Peng Suo

Papers

Total Citations

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About

Peng Suo is a researcher in rehabilitation robotics and sensor-based human-machine interaction, with a focus on developing intelligent training methods for motor recovery. Their most-cited work, "A Training Method for a Sensor-Based Exercise Rehabilitation Robot" (2022), addresses critical limitations in traditional mirror therapy by integrating real-time sensor feedback to enhance the rehabilitation of affected limbs. This system enables active, mirror-based training that adapts to patient progress, improving both engagement and therapeutic outcomes. With 4 citations, this paper has already garnered attention in the growing field of assistive robotics. Suo’s contributions lie at the intersection of biomedical engineering and interactive robotics, where they design systems that combine motion sensing, real-time data processing, and patient-centered control. Their work holds promise for advancing personalized rehabilitation, particularly for stroke and injury recovery. By bridging sensor technology with clinical practice, Peng Suo is helping to shape the next generation of smart, responsive rehabilitation tools that empower patients and clinicians alike.