ECG Data Compression Analysis by Employing Different Transforms in Orthogonal Transformation Technique

Using the orthogonal transformation method, this paper presents the performance analysis of FFT, DHT, DCT, and DST for ECG data compression. When the heart muscle contracts or expands as a response to the command signals coming from electrical stimulus in its electro-conduction system, an ECG signal is generated. In today's fast-paced life, ECG data compression is essential as today's lifestyle leads to many health problems. More storage space is required for research purposes or data transmission, and data compression utilizes memory storage effectively. The performance of each transform has been recorded by calculating compression ratio (CR) to measure the compression acquired, signal-to-noise ratio (SNR) to measure signal strength to the background noise, and percent rms difference (PRD) for error measurement. The parameters have been measured using Python and has been compared with the literature. The Discrete Cosine transform performed well compared to the rest in the orthogonal transformation method with a PRD of 4.80 at CR of 5.14 and an SNR of 26.36.