Detection of convulsive seizures using surface electromyography
Detection of convulsive seizures using surface electromyography
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DOI：
10.1111/epi.14048
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发表时间：
2018-06-01
期刊：
影响因子：
5.6
通讯作者：
Wolf, Peter
中科院分区：
文献类型：
--
作者：
Beniczky, Sandor;Conradsen, Isa;Wolf, Peter
双侧（全身性）强直-阵挛性发作（TCS）增加了癫痫猝死（SUDEP）的风险，尤其是当患者无人看管时。在睡眠中，TCS通常不会被注意到，这可能导致次优的治疗决策。需要使用可穿戴设备自动检测这些主要癫痫发作。定量表面肌电图（EMG）的变化是特定的TCS，其特征在于低频和高频信号分量的动态演变。针对高频EMG信号增加的算法构成了TCS的生物标志物;它们既可用于癫痫发作检测，也可用于区分TCS与惊厥性非癫痫性发作。两项大规模、设盲、前瞻性研究证明了可穿戴EMG设备检测TCS的准确性，具有高灵敏度（76%-100%）。虚警率（0.7-2.5/24 h）有待进一步提高。本文总结了肌肉激活在惊厥发作的病理生理学，并回顾了已发表的证据的准确性，肌电图为基础的癫痫发作检测。
Bilateral (generalized) tonic-clonic seizures (TCS) increase the risk of sudden unexpected death in epilepsy (SUDEP), especially when patients are unattended. In sleep, TCS often remain unnoticed, which can result in suboptimal treatment decisions. There is a need for automated detection of these major epileptic seizures, using wearable devices. Quantitative surface electromyography (EMG) changes are specific for TCS and characterized by a dynamic evolution of low- and high-frequency signal components. Algorithms targeting increase in high-frequencyEMG signals constitute biomarkers of TCS; they can be used both for seizure detection and for differentiating TCS from convulsive nonepileptic seizures. Two large-scale, blinded, prospective studies demonstrated the accuracy of wearable EMG devices for detecting TCS with high sensitivity (76%-100%). The rate of false alarms (0.7-2.5/24h) needs further improvement. This article summarizes the pathophysiology of muscle activation during convulsive seizures and reviews the published evidence on the accuracy of EMG-based seizure detection.