中文摘要：

为了研究深部大脑电刺激对于癫痫等疾病的治疗作用,本文利用LabVIEW虚拟仪器环境和NI数据采集卡开发了一种闭环式电刺激系统,用于实现癫痫电信号的自动检测和刺激信号的输出。设计了结合场电位的幅值、斜率和海岸线参数3个特征量的癫痫波自动判定新算法。大鼠海马区癫痫模型的实验测试结果表明,该系统判定癫痫发作信号的正确率为91.3%,误检率为8.0%。而且,实时发生的高频电刺激展示了其抑制癫痫发作的效果。此外,系统设计了自动和手动等多种模式,具有较高的适应性和灵活性。癫痫波判定的简单时域算法也保证了系统具有较高的实时性,为电刺激控制癫痫的实验研究提供了一种简便易用的设备。

英文摘要：

In order to investigate the effect of deep brain stimulation on diseases such as epilepsy,we developed a closed-loop electrical stimulation system using LabVIEW virtual instrument environment and NI data acquisition card.The system was used to detect electrical signals of epileptic seizures automatically and to generate electrical stimuli.We designed a novel automatic detection algorithm of epileptic seizures by combining three features of field potentials：the amplitude,slope and coastline index.Experimental results of rat epileptic model in the hippocampal region showed that the system was able to detect epileptic seizures with an accuracy rate 91.3%and false rate 8.0%.Furthermore,the on-line high frequency electrical stimuli showed a suppression effect on seizures.In addition,the system was adaptive and flexible with multiple work modes,such as automatic and manual modes.Moreover,the simple time-domain algorithm of seizure detection guaranteed the real-time feature of the system and provided an easy-to-use equipment for the experiment researches of epilepsy control by electrical stimulation.