Name
Title | ||
|---|---|---|
Arm-ECG bipolar leads signal recovery methods for wearable long-term heart rate and rhythm monitoring |
Abstract | ||
|---|---|---|
A clinical database of distal electrogram recordings was created in conjunction with the Craigavon Area Hospital Cardiac Research Department. Signal averaged ECG (SAECG) methods were then used to inspect electrograms recorded bilaterally in a pilot study and the evidence based outcome of which directed the WASTCArD research group to consider the left arm as a prime location for a potential long term cardiac monitor. Empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and data fusion (DF) techniques were developed due to their ability to extract morphologically intact information from a dynamic data stream and their performance compared to the control SAECG reference method and clinically accepted denoising approach in high-resolution electrocardiography. EEMD was found to be a robust, low latency denoising technique, in comparison to SAECG performance; achieving signal to noise enhancement figures that, in some cases, improved on the SAECG control method, when used with far-field bipolar leads along the left arm ECG data. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.22489/CinC.2017.072-464 | 2017 Computing in Cardiology (CinC) |
Keywords | Field | DocType |
rhythm monitoring,clinical database,distal electrogram recordings,Craigavon Area Hospital Cardiac Research Department,electrograms,WASTCArD research group,potential long term cardiac monitor,empirical mode decomposition,EEMD,morphologically intact information,dynamic data stream,high-resolution electrocardiography,SAECG performance,SAECG control method,far-field bipolar,left arm ECG data,arm-ECG bipolar leads signal recovery methods,wearable long-term heart rate,signal averaged ECG methods,ensemble empirical mode decomposition,EMD,data fusion,denoising approach,low latency denoising technique,signal-to-noise enhancement figures,SAECG leads | Noise reduction,Pattern recognition,Computer science,Signal-to-noise ratio,Sensor fusion,Dynamic data,Artificial intelligence,Signal-averaged electrocardiogram,Electrocardiography,Signal averaging,Hilbert–Huang transform | Conference |
Volume | ISSN | ISBN |
44 | 2325-8861 | 978-1-5386-4555-0 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| William David Lynn | 1 | 0 | 0.34 |
| Omar Escalona | 2 | 0 | 1.01 |
| Pedro Vizcaya | 3 | 0 | 0.34 |
| david mceneaney | 4 | 1 | 3.67 |