The necessity of safeguarding electrocardiogram (ECG) streams has become essential in IoT-driven healthcare. However, the sensor nodes involved are operating under constrained power and memory budgets, necessitating cryptography that is both lightweight and robust. In response, this study introduces an encryption scheme that integrates controlled chaotic dynamics with the modest-footprint ASCON-1, thereby strengthening ECG telemetry without overtaxing constrained hardware. The cypher’s internal state is significantly less predictable and, as a result, more resistant to analytic enquiries due to the fact that a key schedule is refreshed on the fly: logistic-map permutations agitate the key space. Operationally, the raw ECG trace is initially normalised and quantized, and the linked data is subsequently processed by ASCON-1 to ensure integrity and confidentiality. Despite the fact that CPU cycles and memory footprints are modest, peak signal-to-noise ratios remain high, bit-error rates hover near zero, and correlations mirror the unencrypted baseline in bench experiments. Collectively, these characteristics indicate that the proposal has the potential to function as a practicable, forward-scalable safeguard for biomedical telemetry in contemporary e-health ecosystems, particularly for resource-limited IoT nodes.