Removal of Baseline Wander from ECG Signals
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Resource Overview
Removal of baseline wander from ECG signals using adaptive filtering and other methods, including MATLAB implementation with algorithm explanations
Detailed Documentation
During experimental procedures, baseline wander in ECG signals may interfere with data analysis and interpretation. To eliminate this interference, we can employ methods such as adaptive filtering to remove baseline drift. Adaptive filtering is a signal processing technique that automatically adjusts filter parameters to adapt to signal characteristics. In our research, we implemented an adaptive filtering algorithm using MATLAB to remove baseline wander from ECG signals. The implementation typically involves key functions like `adaptfilt.lms` for Least Mean Squares adaptation or wavelet transform functions for multi-resolution analysis. This program enables more accurate analysis of ECG signals and helps derive more reliable conclusions by maintaining signal integrity through dynamic parameter optimization.
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