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癫痫发作检测设备

Seizure Detection Devices.

作者信息

Baumgartner Christoph, Baumgartner Jakob, Lang Clemens, Lisy Tamara, Koren Johannes P

机构信息

Department of Neurology, Clinic Hietzing, 1130 Vienna, Austria.

Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, 1130 Vienna, Austria.

出版信息

J Clin Med. 2025 Jan 28;14(3):863. doi: 10.3390/jcm14030863.

Abstract

Goals of automated detection of epileptic seizures using wearable devices include objective documentation of seizures, prevention of sudden unexpected death in epilepsy (SUDEP) and seizure-related injuries, obviating both the unpredictability of seizures and potential social embarrassment, and finally to develop seizure-triggered on-demand therapies. Automated seizure detection devices are based on the analysis of EEG signals (scalp-EEG, subcutaneous EEG and intracranial EEG), of motor manifestations of seizures (surface EMG, accelerometry), and of physiologic autonomic changes caused by seizures (heart and respiration rate, oxygen saturation, sweat secretion, body temperature). While the detection of generalized tonic-clonic and of focal to bilateral tonic-clonic seizures can be achieved with high sensitivity and low false alarm rates, the detection of focal seizures is still suboptimal, especially in the everyday ambulatory setting. Multimodal seizure detection devices in general provide better performance than devices based on single measurement parameters. Long-term use of seizure detection devices in home environments helps to improve the accuracy of seizure diaries and to reduce seizure-related injuries, while evidence for prevention of SUDEP is still lacking. Automated seizure detection devices are generally well accepted by patients and caregivers.

摘要

使用可穿戴设备自动检测癫痫发作的目标包括癫痫发作的客观记录、预防癫痫猝死(SUDEP)和与发作相关的损伤、消除发作的不可预测性和潜在的社交尴尬,以及最终开发由发作触发的按需治疗。自动发作检测设备基于对脑电图信号(头皮脑电图、皮下脑电图和颅内脑电图)、发作的运动表现(表面肌电图、加速度测量)以及由发作引起的生理自主变化(心率和呼吸率、血氧饱和度、汗液分泌、体温)的分析。虽然全身性强直阵挛发作和局灶性至双侧强直阵挛发作的检测可以实现高灵敏度和低误报率,但局灶性发作的检测仍然不理想,尤其是在日常门诊环境中。一般来说,多模态发作检测设备比基于单一测量参数的设备性能更好。在家庭环境中长期使用发作检测设备有助于提高发作日记的准确性并减少与发作相关的损伤,而预防SUDEP的证据仍然不足。自动发作检测设备通常受到患者和护理人员的广泛接受。

相似文献

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Seizure Detection Devices.癫痫发作检测设备
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Automatic Computer-Based Detection of Epileptic Seizures.基于计算机的癫痫发作自动检测
Front Neurol. 2018 Aug 9;9:639. doi: 10.3389/fneur.2018.00639. eCollection 2018.
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Are Seizure Detection Devices Ready for Prime Time?癫痫检测设备准备好投入实际应用了吗?
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本文引用的文献

2
Sudden death in epilepsy: the overlap between cardiac and neurological factors.癫痫猝死:心脏与神经因素的重叠
Brain Commun. 2024 Oct 1;6(5):fcae309. doi: 10.1093/braincomms/fcae309. eCollection 2024.
4
The spectrum of indications for ultralong-term EEG monitoring.超长程脑电图监测的适应证谱。
Seizure. 2024 Oct;121:262-270. doi: 10.1016/j.seizure.2024.08.015. Epub 2024 Aug 22.

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