Abstract
Body surface potential maps (BSPMs) are typically recorded from a large number of ECG leads that cover the entire thorax. This improves diagnostic accuracy and is required in Electrocardiographic imaging (ECGi). BSPMs recorded in the clinical setting may have some leads that are noisy due to poor skin electrode contact. We analyzed 117 lead BSPMs recorded from 360 subjects. We successively simulated the removal of ECG leads at various locations and tested the ability of our algorithm to accurately reconstruct the missing information.
| Original language | English |
|---|---|
| Pages | 1 |
| Number of pages | 4 |
| Publication status | Published online - 1 Oct 2018 |
| Event | Computing in Cardiology - Maastricht, Netherlands Duration: 23 Sept 2018 → 26 Sept 2018 http://www.cinc.org/2018/CinC2018ProgramOverview.pdf |
Conference
| Conference | Computing in Cardiology |
|---|---|
| Country/Territory | Netherlands |
| City | Maastricht |
| Period | 23/09/18 → 26/09/18 |
| Internet address |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- ECG
- BSPM
- Laplacian
- Noise
- Signal Processing
Fingerprint
Dive into the research topics of 'An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps'. Together they form a unique fingerprint.Student theses
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Methods for signal processing and interpolation of body surface ECG signals and the impact on the inverse reconstructed cardiac electrical activity
Rababah, A. (Author), Mc Laughlin, J. (Supervisor) & Finlay, D. (Supervisor), Oct 2021Student thesis: Doctoral Thesis
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