Automated ventricular ectopic beat classification
US11763943B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Feb 22, 2019 |
| Grant date | Sep 19, 2023 |
| Priority date | — |
| Expiry date | Feb 22, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/082
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for classifying heartbeats using patient electrocardiogram (ECG) data are described. ECG data is received, including waveform data and time interval data relating to a plurality of heartbeats for the patient. A convolutional neural network in a first path of a machine learning architecture generates a first plurality of output values by analyzing the waveform data. A fully-connected neural network in a second path of the machine learning architecture generates a second plurality of output values by analyzing the time interval data. The plurality of heartbeats in the ECG data are classified by concatenating the first plurality of output values and the second plurality of output values using the machine learning architecture.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.