Related Experiment Videos
Temporal and spatial analysis of potential maps via multiresolution decompositions
D H Brooks1, R S MacLeod, R V Chary
1ECE Department, Northeastern University, Boston, Massachusetts 02115, USA.
Journal of Electrocardiology
|January 1, 1996
Summary
This study introduces wavelet-type transforms for analyzing cardiac electrical signals. This method offers a flexible alternative to traditional techniques for both spatial and temporal signal segmentation.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Cardiology
Background:
- Cardiac potential analysis typically uses spatial or temporal descriptors separately.
- Existing methods like Karhunen-Loeve transform are global and data-dependent.
- There is a need for methods combining spatial and temporal analysis effectively.
Purpose of the Study:
- To explore multiresolution decompositions and wavelet-type transforms for cardiac signal analysis.
- To provide a flexible alternative to global transform techniques.
- To demonstrate the utility of wavelet transforms for temporal and spatial segmentation of cardiac mapping data.
Main Methods:
- Application of multiresolution decompositions and wavelet-type transforms.
- Analysis of both spatial distributions and temporal waveforms of cardiac potentials.
- Utilizing local, fixed databases for transformations.
Main Results:
- Wavelet-type transforms enable flexible, local analysis of cardiac signals.
- The method effectively combines spatial and temporal characteristics.
- Demonstrated utility in segmenting and analyzing epicardial plaque and body surface potential mapping data.
Conclusions:
- Wavelet-type transforms offer a powerful and flexible approach for cardiac signal analysis.
- This method enhances the combined temporal and spatial segmentation of cardiac mapping data.
- The approach is particularly useful for analyzing data from interventions like percutaneous transluminal coronary angioplasty.