An Uncommon Culprit: Dural Arteriovenous Fistula Presenting as Otodynia and Dizziness.

Dural arteriovenous fistulas (DAVFs) are rare vascular abnormalities that can present with diverse neurological symptoms. We report a case of a woman in her early 60s who presented with pain in the left ear and dizziness. Neurological evaluation and imaging studies revealed a DAVF in the left cerebellopontine angle.

Artificial intelligence-enhanced epileptic seizure detection by wearables.

Objective: Wrist- or ankle-worn devices are less intrusive than the widely used electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom-developed deep-learning seizure detection models, we demonstrate the detection of a broad range of seizure types by wearable signals.

Methods: Patients admitted to the epilepsy monitoring unit were enrolled and asked to wear wearable sensors on either wrists or ankles.

Seizure-related differences in biosignal 24-h modulation patterns.

A seizure likelihood biomarker could improve seizure monitoring and facilitate adjustment of treatments based on seizure risk. Here, we tested differences in patient-specific 24-h-modulation patterns of electrodermal activity (EDA), peripheral body temperature (TEMP), and heart rate (HR) between patients with and without seizures. We enrolled patients who underwent continuous video-EEG monitoring at Boston Children's Hospital to wear a biosensor.

Generalized tonic-clonic seizures are accompanied by changes of interrelations within the autonomic nervous system.

Purpose: A seizure is a strong central stimulus that affects multiple subsystems of the autonomic nervous system (ANS), and results in different interactions across ANS modalities. Here, we aimed to evaluate whether multimodal peripheral ANS measures demonstrate interactions before and after seizures as compared to controls to provide the basis for seizure detection and forecasting based on peripheral ANS signals.

Methods: Continuous electrodermal activity (EDA), heart rate (HR), peripheral body temperature (TEMP), and respiratory rate (RR) calculated based on blood volume pulse were acquired by a wireless multi-sensor device.

Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit.

Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (EDA) has been shown effective to detect primarily and secondarily generalized tonic-clonic seizures, here termed as convulsive seizures (CS). A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm. Here we present its performance on pediatric and adult patients in epilepsy monitoring units (EMUs).

Association between semiologic, autonomic, and electrographic seizure characteristics in children with generalized tonic-clonic seizures.

Introduction: Generalized tonic-clonic seizures (GTCS) are associated with elevated electrodermal activity (EDA) and postictal generalized electroencephalographic suppression (PGES), markers that may indicate sudden unexpected death in epilepsy (SUDEP) risk. This study investigated the association of GTCS semiology, EDA, and PGES in children with epilepsy.

Methods: Patients admitted to the Boston Children's Hospital long-term video-EEG monitoring unit wore a sensor that records EDA.

Measuring the effects of sleep on epileptogenicity with multifrequency entropy.

Objective: We demonstrate that multifrequency entropy gives insight into the relationship between epileptogenicity and sleep, and forms the basis for an improved measure of medical assessment of sleep impairment in epilepsy patients.

Methods: Multifrequency entropy was computed from electroencephalography measurements taken from 31 children with Benign Epilepsy with Centrotemporal Spikes and 31 non-epileptic controls while awake and during sleep. Values were compared in the epileptic zone and away from the epileptic zone in various sleep stages.

Seizure detection using wearable sensors and machine learning: Setting a benchmark.

Objective: Tracking seizures is crucial for epilepsy monitoring and treatment evaluation. Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may miss seizures. Wearable devices may be better tolerated and more suitable for long-term ambulatory monitoring.

Twenty-four-hour patterns in electrodermal activity recordings of patients with and without epileptic seizures.

Objective: Daytime and nighttime patterns affect the dynamic modulation of brain and body functions and influence the autonomic nervous system response to seizures. Therefore, we aimed to evaluate 24-hour patterns of electrodermal activity (EDA) in patients with and without seizures.

Methods: We included pediatric patients with (a) seizures (SZ), including focal impaired awareness seizures (FIAS) or generalized tonic-clonic seizures (GTCS), (b) no seizures and normal electroencephalography (NEEG), or (c) no seizures but epileptiform activity in the EEG (EA) during vEEG monitoring.

Video-Based Detection of Generalized Tonic-Clonic Seizures Using Deep Learning.

Timely detection of seizures is crucial to implement optimal interventions, and may help reduce the risk of sudden unexpected death in epilepsy (SUDEP) in patients with generalized tonic-clonic seizures (GTCSs). While video-based automated seizure detection systems may be able to provide seizure alarms in both in-hospital and at-home settings, earlier studies have primarily employed hand-designed features for such a task. In contrast, deep learning-based approaches do not rely on prior feature selection and have demonstrated outstanding performance in many data classification tasks.

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.

Objective: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessment is in principle possible, these early approaches relied largely on complex, often invasive setups including intracranial electrocorticography, implanted devices, and multichannel electroencephalography, and required patient-specific adaptation or learning to perform optimally, all of which limit translation to broad clinical application. To facilitate broader adaptation of seizure forecasting in clinical practice, noninvasive, easily applicable techniques that reliably assess seizure risk without much prior tuning are crucial.

Photoplethysmography: A measure for the function of the autonomic nervous system in focal impaired awareness seizures.

Objectives: Photoplethysmography (PPG) reflects variations of blood perfusion in tissues, which may signify seizure-related autonomic changes. The aim of this study is to assess the variability of PPG signals and their value in detecting peri-ictal changes in patients with focal impaired awareness seizures (FIASs).

Methods: PPG data were recorded using a wearable sensor placed on the wrist or ankle of children with epilepsy admitted for long-term video-electroencephalographic monitoring.

Autonomic nervous system changes detected with peripheral sensors in the setting of epileptic seizures.

A better understanding of the early detection of seizures is highly desirable as identification of an impending seizure may afford improved treatments, such as antiepileptic drug chronotherapy, or timely warning to patients. While epileptic seizures are known to often manifest also with autonomic nervous system (ANS) changes, it is not clear whether ANS markers, if recorded from a wearable device, are also informative about an impending seizure with statistically significant sensitivity and specificity. Using statistical testing with seizure surrogate data and a unique dataset of continuously recorded multi-day wristband data including electrodermal activity (EDA), temperature (TEMP) and heart rate (HR) from 66 people with epilepsy (9.

Photoplethysmographic evaluation of generalized tonic-clonic seizures.

Objective: Photoplethysmography (PPG) is an optical technique measuring variations of blood perfusion in peripheral tissues. We evaluated alterations in PPG signals in relationship to the occurrence of generalized tonic-clonic seizures (GTCSs) in patients with epilepsy to evaluate the feasibility of seizure detection.

Methods: During electroencephalographic (EEG) long-term monitoring, patients wore portable wristband sensor(s) on their wrists or ankles recording PPG signals.

Nonlinear Analysis of Visually Normal EEGs to Differentiate Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS).

Childhood epilepsy with centrotemporal spikes, previously known as Benign Epilepsy with Centro-temporal Spikes (BECTS) or Rolandic Epilepsy, is one of the most common forms of focal childhood epilepsy. Despite its prevalence, BECTS is often misdiagnosed or missed entirely. This is in part due to the nocturnal and brief nature of the seizures, making it difficult to identify during a routine electroencephalogram (EEG).

Electrocardiographic changes associated with epilepsy beyond heart rate and their utilization in future seizure detection and forecasting methods.

The ability to assess seizure risk may help provide timely warnings and more personalized treatment plans for people with epilepsy (PWE). ECG changes are commonly observed in epilepsy which make ECG a promising candidate to monitor seizure risk. Most ECG research in this domain has focused on heart rate-related changes.

Peripheral multimodal monitoring of ANS changes related to epilepsy.

The goal of this study was to evaluate and summarize the current literature on multimodal changes of the autonomic nervous system (ANS) in people with epilepsy (PWE). We included studies reporting ANS measures of at least two modalities and with a minimum of one group of people with epilepsy. We screened two hundred eighty-three abstracts and sixty-six full texts, of which twenty-two met our inclusion criteria.

Outcome of ambulatory video-EEG monitoring in a ˜10,000 patient nationwide cohort.

Purpose: We evaluate outcome of in-home diagnostic ambulatory video-EEG monitoring (AVEM) performed on a nationwide cohort of patients over one calendar year, and we compare our findings with outcomes of inpatient adult and pediatric VEM performed during the same year at two academic epilepsy centers.

Methods: This is a retrospective cohort study. We obtained AVEM outcome data from an independent ambulatory-EEG testing facility.