Noninvasive detection of focal seizures in ambulatory patients

Abstract

Reliably detecting focal seizures without secondary generalization during daily life activities, chronically, using convenient portable or wearable devices, would offer patients with active epilepsy a number of potential benefits, such as providing more reliable seizure count to optimize treatment and seizure forecasting, and triggering alarms to promote safeguarding interventions. However, no generic solution is currently available to reach these objectives. A number of biosignals are sensitive to specific forms of focal seizures, in particular heart rate and its variability for seizures affecting the neurovegetative system, and accelerometry for those responsible for prominent motor activity. However, most studies demonstrate high rates of false detection or poor sensitivity, with only a minority of patients benefiting from acceptable levels of accuracy. To tackle this challenging issue, several lines of technological progress are envisioned, including multimodal biosensing with cross‐modal analytics, a combination of embedded and distributed self‐aware machine learning, and ultra–low‐power design to enable appropriate autonomy of such sophisticated portable solutions.

Wearables bei Epilepsien

“…Solche autonomen Symptome können aber gerade bei Anfällen mit fehlender oder geringer motorischer Beteiligung -also fokale bewusst erlebte Anfälle mit verschiedenen Sensationen (Auren) oder fokale, nicht bewusst erlebte Anfälle mit Verharren und Schluckautomatismen -besonders wichtige Surrogatmarker epileptischer Aktivität sein (▶abb. 2) [30,31]. So steigt bspw.…”

“…Die automatisierte Erfassung fokaler Anfälle ohne ausgeprägte motorische Symptome ist die größte Herausforderung. Es kristallisiert sich zunehmend heraus, dass es hier keine "One fits all" Lösung gibt, sondern dass individuell adaptierte Al-gorithmen und multimodale Signale und Daten erforderlich sind [31,[60][61][62], um eine klinisch sinnvolle Anfallszählung zu ermöglichen. Erst die Validierung solcher Technologien nach höchsten Gütekriterien auch unter nicht kontrollierten Bedingungen (Phase 4-Studie nach [12]) wird den zuverlässigen Einsatz im häuslichen Umfeld und in Einrichtungen, aber auch in randomisierten klinischen Studien zur Wirksamkeitsprüfung von Medikamenten, implantierten Neurostimulation-Systemen und epilepsiechirurgischen Eingriffen erlauben.…”

The Challenging Path to Developing a Mobile Health Device for Epilepsy: The Current Landscape and Where We Go From Here

“…The overarching goal of these devices is to provide continuous long-term monitoring of non-EEG seizure related signals in order to detect or forecast seizures (2)(3)(4)(5)(6)(7)(8)(9). Currently, however, seizure detection with appropriate sensitivity and false-alarm rates has only been possible for generalized tonic-clonic seizures (GTCS) (10,11), while clinically-relevant accuracy is still lacking for most other seizures types (12). Solutions to this limitation are likely to emerge from the rapid advances in machine-learning seizure detection and algorithms forecasting the cyclic nature of seizures (13,14).…”

Atrioventricular Conduction in Mesial Temporal Lobe Seizures

“…Given the intricate overlap of regions involved in the central autonomic nervous system (CAN) and networks that generate or maintain epileptic activity, seizures are frequently accompanied by alterations of cardiac properties and heart activity (1,2). These changes are mostly benign and may be used to detect and count epileptic seizures using wearable devices (3). Potentially lethal cardiac arrhythmias such as ventricular tachycardia or sustained asystole are rare and contribute to the elevated risk of premature mortality and sudden cardiac death in people with epilepsy (2,4).…”