Sunny Gupta,Mohsen Najafi Yazdi,Timothy William Fawcett Burton,Shyamlal Ramchandani,Derek Vincent Exner
申请号：
US15941736
公开号：
US10383535B2
申请日:
2018.03.30
申请国别(地区):
US
年份:
2019
代理人:
摘要：
Methods and systems for evaluating the electrical activity of the heart to identify novel ECG patterns closely linked to the subsequent development of serious heart rhythm disturbances and fatal cardiac events. Two approaches are describe, for example a model-based analysis and space-time analysis, which are used to study the dynamical and geometrical properties of the ECG data. In the first a model is derived using a modified Matching Pursuit (MMP) algorithm. Various metrics and subspaces are extracted to characterize the risk for serious heart rhythm disturbances, sudden cardiac death, other modes of death, and all-cause mortality linked to different electrical abnormalities of the heart. In the second method, space-time domain is divided into a number of regions (e.g., 12 regions), the density of the ECG signal is computed in each region and input to a learning algorithm to associate them with these events.
