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About

Xiangzhi Liu is advancing the frontier of wearable sensing systems for human motion analysis, clinical rehabilitation, and human–robot interaction. His research centers on developing flexible, multi-sensor platforms that combine magnetic–inertial measurement units (MIMUs) with novel algorithms to overcome the limitations of traditional motion capture—such as magnetic disturbance, sensor rigidity, and restricted measurement points. Among his most impactful contributions is a flexible sensor and MIMU-based wearable system for human motion analysis (20 citations), alongside an automatic assessment framework for Parkinsonian gait that enables objective, real-time evaluation of motor symptoms in assistive technologies. Liu has also pioneered a potential-real-time thigh orientation prediction method using only two shank-mounted IMUs (14 citations), significantly reducing sensor burden while maintaining clinical accuracy. His work extends to robust muscle activity monitoring and indirect foot posture measurement for rehabilitation robots. With multiple papers published in 2022–2025 and growing citation impact, Liu is shaping the next generation of unobtrusive, intelligent wearables that bridge sensing, biomechanics, and robotics—offering practical solutions for patient diagnosis, rehabilitation, and human–machine collaboration.