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Accurate low-frequency response in digital electrocardiogram (ECG) systems is critical for preserving ST-segment morphology and ensuring diagnostic fidelity in ischemia detection. This study validates the low-frequency performance of SydäntekTM, a wearable 12-lead ECG platform, using impulse-based protocols aligned with IEC 60601-2-25 standards. Synthetic 3 mV square wave-forms with 100 ms isoelectric segments were injected to simulate baseline drift and assess high-pass filter behavior near the 0.67 Hz cutoff. Forward–reverse finite impulse response (FIR) convolution and filtfilt-based processing ensured zero-phase distortion and amplitude preservation. Hardware calibration employed WhaleTeq modules generating programmable impulses and sinusoidal drifts, confirming analog-to-digital fidelity across physiologic bradycardia thresholds. Real-world validation was conducted using 79 annotated records from the European ST-T Database from Physionet, encompassing both ST elevation and depression events. The SydäntekTM system consistently preserved ST-segment morphology across heart rate bins, maintaining a bias of less than 5 µV at J+40, J+60, and J+80 ms intervals. Among these, J-point anchoring at J+60 ms demonstrated the strongest correlation with reference annotations in the ST-T Database. Of note, J+60 aligns with published literature identifying it as a sensitive and specific marker for subendocardial ischemia. Artifact suppression in lead V2 was achieved using adaptive Wiener filtering, which effectively minimized motion-induced distortion while preserving low-amplitude ST features critical for diagnostic fidelity. Digitization fidelity was confirmed through direct waveform analysis, demonstrating consistent temporal precision and preservation of ST-segment morphology. The platform adheres to key performance criteria outlined in IEC 60601-2-25, -2-27, and -2-47, supporting its suitability for deployment in resting, monitoring, and ambulatory ECG contexts. These findings position SydäntekTM as a clinically capable solution for low-frequency ECG acquisition, with relevance to infarct detection, pericarditis, and myocardial disease screening. The methodology provides a reproducible framework for waveform validation, morphology-aware signal processing, and alignment with regulatory expectations in next-generation cardiac diagnostics. Received: 23 October 2025 | Revised: 2 December 2025 | Accepted: 22 December 2025 Conflicts of Interest Dr Sugandhi Gopal, the principal investigator served as both system designer and study director; this dual role is disclosed, governance measures minimized bias, and all underlying data are available for review to ensure transparency and reproducibility. The investigator’s primary professional role is as an interventional cardiologist, with research activities conducted in alignment with that clinical focus. Mr Mohith Subramanian, Vishwateja Reddy, and Ms Poulami Roy Engineers, are involved in this project and are affiliated with Carditek Medical Devices in roles specific to signal processing, algorithm development. Their contribution was technical in nature and did not influence the study’s clinical design or data interpretation. Shasha Jumbe also declares no conflict of interest. All contributors affirm adherence to ethical research practices, and confirm that their roles did not introduce bias or commercial influence into the study’s execution or reporting. Data Availability Statement Data are available from the corresponding author upon reasonable request. Author Contribution Statement Sugandhi Gopal: Conceptualization, Methodology, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Prabhavathi Bhat: Validation. Shasha Jumbe: Validation. Mohith Subramanian: Methodology, Software, Formal analysis, Writing – review & editing. Vishwateja Reddy: Methodology, Software, Formal analysis, Investigation, Data curation. Poulami Roy: Methodology, Software, Formal analysis, Investigation, Data curation.