Transactions on Machine Intelligence 2821-1693 8 3 2025 09 01 ECG Signal Compression in Wireless Body Area Networks Using the Bat Algorithm 141 150 244862 10.22034/tmi.2025.244862 EN P. Keshani Department of Computer Science and Automation, Indian Institute of Science, Bengaluru, India Journal Article 2025 06 04 In this research, a novel method for Electrocardiogram (ECG) signal compression is proposed based on the Discrete Wavelet Transform (DWT) and the Bat Algorithm. In this approach, the raw signal is transformed into the wavelet domain, where the Bat Algorithm is employed to select the optimal wavelet coefficients by maximizing the Peak Signal-to-Noise Ratio (PSNR) metric. The selected coefficients capture the primary information of the signal, while the remaining coefficients are discarded to achieve a high compression ratio while maintaining reconstruction quality. Performance evaluations conducted on the MIT-BIH database demonstrate that the proposed method exhibits a distinct superiority in terms of PSNR compared to conventional techniques. The results indicate that this method can serve as an effective, low-power solution for real-time ECG signal compression in Wireless Body Area Networks (WBANs).