"An sEMG Denoising Method Based on Efficient VMD and Adaptive Cross-Correlation Reconstruction"

"This dataset is a specialized experimental resource tailored for analog signal denoising research and surface electromyography (sEMG) signal analysis, comprising 5 groups of well-structured experimental data. These include threshold experiments to explore the impact of denoising thresholds on signal fidelity, ablation experiments to validate the necessity and contribution of each algorithm module, denoising results of three distinct algorithm models for horizontal performance comparison, sEMG sampling data from 6 subjects covering diverse physiological states, and analog signal denoising analysis to test algorithm robustness under controlled noise conditions. It spans multiple experimental paradigms from basic parameter exploration to real-scenario validation and covers both analog and physiological signal types, serving as a standardized benchmark for evaluating analog signal denoising algorithms and supporting in-depth research on sEMG signals, algorithm performance verification, and biomedical signal processing analysis."