NEUROMAGNETOMETER COMPUTER SYSTEM

NINDS医学神经科和计算机系统实验室， DCRT合作了一个研究项目，以非侵入性的本地化 利用神经磁学技术研究人脑内癫痫放电的来源 与常规脑电(EEG)联合记录 正在录音。许多癫痫患者表现出低水平的细胞 发作之间的放电，表现为发作间期的尖峰或尖波 在他们的脑电和脑磁图记录中。这个项目 涉及计算机技术的发展，以实现自动化和 改进NINDS神经病学家用来确定 儿童癫痫样放电来源的颅内定位 癫痫患者。 在上一财年，CSL设计了一个计算机系统，可以检测到 脑电和脑磁图信号中的癫痫样放电。这 系统已经用多个检测算法实现， 包括CSL开发的和从出版的 文献，以及配置这些算法的各种选项 允许医务人员为给定的疾病选择最佳方法 有耐心的。该系统提供信号的实时显示 其中检测到事件并允许神经科医生手动保存 癫痫样放电和更长的癫痫发作活动。 在过去的一年里，CSL进行了全面的临床评估 该实时检测系统具有多种患者信号和 将其性能与使用 算法在CSL系统上不可用。中超系统可靠 检测到的癫痫事件，表现优于商业系统，以及 已投入临床运行。

The Medical Neurology Branch, NINDS, and the Computer Systems Laboratory, DCRT, have collaborated on a research project to noninvasively localize epileptic discharge sources within the human brain by using neuromagnetic recording in conjunction with conventional electroencephalogram (EEG) recording. Many patients with seizure disorders exhibit low-level cellular discharges between seizures, indicated by interictal spikes or sharp waves in their EEG and magnetoencephalogram (MEG) recordings. This project involved the development of computer techniques for automating and enhancing the procedure that is used by NINDS neurologists to determine the intracranial locations of the sources of epileptiform discharges in patients with epilepsy. In a previous fiscal year, CSL designed a computer system that detects epileptiform discharges from the EEG and MEG signals in real-time. This system has been implemented with a number of detection algorithms, including both those developed by CSL and some selected from the published literature, and a variety of options for configuring these algorithms allowing the medical staff to choose the optimal method for a given patient. The system provides a real-time display of the signals showing where an event is detected and allows the neurologists to manually save both epileptiform discharges and longer seizure activity. During the past year, CSL performed a comprehensive clinical evaluation of the real-time detection system with a variety of patient signals and compared its performance to that of a new commercial system that uses an algorithm not available on the CSL system. The CSL system reliably detected epileptic events, performed better than the commercial system, and was placed into clinical operation.