Non-EEG based ambulatory seizure detection designed for home use: What is available and how will it influence epilepsy care?
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. PubMed and EMBASE were searched up to November 2014, using variations and synonyms of search terms “seizure p...
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Published in | Epilepsy & behavior Vol. 57; no. Pt A; pp. 82 - 89 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.04.2016
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Subjects | |
Online Access | Get full text |
ISSN | 1525-5050 1525-5069 |
DOI | 10.1016/j.yebeh.2016.01.003 |
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Abstract | 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.
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”.
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 (0.2–4/24h). 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: 0.2/24h).
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.
•We evaluated systems and algorithms for ambulatory automatic seizure detection.•Detection of seizure types other than generalized tonic–clonic is unreliable.•Two detectors of generalized tonic–clonic seizures show promising results in clinic.•Evaluation in home setting necessary to assess true value of seizure detectors•Seizure detection may help prevent SUDEP and improve the QoL of patients and caregivers. |
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AbstractList | 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.
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”.
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 (0.2–4/24h). 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: 0.2/24h).
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.
•We evaluated systems and algorithms for ambulatory automatic seizure detection.•Detection of seizure types other than generalized tonic–clonic is unreliable.•Two detectors of generalized tonic–clonic seizures show promising results in clinic.•Evaluation in home setting necessary to assess true value of seizure detectors•Seizure detection may help prevent SUDEP and improve the QoL of patients and caregivers. 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. OBJECTIVEThis 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.METHODSPubMed and EMBASE were searched up to November 2014, using variations and synonyms of search terms "seizure prediction" OR "seizure detection" OR "seizures" AND "alarm".RESULTSSeventeen 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).SIGNIFICANCEDetection 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. 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. 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. 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". 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). 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. |
Author | de Weerd, Al van Andel, Judith Thijs, Roland D. Arends, Johan Leijten, Frans |
Author_xml | – sequence: 1 givenname: Judith surname: van Andel fullname: van Andel, Judith email: judithvanandel@gmail.com organization: University Medical Centre Utrecht, Department of Clinical Neurophysiology, Utrecht, The Netherlands – sequence: 2 givenname: Roland D. surname: Thijs fullname: Thijs, Roland D. organization: Stichting Epilepsie Instellingen Nederland SEIN, Department of Clinical Neurophysiology, Heemstede, The Netherlands – sequence: 3 givenname: Al surname: de Weerd fullname: de Weerd, Al organization: Stichting Epilepsie Instellingen Nederland SEIN, Department of Clinical Neurophysiology, Zwolle, The Netherlands – sequence: 4 givenname: Johan surname: Arends fullname: Arends, Johan organization: Academic Centre for Epileptology Kempenhaeghe, Department of Clinical Neurophysiology, Heeze, The Netherlands – sequence: 5 givenname: Frans surname: Leijten fullname: Leijten, Frans organization: University Medical Centre Utrecht, Department of Clinical Neurophysiology, Utrecht, The Netherlands |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26926071$$D View this record in MEDLINE/PubMed |
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publication-title: Epilepsy Behav doi: 10.1016/j.yebeh.2011.09.012 |
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Snippet | This study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and disadvantages of... Abstract Objective This study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and... OBJECTIVEThis study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and... Objective: This study aimed to (1) evaluate available systems and algorithms for ambulatory automatic seizure detection and (2) discuss benefits and... |
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SubjectTerms | Adult Algorithms Child Death, Sudden - prevention & control Electrocardiography, Ambulatory - methods Electroencephalography Epilepsy - diagnosis Epilepsy - psychology Female Humans Neurology Quality of Life Seizure detection Seizures - diagnosis Seizures - psychology Status Epilepticus |
Title | Non-EEG based ambulatory seizure detection designed for home use: What is available and how will it influence epilepsy care? |
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