Wearable seizure detection devices in refractory epilepsy
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REVIEW ARTICLE
Wearable seizure detection devices in refractory epilepsy Julie Verdru1 · Wim Van Paesschen2,3 Received: 10 March 2020 / Accepted: 29 June 2020 © Belgian Neurological Society 2020
Abstract Epilepsy affects 50 million patients and their caregivers worldwide. Devices that facilitate the detection of seizures can have a large influence on a patient’s quality of life, therapeutic decisions and the conduct of clinical trials with anti-epileptic drugs. This article provides an up-to-date overview and comparison between wearable seizure detection devices (WSDDs), taking into account the newly proposed standards for testing and clinical validation of devices. 16 devices were included in our comparison. The F1-score, combining the device’s accurate recall and precision, was calculated for each of these devices and used to evaluate their performance. The devices were separated by development phase and ranked by F1-score from highest to lowest. We describe 16 WSDDs: 6 of which were accelerometry (ACM)-based, 3 surface electromyography-based, 1 was a wearable application of EEG, 4 had multimodal sensors and 2 other types of sensors. We observed a significant inconsistency in the description of performance measures. The devices in the most advanced development phase with the highest F1-scores incorporated ACM- and sEMG-based sensors to detect tonic–clonic seizures. This review highlights the importance of implementing standards for an optimal comparison and, therefore, improving the research and development of WSDDs. WSDDs can improve the patient’s care and quality of life, decrease seizure underreporting and they could potentially prevent sudden-unexpected-death in epilepsy. We discuss the central role of the neurologist in the use of WSDDs, and why a business to business to consumer model is better than the current business to consumer model of most WSDDs. Keywords Seizure detection · Wearable devices · Clinical validation · Business model
Introduction Epilepsy is caused by a hyperexcitability and hypersynchronisation of neural activity. Around 30% of patients with epilepsy are refractory, meaning the disease is not controllable with various different types of medication regimens [1]. Seizure detection affects aspects of the disease such as individual therapeutic assessment, clinical trials involving anti-epileptic drugs (AEDs) and the patient’s quality of life (e.g., ability to drive), and prevention of sudden unexpected death in epilepsy (SUDEP) [2]. Patient self-reporting of seizures has been proven to be inaccurate: less than half of * Julie Verdru [email protected] 1
Faculty of Medicine/UZ Leuven, KU Leuven, Leuven, Belgium
2
Laboratory for Epilepsy Research, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
3
Department of Neurology, UZ Leuven, Herestraat 49, 3000 Leuven, Belgium
the seizures were reported correctly through self-reporting [3]. This influences clinical practice and the results of clinical trials due to an inaccurate representation of the patient’s response
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