Department of Computer Science and Automation, Indian Institute of Science, Bengaluru, India
Abstract
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).
Keshani,P . (2025). ECG Signal Compression in Wireless Body Area Networks Using the Bat Algorithm. Transactions on Machine Intelligence, 8(3), 141-150.
MLA
Keshani,P . "ECG Signal Compression in Wireless Body Area Networks Using the Bat Algorithm", Transactions on Machine Intelligence, 8, 3, 2025, 141-150.
HARVARD
Keshani P. (2025). 'ECG Signal Compression in Wireless Body Area Networks Using the Bat Algorithm', Transactions on Machine Intelligence, 8(3), pp. 141-150.
CHICAGO
P Keshani, "ECG Signal Compression in Wireless Body Area Networks Using the Bat Algorithm," Transactions on Machine Intelligence, 8 3 (2025): 141-150,
VANCOUVER
Keshani P. ECG Signal Compression in Wireless Body Area Networks Using the Bat Algorithm. Trans. Mach. Intell.. 2025;8(3):141-150.
