A Novel Lossless ECG Compression Algorithm for Active Implants.

Area of Science:

• Biomedical Engineering
• Signal Processing
• Medical Informatics

Background:

• Effective data compression is crucial for implantable medical devices, particularly for continuous monitoring like electrocardiograms (ECGs).
• Existing algorithms may lack the necessary efficiency or low complexity for real-time processing within active implants.

Purpose of the Study:

• To propose and evaluate a novel, low-complexity, lossless ECG compression algorithm tailored for active implant applications.
• To assess the algorithm's compression ratio and fidelity using standard ECG datasets.

Main Methods:

• The algorithm employs adaptive length encoding, integrating linear prediction with delta encoding for ECG signal compression.
• Compression performance was evaluated on 48 segments of 30-minute ECG signals from the MIT-BIH Arrhythmia Database.

Main Results:

• The algorithm achieved an average compression rate of 2.43 with a data segment length of 33 and a predictor order of 2.
• No discernible difference was observed between the reconstructed and original ECG signals, confirming lossless compression.

Conclusions:

• The developed algorithm offers a high compression ratio while maintaining signal integrity, crucial for lossless ECG data.
• Its low computational complexity makes it highly suitable for resource-constrained active implantable medical devices for continuous ECG monitoring.