partly overlapped, and non-overlapped electrode placements across two sessions. The target identification accuracy of the proposed methods with transferred training data significantly outperformed a conventional training-free algorithm. The result suggests training data required in the BCI speller could be transferred from different EEG montages and/or headsets.

Automated detection of electroencephalography artifacts in human, rodent and canine subjects using machine learning

BackgroundElectroencephalography (EEG) invariably contains extra-cranial artifacts that are commonly dealt with based on qualitative and subjective criteria. Failure to account for EEG artifacts compromises data interpretation. New MethodWe have developed a quantitative and automated support vector machine (SVM)-based algorithm to accurately classify artifactual EEG epochs in awake rodent, canine and humans subjects. An embodiment of this method also enables the determination of ‘eyes open/closed’ states in human subjects. ResultsThe levels of SVM accuracy for artifact classification in humans, Sprague Dawley rats and beagle dogs were 94.17%, 83.68%, and 85.37%, respectively, whereas 'eyes open/closed' states in humans were labeled with 88.60% accuracy. Each of these results was significantly higher than chance. Comparison with Existing MethodsOther existing methods, like those dependent on Independent Component Analysis, have not been tested in non-human subjects, and require full EEG montages, instead of only single channels, as this method does. ConclusionsWe conclude that our EEG artifact detection algorithm provides a valid and practical solution to a common problem in the quantitative analysis and assessment of EEG in pre-clinical research settings across evolutionary spectra.

Sensitivity of a Reduced EEG Montage for Seizure Detection in the Neurocritical Care Setting.

Neurocritical care units commonly implement the double-distance reduced EEG montage in postoperative neurosurgic patients who have structural barriers that hinder the placement of a standard 10-20 system array. Despite its widespread use, its sensitivity has not been adequately addressed. We evaluated the sensitivity and specificity of this montage for seizure detection. One hundred fifty-five full-montage continuous EEGs (cEEGs) completed in the Johns Hopkins University neurocritical care unit containing unequivocal electrographic seizures, status epilepticus, or other abnormalities were selected, comprising 73 ictal and 82 nonictal EEGs. EEGs were reformatted to the reduced montage, and 2-hour clips were reviewed independently by 2 epileptologists who documented the presence of seizures, status, or background abnormalities. The sensitivity and specificity of the reduced montage for electrographic seizure detection was 81% and 92% with substantial interrater agreement (kappa 0.71). The sensitivity for status epilepticus was lower at 69%, but specificity remained high at 97% (kappa 0.67). Several EEGs miscategorized as nonictal were labeled as rather having rhythmic activity or periodic discharges. Evaluation of background patterns on the ictal-interictal continuum resulted in sensitivities ranging from 68% to 83%. Although the specificity of the reduced array is good, epileptologists should remain vigilant when monitoring patients using this montage, given its reduced sensitivity for epileptic activity, especially status epilepticus.

Platform Session – Evoked potentials & NIOM: Reduced electrode arrays for the automated detection of rhythmic and periodic patterns in the intensive care unit: Frequently tried, frequently failed?

Introduction To investigate the effect of systematic electrode reduction from a common 10–20 EEG system on pattern detection sensitivity (SEN). Methods Two reviewers rated 17,130 one-minute segments of 83 prospectively recorded cEEGs according to the ACNS standardized critical care EEG terminology (CCET), including burst suppression patterns (BS) and unequivocal electrographic seizures. Consensus annotations between reviewers were used as a gold standard to determine pattern detection SEN and specificity (SPE) of a computational algorithm (baseline, 19 electrodes). Electrodes were than reduced one by one in four different variations. SENs and SPEs were calculated to determine the most beneficial assembly with respect to the number and location of electrodes. Results High automated baseline SENs (84.99–93.39%) and SPEs (90.05–95.6%) were achieved for all patterns. Best overall results in detecting BS and CCET patterns were found using the “hairline + vertex” montage. While the “forehead + behind ear” montage showed an advantage in detecting ictal patterns, reaching a 15% drop of SEN with 10 electrodes, all montages could detect BS sufficiently if at least nine electrodes were available. Conclusion For the first time an automated approach was used to systematically evaluate the effect of electrode reduction on pattern detection SEN in cEEG. Prediction of the expected detection SEN of specific EEG patterns with reduced EEG montages in ICU patients.

S80. Utility of reduced montage EEG in detecting seizures or seizure-like activity

Introduction Standard scalp EEG is used to detect a wide range of cerebral pathologies. However, its utility in emergency and resource-limited settings may be impeded by delays in setup and interpretation. Past studies have investigated reduced channel arrays as screening tools, but inferred a lower utility in detecting epileptiform abnormalities. The current study tested the utility of reduced (8-channel) montage (rm-EEG) covering the lateral hemispheres compared to full (18-channel) montage (fm-EEG) for detection of generalized and hemispheric seizures and seizure-like patterns by neurologists with extensive EEG training, neurology residents with minimal EEG training, and medical students without EEG training. Methods Forty neurologists (7 epileptologists, 13 epilepsy fellows, 20 neurology residents) from 7 institutions and 42 medical students from Stanford University were presented 44 samples of EEG recordings (15-s long) as both fm-EEG and rm-EEG formats in a random order. Samples represented seizures ( n = 8), seizure-like activity (lateralized or generalized periodic discharges or burst suppression, n = 12) or non-rhythmic, non-periodic patterns (normal or slowing, n = 24) as determined by majority agreement among 3 senior epileptologists with >10 years of training (Fleiss’ kappa 0.79). Both physicians and students were asked to determine whether each sample represented seizure activity (yes/no), while epileptologists and residents were also asked to specify any and all pathological activity present in each sample. We calculated the overall accuracy of fm-EEG and rm-EEG, as well as their sensitivity and specificity for seizures and seizure-like activity; differences were assessed using paired t -tests. Results EEG samples were evaluated with almost identical accuracy using fm-EEG (epileptologists: 88%; residents: 75%; students: 57%) and rm-EEG (epileptologists: 84%, p = 0.156; residents: 75%, p = 0.086; students: 57%, p = 0.461). While epileptologists identified hemispheric or generalized seizure activity with high sensitivity using fm-EEG (99%) and rm-EEG (94%, p = 0.172), individuals with minimal or no EEG experience demonstrated lower sensitivity using rm-EEG (residents: 79%; students: 45%) compared to fm-EEG (residents: 91%, p = 0.031; students: 62%, p = 0.048). However, specificity for seizures/seizure-like activity was greater using rm-EEG (epileptologists: 91%; residents: 84%; students: 73%) compared to fm-EEG (epileptologists: 85%, p = 0.015; residents: 77%, p = 0.018; students: 63%, p Conclusion Our study demonstrates that a reduction from 18 to 8 channels does not degrade the sensitivity for generalized and hemispheric seizures, and yet provide more specific information for ruling in such epileptic activity even when read by individuals with minimal or no EEG experience. On the basis of these findings, we suggest that a restricted channel configuration can be used for faster diagnosis of generalized and hemispheric seizures that ought to be detected and treated expeditiously.

A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance.

Motor imagery–based brain–computer interface (BCI) using electroencephalography (EEG) has demonstrated promising applications by directly decoding users' movement related mental intention. The selection of control signals, e.g., the channel configuration and decoding algorithm, plays a vital role in the online performance and progressing of BCI control. While several offline analyses report the effect of these factors on BCI accuracy for a single session—performance increases asymptotically by increasing the number of channels, saturates, and then decreases—no online study, to the best of our knowledge, has yet been performed to compare for a single session or across training. The purpose of the current study is to assess, in a group of forty-five subjects, the effect of channel number and decoding method on the progression of BCI performance across multiple training sessions and the corresponding neurophysiological changes. The 45 subjects were divided into three groups using Laplacian Filtering (LAP/S) with nine channels, Common Spatial Pattern (CSP/L) with 40 channels and CSP (CSP/S) with nine channels for online decoding. At the first training session, subjects using CSP/L displayed no significant difference compared to CSP/S but a higher average BCI performance over those using LAP/S. Despite the average performance when using the LAP/S method was initially lower, but LAP/S displayed improvement over first three sessions, whereas the other two groups did not. Additionally, analysis of the recorded EEG during BCI control indicates that the LAP/S produces control signals that are more strongly correlated with the target location and a higher R-square value was shown at the fifth session. In the present study, we found that subjects' average online BCI performance using a large EEG montage does not show significantly better performance after the first session than a smaller montage comprised of a common subset of these electrodes. The LAP/S method with a small EEG montage allowed the subjects to improve their skills across sessions, but no improvement was shown for the CSP method.

Evidence of Variabilities in EEG Dynamics During Motor Imagery-Based Multiclass Brain-Computer Interface.

Inter-subject and inter-session variabilities pose a significant challenge in electroencephalogram (EEG)-based brain-computer interface (BCI) systems. Furthermore, high dimensional EEG montages introduce huge computational burden due to excessive number of channels involved. Two experimental, i.e., inter-session and inter-subject, variabilities of EEG dynamics during motor imagery (MI) tasks are investigated in this paper. In particular, the effect on the performance of the BCIs due to day-to-day variability in EEG dynamics during the alterations in cognitive stages is explored. In addition, the inter-subject BCIs feasibility between cortically synchronized and desynchronized subject pairs on pairwise performance associativity is further examined. Moreover, the consequences of integrating spatial brain dynamics of varying the number of channels - from specific regions of the brain - are also discussed in case of both the contexts. The proposed approach is validated on real BCI data set containing EEG data from four classes of MI tasks, i.e., left/right hand, both feet, and tongue, subjected prior to a preprocessing of three different spatial filtering techniques. Experimental results have shown that a maximum classification accuracy of around 58% was achieved for the inter-subject experimental case, whereas a 31% deviation was noticed in the classification accuracies across two sessions during the inter-session experimental case. In conclusion, BCIs, without the subject-and session-specific calibration and with lesser number of channels employed, play a vital role while promoting a generic and efficient framework for plug and play use.

Quality of frequency-following response to speech sounds linked with left prefrontal hemodynamic activity using fNIRS+EEG

Quality of frequency-following response to speech sounds linked with left prefrontal hemodynamic activity using fNIRS+EEG

Diagnostic utility of eight-channel EEG for detecting generalized or hemispheric seizures and rhythmic periodic patterns

ObjectivesTo compare the diagnostic utility of electroencephalography (EEG) using reduced, 8-channel montage (rm-EEG) to full, 18-channel montage (fm-EEG) for detection of generalized or hemispheric seizures and rhythmic periodic patterns (RPPs) by neurologists with extensive EEG training, neurology residents with minimal EEG exposure, and medical students without EEG experience. MethodsWe presented EEG samples in both fm-EEG (bipolar montage) and rm-EEG (lateral leads of bipolar montage) to 20 neurologists, 20 residents, and 42 medical students. Unanimous agreement of three senior epileptologists defined samples as seizures (n = 7), RPPs (n = 10), and normal or slowing (n = 20). Differences in median accuracy, sensitivity, and specificity were assessed using Wilcoxon signed-rank tests. ResultsFull and reduced EEG demonstrated similar accuracy when read by neurologists (fm-EEG: 95%, rm-EEG: 95%, p = 0.29), residents (fm-EEG: 80%, rm-EEG: 80%, p = 0.05), and students (fm-EEG: 60%, rm-EEG: 51%, p = 0.68). Moreover, neurologists’ sensitivity for detecting seizure activity was comparable between fm-EEG (100%) and rm-EEG (98%) (p = 0.17). Furthermore, the specificity of rm-EEG for seizures and RPP (neurologists: 100%, residents: 90%, students: 86%) was significantly greater than that of fm-EEG (neurologists: 93%, p = 0.03; residents: 80%, p = 0.01; students: 69%, p < 0.001). ConclusionsThe reduction of the number of EEG channels from 18 to 8 does not compromise neurologists’ sensitivity for detecting seizures that are often a core reason for performing urgent EEG. It may also increase their specificity for detecting rhythmic and periodic patterns, and thereby providing important diagnostic information to guide patient’s management. SignificanceOur study is the first to document the utility of a reduced channel EEG above the hairline compared to full montage EEG in aiding medical staff with varying degrees of EEG training to detect generalized or hemispheric seizures.

The effect of reducing EEG electrode number on the visual interpretation of the human expert for neonatal seizure detection

ObjectivesTo measure changes in the visual interpretation of the EEG by the human expert for neonatal seizure detection when reducing the number of recording electrodes. MethodsEEGs were recorded from 45 infants admitted to the neonatal intensive care unit (NICU). Three experts annotated seizures in EEG montages derived from 19, 8 and 4 electrodes. Differences between annotations were assessed by comparing intra-montage with inter-montage agreement (K). ResultsThree experts annotated 4464 seizures across all infants and montages. The inter-expert agreement was not significantly altered by the number of electrodes in the montage (p = 0.685, n = 43). Reducing the number of EEG electrodes altered the seizure annotation for all experts. Agreement between the 19-electrode montage (K19,19 = 0.832) was significantly higher than the agreement between 19 and 8-electrode montages (dK = 0.114; p < 0.001, n = 42) or 19 and 4-electrode montages (dK = 0.113, p < 0.001, n = 43). Seizure burden and number were significantly underestimated by the 4 and 8-electrode montage (p < 0.001). No significant difference in agreement was found between 8 and 4-electrode montages (dK = 0.002; p = 0.07, n = 42). ConclusionsReducing the number of EEG electrodes from 19 electrodes resulted in slight but significant changes in seizure detection. SignificanceFour-electrode montages for routine EEG monitoring are comparable to eight electrodes for seizure detection in the NICU.

Use of amplitude-integrated electroencephalograpy in monitoring critically ill neurological patients

Background: Use of continuous electroencephalography (cEEG) is recommended for monitoring various kinds of critically-ill neurological patients. However, because of its complexity and a lack of resources, high-quality cEEG monitoring is underutilized. Amplitude-integrated EEG (aEEG), generated from simplified EEG montage with a limited number of raw EEG curves, is notably easy to read. It has been used in neonatal hypoxic ischemic encephalopathy and adult post cardiac arrest syndrome (PCAS) for prognostication.

ANALYSIS OF APPLIED REFERENCE LEADS INFLUENCE ON AN EEG SPECTRUM

The article presents the analysis of various kinds of montage applied in the analysis of electroencephalographic data. The present study covers analysis of data obtained as a result of EEG examination of several persons with the age of 23–24 years. Every person has undergone an examination with appliance of 21 electrodes in accordance with classic EEG record method applying the 10–20 system. The examined persons were asked to perform the following activities: sitting steadily with opened eyes, sitting steadily with closed eyes as well as typical cognitive activity i.e. silent reading of given text. Every fragment has been subjected to initial data analysis (filtering, artifact correction) and used for spectral analysis afterwards. The whole analysis has been realized on the basis of four EEG montage examples (two bipolar and two monopolar). For each of them comparative analysis concerning the following points has been carried out: EEG spectra as well as other measures, such as activity maps, diffraction histograms for separate waves and spectrum charts for the selected electrodes.

Reduced electrode arrays for the automated detection of rhythmic and periodic patterns in the intensive care unit: Frequently tried, frequently failed?

To investigate the effect of systematic electrode reduction from a common 10-20 EEG system on pattern detection sensitivity (SEN). Two reviewers rated 17130 one-minute segments of 83 prospectively recorded cEEGs according to the ACNS standardized critical care EEG terminology (CCET), including burst suppression patterns (BS) and unequivocal electrographic seizures. Consensus annotations between reviewers were used as a gold standard to determine pattern detection SEN and specificity (SPE) of a computational algorithm (baseline, 19 electrodes). Electrodes were than reduced one by one in four different variations. SENs and SPEs were calculated to determine the most beneficial assembly with respect to the number and location of electrodes. High automated baseline SENs (84.99-93.39%) and SPEs (90.05-95.6%) were achieved for all patterns. Best overall results in detecting BS and CCET patterns were found using the "hairline+vertex" montage. While the "forehead+behind ear" montage showed an advantage in detecting ictal patterns, reaching a 15% drop of SEN with 10 electrodes, all montages could detect BS sufficiently if at least nine electrodes were available. For the first time an automated approach was used to systematically evaluate the effect of electrode reduction on pattern detection SEN in cEEG. Prediction of the expected detection SEN of specific EEG patterns with reduced EEG montages in ICU patients.

American Clinical Neurophysiology Society Guideline 5: Minimum Technical Standards for Pediatric Electroencephalography.

This revision to the EEG Guidelines is an update incorporating the current electroencephalography technology and practice. It was previously published as Guideline 2. Similar to the prior guideline, it delineates the aspects of Guideline 1 that should be modified for neonates and young children. Recording conditions for photic stimulation and hyperventilation are revised to enhance the provocation of epileptiform discharges. Revisions recognize the difficulties involved in performing an EEG under sedation in young children. Recommended neonatal EEG montages are displayed for the reduced set of electrodes only since the montages in Guideline 3 should be used for a 21-electrode 10-20 system array. Neonatal documentation is updated to use current American Academy of Pediatrics term "postmenstrual age" rather than "conceptional age." Finally, because therapeutic hypothermia alters the prognostic value of neonatal EEG, the necessity of documenting the patient's temperature at the time of recording is emphasized.

Identifying montages that best detect the electroencephalogram power spectrum alteration during freezing of gait in Parkinson's disease patients.

Our research team has previously used four Electroencephalography (EEG) leads to successfully detect and predict Freezing of Gait (FOG) in Parkinson's disease (PD). However, it remained to be determined whether these four sensor locations that were arbitrarily chosen based on their role in motor control are indeed the most optimal for FOG detection. The aim of this study was therefore to determine the most optimal location and combination of sensors to detect FOG amongst a 32-channel EEG montage using our EEG classification system. EEG measures, including power spectral density, centroid frequency and power spectral entropy, were extracted from 7 patients with PD and FOG during a series of Timed up and Go tasks. By applying a feed-forward neural networks to classify EEG data, the obtained results showed that even a small number of electrodes suffice to construct a FOG detector with expected performance, which is comparable to the use of a full 32 channels montage. This finding therefore progresses the realization of a FOG detection system that can be effectively implemented on a daily basis for FOG prevention, improving the quality of life for many patients with PD.

Minimal EEG montage with high yield for the detection of status epilepticus in the setting of postanoxic brain damage.

For the diagnosis of electrographic seizures or status epilepticus, we reduced the number of EEG-electrodes to make urgent EEG monitoring more feasible. Unlike the current existing research, with mixed results, we studied a specific population with postanoxic brain damage, expecting a higher yield of detection of ictal EEG patterns. In a population treated with therapeutic hypothermia post-cardiac arrest, the initial EEGs were reformatted in a longitudinal, a hairline and an 8-lead montage, and independently reviewed by two investigators. The EEGs were categorized into three categories: one without ictal EEG activity, one with interictal activity and one with probable electrographic seizure(s). Generalized ictal EEG activity was the most frequently observed EEG pattern. The average sensitivity for the detection of probable electrographic seizure(s) was 100% for the 8-lead montage and 92% in the hairline montage. In comparison to the routine longitudinal montage, the 8-lead montage proved to be reliable for the detection of electrographic seizure activity in a postanoxic population even with limited training in EEG interpretation. The hairline montage did not suffice with regard to the differential diagnosis of triphasic waves associated with metabolic encephalopathy and generalized nonconvulsive status epilepticus, but nonetheless detected the vast majority of probable electrographic seizure(s). Our results support the use of EEG monitoring with fewer electrodes for the detection of ictal EEG activity in the postanoxic population.