Max Robotics — Global Service Robot Directory + US Certification

About

Dan Guo is a leading researcher at the intersection of flexible electronics and intelligent rehabilitation robotics. His work bridges two transformative fields: stretchable electromechanical sensors for wearable health monitoring and AI-driven robotic systems for motor rehabilitation. Guo’s most impactful contribution is the development of a solution-processed MoS₂ strain sensor (2019, 46 citations), which achieves ultrahigh sensitivity and a large detection range for skin-on monitoring—a breakthrough that overcomes the limitations of traditional two-dimensional materials in electromechanical sensing. In parallel, he has pioneered AI-enhanced rehabilitation technologies, including an LSTM-based method for predicting lower limb intention from Kinect visual signals (2020, 22 citations) and an intelligent PID controller integrated with RBF neural networks for assistive robotics (2022, 25 citations). His recent work on compact end-effector ankle rehabilitation robots (2024) demonstrates a practical, bilaterally symmetrical design with three degrees of freedom, addressing critical needs in post-stroke gait recovery. With a growing citation record and a clear trajectory from fundamental materials science to applied robotic systems, Guo’s research offers a compelling model for integrating soft sensing and intelligent control in next-generation healthcare technologies.