Judith van Andel1, Roland D Thijs2, Al de Weerd3, Johan Arends4, Frans Leijten5. 1. University Medical Centre Utrecht, Department of Clinical Neurophysiology, Utrecht, The Netherlands. Electronic address: judithvanandel@gmail.com. 2. Stichting Epilepsie Instellingen Nederland SEIN, Department of Clinical Neurophysiology, Heemstede, The Netherlands; Leiden University Medical Centre, Department of Neurology, Leiden, The Netherlands. 3. Stichting Epilepsie Instellingen Nederland SEIN, Department of Clinical Neurophysiology, Zwolle, The Netherlands. 4. Academic Centre for Epileptology Kempenhaeghe, Department of Clinical Neurophysiology, Heeze, The Netherlands. 5. University Medical Centre Utrecht, Department of Clinical Neurophysiology, Utrecht, The Netherlands.
Abstract
OBJECTIVE: This study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and disadvantages of seizure detection in epilepsy care. METHODS: PubMed and EMBASE were searched up to November 2014, using variations and synonyms of search terms "seizure prediction" OR "seizure detection" OR "seizures" AND "alarm". RESULTS: Seventeen studies evaluated performance of devices and algorithms to detect seizures in a clinical setting. Algorithms detecting generalized tonic-clonic seizures (GTCSs) had varying sensitivities (11% to 100%) and false alarm rates (0.2-4/24 h). For other seizure types, detection rates were low, or devices produced many false alarms. Five studies externally validated the performance of four different devices for the detection of GTCSs. Two devices were promising in both children and adults: a mattress-based nocturnal seizure detector (sensitivity: 84.6% and 100%; false alarm rate: not reported) and a wrist-based detector (sensitivity: 89.7%; false alarm rate: 0.2/24 h). SIGNIFICANCE: Detection of seizure types other than GTCSs is currently unreliable. Two detection devices for GTCSs provided promising results when externally validated in a clinical setting. However, these devices need to be evaluated in the home setting in order to establish their true value. Automatic seizure detection may help prevent sudden unexpected death in epilepsy or status epilepticus, provided the alarm is followed by an effective intervention. Accurate seizure detection may improve the quality of life (QoL) of subjects and caregivers by decreasing burden of seizure monitoring and may facilitate diagnostic monitoring in the home setting. Possible risks are occurrence of alarm fatigue and invasion of privacy. Moreover, an unexpectedly high seizure frequency might be detected for which there are no treatment options. We propose that future studies monitor benefits and disadvantages of seizure detection systems with particular emphasis on QoL, comfort, and privacy of subjects and impact of false alarms.
OBJECTIVE: This study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and disadvantages of seizure detection in epilepsy care. METHODS: PubMed and EMBASE were searched up to November 2014, using variations and synonyms of search terms "seizure prediction" OR "seizure detection" OR "seizures" AND "alarm". RESULTS: Seventeen studies evaluated performance of devices and algorithms to detect seizures in a clinical setting. Algorithms detecting generalized tonic-clonic seizures (GTCSs) had varying sensitivities (11% to 100%) and false alarm rates (0.2-4/24 h). For other seizure types, detection rates were low, or devices produced many false alarms. Five studies externally validated the performance of four different devices for the detection of GTCSs. Two devices were promising in both children and adults: a mattress-based nocturnal seizure detector (sensitivity: 84.6% and 100%; false alarm rate: not reported) and a wrist-based detector (sensitivity: 89.7%; false alarm rate: 0.2/24 h). SIGNIFICANCE: Detection of seizure types other than GTCSs is currently unreliable. Two detection devices for GTCSs provided promising results when externally validated in a clinical setting. However, these devices need to be evaluated in the home setting in order to establish their true value. Automatic seizure detection may help prevent sudden unexpected death in epilepsy or status epilepticus, provided the alarm is followed by an effective intervention. Accurate seizure detection may improve the quality of life (QoL) of subjects and caregivers by decreasing burden of seizure monitoring and may facilitate diagnostic monitoring in the home setting. Possible risks are occurrence of alarm fatigue and invasion of privacy. Moreover, an unexpectedly high seizure frequency might be detected for which there are no treatment options. We propose that future studies monitor benefits and disadvantages of seizure detection systems with particular emphasis on QoL, comfort, and privacy of subjects and impact of false alarms.
Authors: Judith van Andel; Constantin Ungureanu; Johan Arends; Francis Tan; Johannes Van Dijk; George Petkov; Stiliyan Kalitzin; Thea Gutter; Al de Weerd; Ben Vledder; Roland Thijs; Ghislaine van Thiel; Kit Roes; Frans Leijten Journal: Epilepsia Open Date: 2017-09-06
Authors: Johan Arends; Roland D Thijs; Thea Gutter; Constantin Ungureanu; Pierre Cluitmans; Johannes Van Dijk; Judith van Andel; Francis Tan; Al de Weerd; Ben Vledder; Wytske Hofstra; Richard Lazeron; Ghislaine van Thiel; Kit C B Roes; Frans Leijten Journal: Neurology Date: 2018-10-24 Impact factor: 9.910
Authors: Anouk van Westrhenen; Thomas De Cooman; Richard H C Lazeron; Sabine Van Huffel; Roland D Thijs Journal: Clin Auton Res Date: 2018-10-30 Impact factor: 4.435