Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark; Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus C, Denmark.
Epilepsia. 2014 Jul;55(7):1128-34. doi: 10.1111/epi.12669. Epub 2014 Jun 2.
To investigate the characteristics of sustained muscle activation during convulsive epileptic and psychogenic nonepileptic seizures (PNES), as compared to voluntary muscle activation. The main goal was to find surface electromyography (EMG) features that can distinguish between convulsive epileptic seizures and convulsive PNES.
In this case-control study, surface EMG was recorded from the deltoid muscles during long-term video-electroencephalography (EEG) monitoring in 25 patients and in 21 healthy controls. A total of 46 clinical episodes were recorded: 28 generalized tonic-clonic seizures (GTCS) from 14 patients with epilepsy, and 18 convulsive PNES from 12 patients (one patient had both GTCS and PNES). The healthy controls were simulating GTCS. To quantitatively characterize the signals we calculated the following parameters: root mean square (RMS) of the amplitude, median frequency (MF), coherence, and duration of the seizures, of the clonic EMG discharges, and of the silent periods between the cloni. Based on wavelet analysis, we distinguished between a low-frequency component (LF 2-8 Hz) and a high-frequency component (HF 64-256 Hz).
Duration of the seizure, and separation between the tonic and the clonic phases distinguished at group-level but not at individual level between convulsive PNES and GTCS. RMS, temporal dynamics of the HF/LF ratio, and the evolution of the silent periods differentiated between epileptic and nonepileptic convulsive seizures at the individual level. A combination between HF/LF ratio and RMS separated all PNES from the GTCS. A blinded review of the EMG features distinguished correctly between GTCS and convulsive PNES in all cases. The HF/LF ratio and the RMS of the PNES were smaller compared to the simulated seizures.
In addition to providing insight into the mechanism of muscle activation during convulsive PNES, these results have diagnostic significance, at the individual level. Surface EMG features can accurately distinguish convulsive epileptic from nonepileptic psychogenic seizures, even in PNES cases without rhythmic clonic movements.
研究癫痫性抽搐发作和非癫痫性精神性抽搐发作（PNES）时肌肉持续激活的特点，与自愿肌肉激活相比。主要目标是找到可区分癫痫性抽搐发作和癫痫性 PNES 的表面肌电图（EMG）特征。
在这项病例对照研究中，对 25 名患者和 21 名健康对照者在长期视频脑电图（EEG）监测期间记录三角肌表面 EMG。共记录了 46 次临床发作：14 名癫痫患者中有 28 次全身性强直阵挛发作（GTCS），12 名患者中有 18 次癫痫性 PNES（1 名患者既有 GTCS 又有 PNES）。健康对照组模拟 GTCS。为了定量描述信号，我们计算了以下参数：幅度的均方根（RMS）、中值频率（MF）、相干性、发作、阵挛性 EMG 放电和阵挛之间的静默期的持续时间。基于小波分析，我们区分了低频成分（LF 2-8 Hz）和高频成分（HF 64-256 Hz）。
发作持续时间和强直与阵挛相之间的分离在组水平上区分了癫痫性和非癫痫性抽搐发作，但在个体水平上没有区分。RMS、HF/LF 比值的时间动态和静默期的演变在个体水平上区分了癫痫性和非癫痫性抽搐发作。HF/LF 比值和 RMS 的组合将所有 PNES 与 GTCS 分开。对 EMG 特征的盲法审查在所有情况下均正确区分了 GTCS 和癫痫性 PNES。PNES 的 HF/LF 比值和 RMS 小于模拟发作。
除了为肌肉在癫痫性 PNES 时的激活机制提供深入了解外，这些结果还具有诊断意义，特别是在个体水平上。表面肌电图特征可以准确区分癫痫性抽搐发作和非癫痫性精神性抽搐发作，即使在没有节律性阵挛运动的 PNES 病例中也是如此。
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