Method and apparatus for beat-space frequency domain prediction of cardiovascular death after acute coronary event

Patent metadata

Field	Value
Publication number	US-9295397-B2
Application number	US-201414305260-A
Country	US
Kind code	B2
Filing date	Jun 16, 2014
Priority date	Jun 14, 2013
Publication date	Mar 29, 2016
Grant date	Mar 29, 2016

Abstract

A method for the machine generation of a model for predicting patient outcome following the occurrence of an event. In one embodiment the method includes the steps of obtaining a physiological signal of interest, the physiological signal having a characteristic; obtaining a time series of a signal characteristic; dividing the time series into a plurality of window segments; converting the time series from time-space to beat-space; computing the power in various frequency bands of each window segment; computing the 90th percentile of the spectral energies across all window segments for each frequency band; and inputting the data into a machine learning program to generate a weighted risk vector.

First claim

What is claimed is:

1. A method for the machine generation of a model for predicting death within a predetermined period following the occurrence of a cardiac event, the method comprising the steps of:
obtaining an ECG of interest from a plurality of patients having a plurality of outcomes, the ECG having a plurality of ECG characteristics;
obtaining a time series of one of the ECG characteristics of the plurality of ECG characteristics;
dividing the time series into a plurali…

Assignees

• Massachusetts Inst Technology

Inventors

• Liu Yun
• Guttag John V
• Stultz Collin M

Classifications

• A61B5/0816

  Human Necessities · mapped topic

• A61B5/7275 Primary

  Human Necessities · mapped topic

• A61B5/7267 Primary

  Human Necessities · mapped topic

• A61B5/04014 Primary

  Human Necessities · mapped topic

• G16H50/30

  Physics · mapped topic