Difference between revisions of "Non-EEG seizure detection systems and potential SUDEP prevention: State of the art: Review and update"
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| − | + | Van de Vel A, Cuppens K, Bonroy B (2016) Non-EEG seizure detection systems and potential SUDEP prevention: State of the art: Review and update. Seizure. 2016 Oct;41:141-53. | |
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| − | == | + | https://ac.els-cdn.com/S1059131116301145/1-s2.0-S1059131116301145-main.pdf?_tid=a40952ed-79ea-415b-9836-2ffb77a12896&acdnat=1531169538_bee3ad5c9ddf963925a205c0c7fe9bef |
| − | == | + | |abstract= |
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| + | PURPOSE: Detection of, and alarming for epileptic seizures is increasingly demanded and researched. Our previous review article provided an overview of non-invasive, non-EEG (electro-encephalography) body signals that can be measured, along with corresponding methods, state of the art research, and commercially available systems. Three years later, many more studies and devices have emerged. Moreover, the boom of smart phones and tablets created a new market for seizure detection applications. METHOD: We performed a thorough literature review and had contact with manufacturers of commercially available devices. RESULTS: This review article gives an updated overview of body signals and methods for seizure detection, international research and (commercially) available systems and applications. Reported results of non-EEG based detection devices vary between 2.2% and 100% sensitivity and between 0 and 3.23 false detections per hour compared to the gold standard video-EEG, for seizures ranging from generalized to convulsive or non-convulsive focal seizures with or without loss of consciousness. It is particularly interesting to include monitoring of autonomic dysfunction, as this may be an important pathophysiological mechanism of SUDEP (sudden unexpected death in epilepsy), and of movement, as many seizures have a motor component. CONCLUSION: Comparison of research results is difficult as studies focus on different seizure types, timing (night versus day) and patients (adult versus pediatric patients). Nevertheless, we are convinced that the most effective seizure detection systems are multimodal, combining for example detection methods for movement and heart rate, and that devices should especially take into account the user's seizure types and personal preferences. | ||
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| + | Alarm system; Epilepsy; Non-EEG based seizure detection; SUDEP; Sudden unexpected death | ||
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Latest revision as of 13:45, 17 June 2019
Van de Vel A, Cuppens K, Bonroy B (2016) Non-EEG seizure detection systems and potential SUDEP prevention: State of the art: Review and update. Seizure. 2016 Oct;41:141-53.
Abstract: PURPOSE: Detection of, and alarming for epileptic seizures is increasingly demanded and researched. Our previous review article provided an overview of non-invasive, non-EEG (electro-encephalography) body signals that can be measured, along with corresponding methods, state of the art research, and commercially available systems. Three years later, many more studies and devices have emerged. Moreover, the boom of smart phones and tablets created a new market for seizure detection applications. METHOD: We performed a thorough literature review and had contact with manufacturers of commercially available devices. RESULTS: This review article gives an updated overview of body signals and methods for seizure detection, international research and (commercially) available systems and applications. Reported results of non-EEG based detection devices vary between 2.2% and 100% sensitivity and between 0 and 3.23 false detections per hour compared to the gold standard video-EEG, for seizures ranging from generalized to convulsive or non-convulsive focal seizures with or without loss of consciousness. It is particularly interesting to include monitoring of autonomic dysfunction, as this may be an important pathophysiological mechanism of SUDEP (sudden unexpected death in epilepsy), and of movement, as many seizures have a motor component. CONCLUSION: Comparison of research results is difficult as studies focus on different seizure types, timing (night versus day) and patients (adult versus pediatric patients). Nevertheless, we are convinced that the most effective seizure detection systems are multimodal, combining for example detection methods for movement and heart rate, and that devices should especially take into account the user's seizure types and personal preferences.
Keywords: Alarm system; Epilepsy; Non-EEG based seizure detection; SUDEP; Sudden unexpected death