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[ECG signal compression based on best basis of wavelet packets]
1Civil Aviation Institute of China, Tianjin 300300.
Summary
This study introduces an efficient electrocardiogram (ECG) signal compression method using wavelet packets and Shannon-Weaker entropy. The new technique achieves high compression ratios with minimal data loss, enabling accurate signal recovery.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Data Compression
Background:
- Electrocardiogram (ECG) signal analysis is crucial for diagnosing cardiac conditions.
- Efficient compression of ECG data is necessary for storage and transmission.
- Existing compression methods may face limitations in achieving high compression ratios and preserving signal fidelity.
Purpose of the Study:
- To develop and evaluate a novel compression method for ECG signals.
- To leverage wavelet packet transform and entropy criteria for optimized signal compression.
- To assess the efficiency of the proposed method in terms of compression ratio and signal reconstruction quality.
Main Methods:
- Implementation of a new ECG signal compression algorithm.
- Utilizing wavelet packet transform for signal decomposition.
- Employing the Shannon-Weaker entropy criterion to determine the best basis for compression.
Main Results:
- The proposed method demonstrates a larger compression ratio compared to existing techniques.
- The compression process results in minimal signal loss.
- Simulations confirm that the original ECG signal can be well recovered after decompression.
Conclusions:
- The novel wavelet packet-based compression method is effective for ECG signals.
- The approach offers a favorable balance between compression efficiency and signal integrity.
- This technique holds promise for practical applications in medical data management.
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