Optimal ECG Signal Denoising Using DWT with Enhanced African Vulture Optimization

Cardiovascular diseases (CVDs) are the world's leading cause of death; therefore cardiac health human heart has been a fascinating topic for decades. The electrocardiogram (ECG) signal is comprehensive non-invasive method determining health. Various practitioners use ECG to ascertain critical information about heart. In this paper, noisy denoised based on Discrete Wavelet Transform (DWT) optimized with Enhanced African Vulture Optimization (AVO) algorithm and adaptive switching mean filter (ASMF) proposed. Initially, input signals obtained from MIT-BIH ARR dataset white Gaussian noise added signals. Then corrupted using in which threshold an obtain optimum threshold. AVO enhanced by Whale Algorithm (WOA). Additionally, ASMF tuned algorithm. experiments conducted proposed built EAVO algorithm, attains significant enhancement reliable parameters, according testing results terms SNR, difference (MD), square error (MSE), normalized root squared (NRMSE), peak reconstruction (PRE), maximum (ME), (NRME) existing algorithms namely, PSO, AOA, MVO, etc.