Method and device for self-learning dynamic electrocardiography analysis employing artificial intelligence
US11234629B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 12, 2018 |
| Grant date | Feb 1, 2022 |
| Priority date | — |
| Expiry date | Mar 23, 2038 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA61B5/7271
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
A self-learning dynamic electrocardiography analysis method employing artificial intelligence. The method comprises: pre-processing data, performing cardiac activity feature detection, interference signal detection and cardiac activity classification on the basis of a deep learning method, performing signal quality evaluation and lead combination, examining cardiac activity, performing analytic computations on an electrocardiogram event and parameters, and then automatically outputting report data. The method achieves an automatic analysis method for a quick and comprehensive dynamic electrocardiography process, and recording of modification information of an automatic analysis result, while also collecting and feeding back modification data to a deep learning model for continuous training, thereby continuously improving and enhancing the accuracy of the automatic analysis method. Also disclosed is a self-learning dynamic electrocardiography analysis device employing artificial intelligence.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.