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arXiv Machine Learning By Guorui Lu, Xiaohui Cai, Todor Stefanov, Qinyu Chen

Vib2ECG: A Co-Located Chest-Lead SCG-ECG Dataset and Benchmark for ECG Reconstruction

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Vib2ECG introduces a new dataset of synchronized twelve‑lead ECG and chest‑wall vibration recordings collected at the six standard precordial sites (V1–V6) from 17 subjects, using inertial measurement units. The accompanying benchmark demonstrates that a lightweight 364K‑parameter U‑Net can reconstruct electrical cardiac signals at various locations from these low‑cost vibrational signals, though a hallucination effect—where ECG waveforms appear without corresponding electrical activity—was observed and analyzed. This work expands the use of cardiac vibrational signals for mobile ECG monitoring and offers insights into the spatial relationship between cardiac electrical and mechanical activities.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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