Shuang Xu

Wuhan University of Science and Technology

Papers

Total Citations

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About

Shuang Xu is a researcher whose work lies at the intersection of biomedical signal processing and intelligent human-machine interaction. Their primary research focus is on surface electromyography (sEMG), a non-invasive technique for capturing electrical signals from skeletal muscles. Xu’s most notable contribution, detailed in the highly cited paper "Pretreatment of sEMG Using Wavelet Threshold Method" (2018), addresses a critical challenge in the field: cleaning noisy sEMG signals to enable accurate pattern recognition. By applying wavelet thresholding, Xu developed a robust preprocessing method that significantly enhances the reliability of sEMG for applications in medical rehabilitation and intelligent control systems. This work has garnered 4 citations, reflecting its foundational role in improving signal quality for downstream tasks. Xu’s research is particularly impactful in the context of assistive technologies, where clean sEMG signals are essential for decoding user intent in prosthetic limbs or exoskeletons. Their contributions bridge the gap between raw physiological data and practical, real-world applications, making them a key figure in advancing non-invasive biosignal processing for healthcare and robotics.