Rahman, Kazi Mohammad AbidurKazi Mohammad AbidurRahmanKhary, LutfiLutfiKharyKulau, UlfUlfKulau2026-09-162026-09-162026-0622nd Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2026https://hdl.handle.net/11420/64863We present the Discrete Wavelet Transform (DWT) as a zero-parameter front-end for near-sensor cardiac-interval estimation from Seismocardiography (SCG), preserving timing-critical structure under embedded constraints. Across 10 wavelet families, we benchmark reconstruction, peak-timing fidelity, and energy on an nRF52840 SoC, showing that energy scales with filter length, while signal fidelity depends on wavelet family. This yields an energy-fidelity Pareto frontier for principled wavelet selection, with ongoing work extending this representation into neural network pipelines for cardiac interval estimation with morphology-dependent inductive bias.encardiac interval estimationDWT-NN frontendSeismocardiography (SCG)wavelet benchmarkingTechnology::600: TechnologyConference Paper10.1109/DCOSS-IoT69657.2026.00066