HEART: A High-Efficiency Adaptive Real-Time Telemonitoring Framework for Secure Electrocardiogram Signal Transmission Using Chaotic Encryption

Abstract

The real-time analysis and secure transmission of electrocardiogram (ECG) signals are critical for accurate diagnosis and safeguarding patient privacy in telemedicine applications. This study presents a novel real-time ECG monitoring system that employs a learnable key generator (LKG) derived from each patient’s own ECG signal characteristics to dynamically produce unique encryption keys. These keys determine the parameters r and x0 of a logistic map used for chaotic encryption. The system securely encrypts real-time ECG data immediately after acquisition, ensuring confidential transmission and storage in the cloud. For remote clinical access, the encrypted data is downloaded and decrypted on the doctor’s side using the matching key generated at the source or securely stored in the cloud. This approach eliminates the need for traditional key exchange and substantially raises the cost of exhaustive key search in practice through per-segment biometric key refresh and combined permutation + XOR diffusion, supported by min-entropy evaluation. Compared to static-key methods, the learnable biometric key design offers greater unpredictability and individualization. A comprehensive set of security assessments including Shannon entropy (7.6–7.8 bits), correlation and autocorrelation disruption, histogram statistics, National Institute of Standards and Technology (NIST) SP 800-22 frequency testing, plaintext/key sensitivity (avalanche effect), fast Fourier transform (FFT)-based spectral flatness, and robustness to noise and occlusion confirms the method’s strength. Reconstruction fidelity (MSE ≈ 5*10^-6, PSNR > 52dB, MAE ≈ 0.002) demonstrates near-lossless decryption and preserved diagnostic features. Encryption latency remains low, preserving real-time performance. The system also supports seamless integration with a neural-network-based disease detection module operating on encrypted data. Overall, the proposed architecture provides a secure, scalable, and real-time framework for remote cardiac monitoring and highlights a promising direction for privacy-preserving biomedical signal processing. Detailed security results are provided in security results analysis, and all source code, test scripts, and processed datasets are openly released to ensure reproducibility.

Cite this article as: B. B. Yüksel and A. Yılmazer-Metin, "HEART: A high-efficiency adaptive real-time telemonitoring framework for secure ECG signal transmission using chaotic encryption," Electrica, 2026, 26, 0232, doi: 10.5152/electrica.2026.25232.