Zhishang Song
Papers
1
Total Citations
6
H-Index
1
About
Zhishang Song is a researcher in rehabilitation robotics and neural engineering, with a focus on developing assistive technologies for post-stroke recovery. His most cited work, "A Sitting Balance Training Robot for Trunk Rehabilitation of Acute and Subacute Stroke Patients" (2017), addresses a critical gap in early-stage rehabilitation by designing a robotic system that targets trunk stability and muscle activation. This study demonstrated the robot’s ability to safely engage core musculature, offering a novel approach to retraining postural control in patients with limited mobility. With 6 citations, the paper has informed subsequent work on robotic interventions for balance and trunk function. Song’s contributions lie at the intersection of mechanical design and clinical application, emphasizing practical, patient-centered solutions. His research holds promise for improving outcomes in acute and subacute stroke care, where early, targeted rehabilitation is key to long-term recovery.
Research Focus
Key Achievements
Top Papers
- 1