Xiaoqiang Lu

Xi'an Institute of Optics and Precision Mechanics

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About

Xiaoqiang Lu is a leading researcher in biomedical signal processing and intelligent control systems, with a focus on robust pattern recognition for human-machine interfaces. His major contributions center on advancing myoelectric control technologies, particularly addressing the critical challenge of noise interference in long-term electromyogram (EMG) recordings. In his highly cited 2018 work (46 citations), Lu pioneered a robust sparse representation-based pattern recognition approach that effectively mitigates white Gaussian noise—a persistent obstacle in practical EMG-driven control systems. This innovation significantly enhances the reliability of prosthetic and assistive devices under real-world conditions. Lu has also explored multi-spectral pedestrian detection (2014, 22 citations), demonstrating his versatility in applying signal processing techniques across domains. His research bridges the gap between theoretical signal denoising methods and practical deployment in healthcare and robotics, earning recognition for improving the robustness of bioelectric control systems. Through his work, Lu continues to push the boundaries of how noisy biological signals can be harnessed for precise, real-time control applications.