Liangnan Hu

Papers

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About

Liangnan Hu is a researcher at the intersection of artificial intelligence, robotics, and human motion analysis, with a primary focus on developing intelligent systems for sports training and rehabilitation. His most notable work, "Application of gaming robot based on gait recognition algorithm in sports training and assistance system" (2024), has garnered 3 citations and introduces a novel framework that integrates gait recognition algorithms with interactive gaming robots to enhance athletic performance and provide real-time assistance. This contribution bridges the gap between computer vision, biomechanics, and human-robot interaction, offering a practical tool for coaches and therapists to monitor and correct movement patterns dynamically. Hu’s research has significant implications for personalized sports training, injury prevention, and assistive technologies, demonstrating how AI-driven robotics can transform traditional coaching methods. By combining robust algorithmic design with user-centered applications, he advances the field of embodied AI, making complex motion analysis accessible and engaging for both athletes and rehabilitation patients. His work stands as a promising step toward more adaptive, responsive training systems that leverage real-time data to optimize human performance.