心电图监测能识别癫痫发作吗？
Can ECG monitoring identify seizures?
作者信息
Varon Carolina, Jansen Katrien, Lagae Lieven, Van Huffel Sabine
机构信息
KU Leuven, Department of Electrical Engineering ESAT-STADIUS, Kasteelpark Arenberg 10, Leuven, Belgium; iMinds Medical IT Department, Kasteelpark Arenberg 10, Leuven, Belgium.
Pediatric neurology, University Hospitals Leuven, UZ Herestraat 49, Leuven, Belgium.
出版信息
J Electrocardiol. 2015 Nov-Dec;48(6):1069-74. doi: 10.1016/j.jelectrocard.2015.08.020. Epub 2015 Aug 6.
BACKGROUND
Seizures affect the autonomic control of the heart rate and respiration, and changes in these two variables are known to occur during, and even before the EEG onset of the seizure.
GOAL
This work aims to quantify these changes and use them to identify the ECG onset.
METHODS
Single-lead ECG signals were recorded from patients suffering from focal and generalized seizures. Two algorithms are proposed: one quantifies changes in the QRS morphology using principal component analysis, and one assesses cardiorespiratory interactions using phase rectified signal averaging.
RESULTS
Positive predictive values of 86.6% and 77.5% and sensitivities of 100% and 90% were achieved for focal and generalized seizures respectively.
CONCLUSION
Results for focal seizures are in accordance with the literature, and detection of generalized seizures is improved after including respiratory information.
SIGNIFICANCE
These findings could improve monitoring systems in epilepsy, and closed-loop techniques that aim to stop seizures.
背景
癫痫发作会影响心率和呼吸的自主控制，并且已知在癫痫发作的脑电图发作期间甚至之前，这两个变量就会发生变化。
目标
这项工作旨在量化这些变化并利用它们来识别心电图发作。
方法
从患有局灶性和全身性癫痫发作的患者记录单导联心电图信号。提出了两种算法：一种使用主成分分析量化QRS形态的变化，另一种使用相位整流信号平均评估心肺相互作用。
结果
局灶性和全身性癫痫发作的阳性预测值分别为86.6%和77.5%，敏感性分别为100%和90%。
结论
局灶性癫痫发作的结果与文献一致，纳入呼吸信息后全身性癫痫发作的检测得到改善。
意义
这些发现可能会改善癫痫监测系统以及旨在终止癫痫发作的闭环技术。
Zotero 插件