Sunny Gupta,Mohsen Najafi Yazdi,Timothy William Fawcett Burton,Shyamlal Ramchandani,Derek Vincent Exner
申请号：
US15961213
公开号：
US20180303360A1
申请日:
2018.04.24
申请国别(地区):
US
年份:
2018
代理人:
摘要：
The present disclosure uses physiological data, ECG signals as an example, to evaluate cardiac structure and function in mammals. Two approaches are presented, e.g., a model-based analysis and a space-time analysis. The first method uses a modified Matching Pursuit (MMP) algorithm to find a noiseless model of the ECG data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to image and characterize cardiovascular tissues using complex-sub-harmonic-frequencies (CSF) quasi-periodic and other mathematical methods. In the second method, space-time domain is divided into a number of regions, the density of the ECG signal is computed in each region and inputted into a learning algorithm to image and characterize the tissues.
