H. Niu

Papers

Total Citations

H-Index

About

H. Niu is a researcher whose work sits at the intersection of biomedical signal processing, human–machine interaction, and rehabilitation engineering. Their most-cited paper, “Continuous Gesture Recognition and Force Estimation Using sEMG Signal” (2023, 9 citations), exemplifies their focus on harnessing surface electromyography (sEMG) signals—rich physiological data that reflect motor intention—to enable intuitive control of robotic and assistive devices. Niu’s major contribution lies in advancing continuous, real-time gesture recognition and force estimation, moving beyond discrete classification to capture the nuanced, dynamic nature of human movement. This work has direct implications for improving prosthetic control, rehabilitation robotics, and human–computer interfaces. While their citation count is still growing, the foundational nature of their research signals strong potential for future impact. By addressing the gap between raw biological signals and practical, responsive systems, Niu is helping to build a bridge between human physiology and machine intelligence—an effort that promises to make assistive technologies more natural, responsive, and effective for users in clinical and everyday settings.