arXiv Computer Vision October 12, 2026 By Kuan-Yu Chen, Kuan-Chen Wang, Yu Tsao, Jian-Jiun Ding

ECGWmark: Deep Watermarking for Electrocardiogram Signals

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ECGWmark is a fully convolutional, quantization‑free deep watermarking framework designed for electrocardiogram (ECG) signals. It embeds patient metadata into ECGs while preserving high‑frequency diagnostic details by operating in a continuous latent space and using a localized frame‑level mechanism to resist severe temporal desynchronization. A differentiable Physiological Loss guided by a clinical classifier helps maintain diagnostic semantics, achieving over 90% channel‑bit extraction accuracy under circular phase shifts and demonstrating mixed effects on class‑level diagnostic metrics in the MIT‑BIH benchmark.

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