Algorithms for detecting atrial arrhythmias from discriminatory signatures of ventricular cycle lengths
US7031765B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 11, 2002 |
| Grant date | Apr 18, 2006 |
| Priority date | — |
| Expiry date | Apr 15, 2024 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2218/18
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Detection of arrhythmias is facilitated using irregularity of ventricular beats measured by delta-RR (ΔRR) intervals that exhibit discriminatory signatures when plotted in a Lorenz scatter-plot. An “AF signature metric” is established characteristic of episodes of AF that exhibit highly scattered (sparse) distributions or formations of 2-D data points. An “AFL signature metric” is established characteristic of episodes of AFL that exhibit a highly concentrated (clustered) distribution or formation of 2-D data points. A set of heart beat interval data is quantified to generate highly scattered (sparse) formations as a first discrimination metric and highly concentrated (clustered) distributions or formations as a second discrimination metric. The first discrimination metric is compared to the AF signature metric, and/or the second discrimination metric is compared to the AFL signature metric. AF or HFL is declared if the first discrimination metric satisfies either one of the AF signature metric.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.