公开(公告)号：WO2018035299A1

公开(公告)日：2018-02-22

申请号：PCT/US2017/047303

申请日：2017-08-17

Applicant: ARIZONA BOARD OF REGENTS ON BEHALF of ARIZONA STATE UNIVERSITY

Inventor： SHAFIQUE, Ashfaque ,  TREIMAN, David ,  TSAKALIS, Konstantinos

IPC: A61B5/0476

CPC classification number: A61B5/4094 ,  A61B5/04012 ,  A61B5/0476 ,  A61B5/0478 ,  A61B5/6803 ,  A61B5/7235 ,  A61B5/7282 ,  A61B5/742

Abstract: Systems and methods for tracking EEG data and providing enhanced seizure detection and prediction are disclosed. The systems and methods use input sensors for receiving and collecting data from a plurality of EEG channels in association with a subject and processing said data to calculate and average Lyapunov exponents for a composite EEG data set. The systems and methods convert the average Lyapunov exponents into graphical representations that are displayed against a time axis. The graphical output adjusts in real-time according to the input data obtained from EEG channels. The systems and methods utilize pattern recognition to output alarms based upon input data and recommend diagnoses related to seizures.

Abstract translation: 公开了用于跟踪EEG数据并提供增强的癫痫发作检测和预测的系统和方法。 该系统和方法使用输入传感器来接收和收集来自与对象相关的多个EEG通道的数据，并处理所述数据以计算和平均复合EEG数据集的Lyapunov指数。 该系统和方法将平均Lyapunov指数转换成相对于时间轴显示的图形表示。 图形输出根据从EEG通道获得的输入数据进行实时调整。 该系统和方法利用模式识别来输出基于输入数据的警报并推荐与癫痫相关的诊断。