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Abstract Objective This systematic review aims to describe the involvement of persons with epilepsy (PWE), healthcare professionals (HP) and caregivers (CG) in the design and development of medical devices is epilepsy. Methods A systematic review was conducted, adhering to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. Eligibility criteria included peer‐reviewed research focusing on medical devices for epilepsy management, involving users (PWE, CG, and HP) during the MDD process. Searches were performed on PubMed, Web of Science, and Scopus, and a total of 55 relevant articles were identified and reviewed. Results From 1999 to 2023, there was a gradual increase in the number of publications related to user involvement in epilepsy medical device development (MDD), highlighting the growing interest in this field. The medical devices involved in these studies encompassed a range of seizure detection tools, healthcare information systems, vagus nerve stimulation (VNS) and electroencephalogram (EEG) technologies reflecting the emphasis on seizure detection, prediction, and prevention. PWE and CG were the primary users involved, underscoring the importance of their perspectives. Surveys, usability testing, interviews, and focus groups were the methods used for capturing user perspectives. User involvement occurs in four out of the five stages of MDD, with production being the exception. Significance User involvement in the MDD process for epilepsy management is an emerging area of interest holding a significant promise for improving device quality and patient outcomes. This review highlights the need for broader and more effective user involvement, as it currently lags in the development of commercially available medical devices for epilepsy management. Future research should explore the benefits and barriers of user involvement to enhance medical device technologies for epilepsy. Plain Language Summary This review covers studies that have involved users in the development process of medical devices for epilepsy. The studies reported here have focused on getting input from people with epilepsy, their caregivers, and healthcare providers. These devices include tools for detecting seizures, stimulating nerves, and tracking brain activity. Most user feedback was gathered through surveys, usability tests, interviews, and focus groups. Users were involved in nearly every stage of device development except production. The review highlights that involving users can improve device quality and patient outcomes, but more effective involvement is needed in commercial device development. Future research should focus on the benefits and challenges of user involvement.

Introduction Epilepsy surgery is the only curative treatment for patients with drug-resistant focal epilepsy. Stereoelectroencephalography (SEEG) is the gold standard to delineate the seizure-onset zone (SOZ). However, up to 40% of patients are subsequently not operated as no focal non-eloquent SOZ can be identified. The 5-SENSE Score is a 5-point score to predict whether a focal SOZ is likely to be identified by SEEG. This study aims to validate the 5-SENSE Score, improve score performance by incorporating auxiliary diagnostic methods and evaluate its concordance with expert decisions.Methods and analysis Non-interventional, observational, multicentre, prospective study including 200 patients with drug-resistant epilepsy aged ≥15 years undergoing SEEG for identification of a focal SOZ and 200 controls at 22 epilepsy surgery centres worldwide. The primary objective is to assess the diagnostic accuracy and generalisability of the 5-SENSE in predicting focality in SEEG in a prospective cohort. Secondary objectives are to optimise score performance by incorporating auxiliary diagnostic methods and to analyse concordance of the 5-SENSE Score with the expert decisions made in the multidisciplinary team discussion.Ethics and dissemination Prospective multicentre validation of the 5-SENSE score may lead to its implementation into clinical practice to assist clinicians in the difficult decision of whether to proceed with implantation. This study will be conducted in accordance with the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (2014). We plan to publish the study results in a peer-reviewed full-length original article and present its findings at scientific conferences.Trial registration number NCT06138808.

IntroductionAutomated seizure detection promises to aid in the prevention of SUDEP and improve the quality of care by assisting in epilepsy diagnosis and treatment adjustment.MethodsIn this phase 2 exploratory study, the performance of a contactless, marker-free, video-based motor seizure detection system is assessed, considering video recordings of patients (age 0–80 years), in terms of sensitivity, specificity, and Receiver Operating Characteristic (ROC) curves, with respect to video-electroencephalographic monitoring (VEM) as the medical gold standard. Detection performances of five categories of motor epileptic seizures (tonic–clonic, hyperkinetic, tonic, unclassified motor, automatisms) and psychogenic non-epileptic seizures (PNES) with a motor behavioral component lasting for >10 s were assessed independently at different detection thresholds (rather than as a categorical classification problem). A total of 230 patients were recruited in the study, of which 334 in-scope (>10 s) motor seizures (out of 1,114 total seizures) were identified by VEM reported from 81 patients. We analyzed both daytime and nocturnal recordings. The control threshold was evaluated at a range of values to compare the sensitivity (n = 81 subjects with seizures) and false detection rate (FDR) (n = all 230 subjects).ResultsAt optimal thresholds, the performance of seizure groups in terms of sensitivity (CI) and FDR/h (CI): tonic–clonic- 95.2% (82.4, 100%); 0.09 (0.077, 0.103), hyperkinetic- 92.9% (68.5, 98.7%); 0.64 (0.59, 0.69), tonic- 78.3% (64.4, 87.7%); 5.87 (5.51, 6.23), automatism- 86.7% (73.5, 97.7%); 3.34 (3.12, 3.58), unclassified motor seizures- 78% (65.4, 90.4%); 4.81 (4.50, 5.14), and PNES- 97.7% (97.7, 100%); 1.73 (1.61, 1.86). A generic threshold recommended for all motor seizures under study asserted 88% sensitivity and 6.48 FDR/h.DiscussionThese results indicate an achievable performance for major motor seizure detection that is clinically applicable for use as a seizure screening solution in diagnostic workflows.

PurposeThe purpose of this study is to investigate the impact of Bergen Epileptiform Morphology Score (BEMS) and interictal epileptiform discharge (IED) candidate count in EEG classification.MethodsWe included 400 consecutive patients from a clinical SCORE EEG database during 2013–2017 who had focal sharp discharges in their EEG, but no previous diagnosis of epilepsy. Three blinded EEG readers marked all IED candidates. BEMS and IED candidate counts were combined to classify EEGs as epileptiform or non-epileptiform. Diagnostic performance was assessed and then validated in an external dataset.ResultsInterictal epileptiform discharge (IED) candidate count and BEMS were moderately correlated. The optimal criteria to classify an EEG as epileptiform were either one spike at BEMS > = 58, two at > = 47, or seven at > = 36. These criteria had almost perfect inter-rater reliability (Gwet’s AC1 0.96), reasonable sensitivity of 56–64%, and high specificity of 98–99%. The sensitivity was 27–37%, and the specificity was 93–97% for a follow-up diagnosis of epilepsy. In the external dataset, the sensitivity for an epileptiform EEG was 60–70%, and the specificity was 90–93%.ConclusionQuantified EEG spike morphology (BEMS) and IED candidate count can be combined to classify an EEG as epileptiform with high reliability but with lower sensitivity than regular visual EEG review.

Objective: To determine the prevalence and characteristics of normal variants in EEG recordings in a large cohort, and provide readers with typical examples of all normal variants for educational purposes. Methods: Using the SCORE EEG system (Standardized Computer-Based Organized Reporting of EEG), we prospectively extracted EEG features in consecutive patients. In this dataset, we analyzed 3050 recordings from 2319 patients (mean age 38.5 years; range: 1–89 years). Results: The distribution of the normal variants was as follows: sharp transients 19.21% (including wicket spikes), rhythmic temporal theta of drowsiness 6.03%, temporal slowing of the old 2.89%, slow fused transients 2.59%, 14-and 6-Hz bursts 1.83%, breach rhythm 1.25%, small sharp spikes 1.05%, 6-Hz spike and slow wave 0.69% and SREDA 0.03%. Conclusions: The most prevalent normal variants are the sharp transients, which must not be over-read as epileptiform discharges. Significance: EEG readers must be familiar with the normal variants to avoid misdiagnosis and misclassification of patients referred to clinical EEG recordings.

Objective: To detail current European EEG education practices and compare European and U.S. EEG teaching systems. Methods: A 19-question online survey focused on EEG clinical practices and residency training was emailed to all 47 European Academy of Neurology Societies. Results: Thirty-two (68 %) out of the 47 Societies completed the survey. In half of countries, general neurologists are either among the providers or the only providers who typically read EEGs. The number of weeks devoted to EEG learning required to graduate ranged from none to 26, and it was expected to be continuous in one country. In most countries (n = 17/32), trainees read >40 EEGs per EEG rotation, and the most commonly interpreted studies are routine and prolonged routine EEGs. Rotations involve clinic/outpatient (90 %), epilepsy monitoring unit/inpatient (60 %), or both (50 %). Roughly half of countries do not use objective measures to assess EEG competency. The most reported educational methods are teaching during EEG rotation and yearly didactics, and the most reported education barriers are insufficient didactics and insufficient EEG exposure. Conclusions: We suggest neurology educators in Europe, especially in those countries where EEGs are read by general neurologists, consider ensuring that residency EEG learning is mandatory and establishing objective measures in teaching and evaluating competency. Significance: Similar to the U.S., neurology resident EEG training in Europe is highly variable.

Objective: To assess whether implementing the freeware version of the SCORE EEG system (Standardized Computer-based Organized Reporting of EEG) leads to improvement in the quality of clinical EEG reading, and whether EEG reports in SCORE EEG are understood and accepted by the referring physicians. Methods: We generated EEG reports in the conventional, free-text style and then using SCORE EEG, in consecutive patients referred to routine EEG. We used the Georgian translation in the SCORE EEG Free Edition. We pre-defined quality indicators consisting of a list of 24 key features that need to be addressed in EEG reports. We compared these quality indicators in free-text reports with SCORE EEG. In addition, EEG reports in SCORE EEG format were assessed by ten referring physicians, who evaluated their usability on a 7-point Likert scale. Results: We included and evaluated EEG reports from 157 patients (80 female; age: 1–75 years; median: 28 years). Fourteen features were reported exclusively in SCORE EEG, four were reported significantly more often in SCORE EEG than in free-text format, and six features were reported equally often in SCORE EEG and in free-text format. Usability aspects of SCORE EEG were highly rated by the referring physicians (median 6–7 on the 7-point Likert scale). Conclusions: The structured system of EEG reporting in SCORE EEG helped the experts reading clinical EEG to cover the important aspects and increase the quality of clinical EEG reports. Significance: Implementing the freeware version of SCORE EEG in underprivileged areas will help improving management of patients with epilepsy.

Objective: To determine the feasibility and accuracy of a handheld optical scanner to measure the three-dimensional (3D) EEG electrode coordinates in a high-density array of 256 electrodes. Methods: We compared the optical scanning with a previously validated method, based on photogrammetry. Electrode coordinates were co-registered with the MRI of the patients, and mean distance error relative to the three-dimensional MRI reconstruction was determined for each patient. We included 60 patients: 30 were measured using the photogrammetry method, and 30 age and gender matched patients were measured with the optical scanner. Results: Using the optical scanner, the mean distance error was 1.78 mm (95% confidence interval: 1.59–1.98 mm) which was significantly lower (p

Objective: The goal of this study was to investigate the diagnostic utility of electric source imaging (ESI) in the presurgical evaluation of children with focal cortical dysplasia (FCD) and to compare it with other imaging techniques. Methods: Twenty patients with epilepsy onset before 18 years, surgically treated focal epilepsy with a minimal follow-up of 2 years, and histologically proven FCD were retrospectively selected. All patients underwent MRI, positron emission tomography (PET), and 16 patients also had ictal single-photon emission computed tomography (iSPECT). ESI, using EEG with 64 electrodes or more (HD-ESI), was performed in all 20 patients. We determined sensitivity, specificity and accuracy of ESI, and compared its yield to that of other imaging techniques. Results: Twelve patients were seizure-free post-operatively (60%). Among all patients, highest localization accuracy (80%) was obtained with ESI, followed by PET and iSPECT (75%). When results from ESI and SPECT were concordant 100% of patients achieved Engel I outcome. If ESI and PET showed concordant localization, 90% of patients achieved postoperative seizure freedom. Conclusions: Our findings demonstrate that HD-ESI allows accurate localization of the epileptogenic zone in patients with FCD. Significance: In combination with other imaging modalities, ESI helps with planning a more accurate surgery and therefore, the chances of postoperative seizure control are higher. Since it is based on EEG recordings, it does not require sedation, which is particularly interesting in pediatric patients. ESI represents an important imaging tool in focal epilepsies due to cortical dysplasia, which might be difficult to detect on standard imaging.

Abstract Background Unsupervised nocturnal tonic‐clonic seizures (TCSs) may lead to sudden unexpected death in epilepsy (SUDEP). Major motor seizures (TCSs and hypermotor seizures) may lead to injuries. Our goal was to develop and validate an automated audio‐video system for the real‐time detection of major nocturnal motor seizures. Methods In this Phase‐3 clinical validation study, we assessed the performance of automated detection of nocturnal motor seizures using audio‐video streaming, computer vision and an artificial intelligence‐based algorithm (Nelli). The detection threshold was predefined, the validation dataset was independent from the training dataset, patients were prospectively recruited, and the analysis was performed in real time. The gold standard was based on expert evaluation of long‐term video electroencephalography (EEG). The primary outcome was the detection of nocturnal major motor seizures (TCSs and hypermotor seizures). The secondary outcome was the detection of other (minor) nocturnal motor seizures. Results We recruited 191 participants aged 1–72 years (median: 20 years), and we monitored them for 4183 h during the night. Device deficiency was present 10.5% of the time. Fifty‐one patients had nocturnal motor seizures during the recording. The sensitivity for the major motor seizures was 93.7% (95% confidence interval: 69.8%–99.8%). The system detected all 11 TCS and four out of five (80%) hypermotor seizures. For the minor motor seizure types, the sensitivity was low (8.3%). The false detection rate was 0.16 per h. Conclusion The Nelli system detects nocturnal major motor seizures with a high sensitivity and is suitable for implementation in institutions (hospitals, residential care facilities), where rapid interventions triggered by alarms can potentially reduce the risk of SUDEP and injuries.

Objectives: Dorsal sural nerve conduction studies (NCS) may increase the sensitivity for the diagnosis of polyneuropathy, but clinical use is limited by a lack of reliable normative reference values in all age-groups. The aim of our study was to develop reference values for the dorsal sural nerve, based on a large multicenter cohort of healthy subjects. Methods: Bilateral antidromic NCS were performed using standard surface electrodes in 229 healthy subjects (aged 21–80 years; median: 54 years). We assessed the normality of data distribution for amplitudes and conduction velocity (CV) and for their logarithmic (ln) transformation. The effects of age and height were determined using linear regression analysis. Results: Sensory potentials were present in all subjects. Logarithmically transformed data were normally distributed. Age2 and height were most significantly associated with amplitude, and age and height with CV, respectively. There was no significant side-difference. Mean amplitudes (right and left) were 4.8 and 4.9 μV and mean CV 46.7 and 46.9 m/s. Reference limits were e (3.712515 – 0.0000956 * age2 – 0.0115883 * height ± 1.96 * 0.51137) for amplitude and e (4.354374 – 0.0021081 * age – 0.0023354 * height ± 1.96 * 0.11161) for CV. Conclusions: Dorsal sural nerve NCS are robust and have well defined normative limits. Significance: The findings provide a basis for more sensitive NCS in clinical practice and future studies of the diagnostic accuracy of NCS in polyneuropathy.

Objective: To investigate the EEG spectral changes induced during hemodialysis in patients with chronic kidney disease (CKD), and to identify the risk factors associated with changes in the Central Nervous System (CNS) during hemodialysis. Paradoxical neurological deterioration at the end of hemodialysis sessions, known as dialysis disequilibrium syndrome (DDS) has been described, but previous studies on EEG spectral changes during hemodialysis were controversial. Methods: We performed quantitative EEG spectral analysis in 56 consecutive patients who underwent hemodialysis. We compared EEG at the start and at the end of the hemodialysis, and we correlated the spectral changes with the biochemical and clinical characteristics of the patients, using multivariate analysis. Results: At the end of hemodialysis sessions, we found a significant increase in total EEG power, relative power in delta frequency band and the ratio of delta-theta/alpha–beta power. EEG spectral changes were associated with younger age, recent start of hemodialysis therapy, level of uremia and lower level of glycaemia. Conclusions: Quantitative EEG spectral analysis showed that hemodialysis induced slowing of the EEG background activity. These changes were associated with risk factors of DDS. Significance: EEG spectral changes are potential biomarkers for monitoring CNS function during hemodialysis.

Electric source imaging (ESI) estimates the cortical generator of the electroencephalography (EEG) signals recorded with scalp electrodes. ESI has gained increasing interest for the presurgical evaluation of patients with drug-resistant focal epilepsy. In spite of a standardised analysis pipeline, several aspects tailored to the individual patient involve subjective decisions of the expert performing the analysis, such as the selection of the analysed signals (interictal epileptiform discharges and seizures, identification of the onset epoch and time-point of the analysis). Our goal was to investigate the inter-analyser agreement of ESI in presurgical evaluations of epilepsy, using the same software and analysis pipeline. Six experts, of whom five had no previous experience in ESI, independently performed interictal and ictal ESI of 25 consecutive patients (17 temporal, 8 extratemporal) who underwent presurgical evaluation. The overall agreement among experts for the ESI methods was substantial (AC1 = 0.65; 95% CI: 0.59–0.71), and there was no significant difference between the methods. Our results suggest that using a standardised analysis pipeline, newly trained experts reach similar ESI solutions, calling for more standardisation in this emerging clinical application in neuroimaging.

Up to 11% of patients with mesial temporal lobe epilepsy experience somatosensory auras, although these structures do not have any somatosensory physiological representation. We present the case of a patient with left mesial temporal lobe epilepsy who had somatosensory auras on the right side of the body. Stereo-EEG recording demonstrated seizure onset in the left mesial temporal structures, with propagation to the sensory cortices, when the patient experienced the somatosensory aura. Direct electrical stimulation of both the left amygdala and the hippocampus elicited the patient's habitual, somatosensory aura, with afterdischarges propagating to sensory cortices. These unusual responses to cortical stimulation suggest that in patients with epilepsy, aberrant neural networks are established, which have an essential role in ictogenesis.

Background: Electric and magnetic source imaging methods (ESI, MSI) estimate the location in the brain of the sources generating the interictal epileptiform discharges (II-ESI, II-MSI) and the ictal activity (IC-ESI, IC-MSI). These methods provide potentially valuable clinical information in the presurgical evaluation of patients with drug-resistant focal epilepsy, evaluated for surgical therapy. In spite of the significant technical advances in this field, and the numerous papers published on clinical validation of these methods, ESI and MSI are still underutilized in most epilepsy centers performing a presurgical evaluation. Our goal was to review and summarize the published evidence on the diagnostic accuracy of interictal and ictal ESI and MSI in epilepsy surgery.Methods: We searched the literature for papers on ESI and MSI that specified the diagnostic reference standard as the site of resection and the postoperative outcome (seizure-freedom). We extracted data from the selected studies, to calculate the diagnostic accuracy measures.Results: Our search resulted in 797 studies; 48 studies fulfilled the selection criteria (25 ESI and 23 MSI studies), providing data from 1,152 operated patients (515 for II-ESI, 440 for II-MSI, 159 for IC-ESI, and 38 for IC-MSI). The sensitivity of source imaging methods was between 74 and 90% (highest for IC-ESI). The specificity of the source imaging methods was between 20 and 54% (highest for II-MSI). The overall accuracy was between 50 and 75% (highest for IC-ESI). Diagnostic Odds Ratio was between 0.8 (IC-MSI) and 4.02–7.9 (II-ESI < II-MSI < IC-ESI).Conclusions: Our systematic review and meta-analysis provides evidence for the accuracy of source imaging in presurgical evaluation of patients with drug-resistant focal epilepsy. These methods have high sensitivity (up to 90%) and diagnostic odds ratio (up to 7.9), but the specificity is lower (up to 54%). ESI and MSI should be included in the multimodal presurgical evaluation.

Background: In contrast to many neuroimaging modalities, clinical interpretation of EEG does not take advantage of post-processing and digital signal analysis. In most centers, EEG is still interpreted at sensor level, exactly as half a century ago. A major task in clinical EEG interpretation is the identification of interictal epileptiform discharges (IEDs). However, due to the overlap of background activity, IEDs can be hard to detect in the scalp EEG. Since traditional montages, like bipolar and average reference, are linear transformations of the recorded channels, the question is whether we can provide linear transformations of the digital EEG to take it back into the brain, at least on a macroscopic level. The goal is to improve visibility of epileptiform activities and to separate out most of the overlap.Methods: Multiple discrete sources provide a stable linear inverse to transform the EEG into source space with little cross-talk between source regions. The model can be based on a few dipoles or regional sources, adapted to the individual EEG and MRI data, or on selected standard sources evenly distributed throughout the brain, e.g. below the 25 EEG standard electrodes.Results: Auditory and somatosensory evoked potentials serve as teaching examples to show how various source spaces can reveal the underlying source components including their loss or alteration due to lesions. Source spaces were able to reveal the propagation of source activities in frontal IEDs and the sequential activation of the major nodes of the underlying epileptic network in myoclonic epilepsy. The power of multiple discrete sources in separating the activities of different brain regions was also evident in the ongoing EEG of cases with frontal cortical dysplasia and bitemporal lobe epilepsy. The new source space 25 made IEDs more clearly visible over the EEG background signals. The more focal nature of source vs. scalp space was quantitatively confirmed using a new measurement of focality.Conclusion: Multiple discrete sources have the power to transform the EEG back into the brain by defining new EEG traces in source space. Using standard source space 25, these can provide for improved clinical interpretation of EEG.

Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality.The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18-70 years) and 13 patients with epilepsy (8 males, age range 21-67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients).RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG recorded during high-speed fMRI and during conventional EPI (p = 0.78). Residual ballistocardiographic artifacts resulted in 58% of EEG data being rated as poor quality.This study demonstrates that high-density EEG can be safely implemented in conjunction with high-speed fMRI and that high-speed fMRI does not adversely affect EEG data quality. However, the deterioration of the EEG quality due to residual ballistocardiographic artifacts remains a significant constraint for routine clinical applications of concurrent EEG-fMRI.