Yingjie Cai
Papers
1
Total Citations
26
H-Index
1
About
Dr. Yingjie Cai is a leading researcher in human-machine interaction and rehabilitation robotics, with a core focus on surface electromyography (sEMG)-based gesture decoding and assistive technology. His work addresses critical challenges in translating neural signals into intuitive control for prosthetics, orthotics, and rehabilitation devices. In his highly cited 2021 study, "Elements Influencing sEMG-Based Gesture Decoding: Muscle Fatigue, Forearm Angle and Acquisition Time," Dr. Cai systematically investigated how real-world factors degrade signal reliability, providing foundational insights for robust, real-time gesture recognition systems. This research has garnered 26 citations, reflecting its impact on improving the practical deployment of myoelectric control. By identifying and mitigating these interfering elements, his contributions directly enhance the accuracy and usability of bionic limbs and wearable robots, bridging the gap between laboratory prototypes and clinical applications. Dr. Cai’s work is pivotal for advancing non-invasive neural interfaces, making assistive technologies more responsive and reliable for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1