Xiaonan Huang

University of Shanghai for Science and Technology

Papers

1

Total Citations

3

H-Index

1

About

Xiaonan Huang is an emerging clinical researcher whose work sits at the intersection of critical care medicine and rehabilitation technology. Huang's primary research focus centers on intensive care unit-acquired weakness (ICUAW), a debilitating complication affecting critically ill patients that has historically lacked standardized diagnostic and therapeutic protocols. Their most notable contribution to date is a pioneering study protocol investigating the early efficacy of suspended lower-limb rehabilitation robots as an assistive therapy for ICUAW patients — a novel approach that bridges advanced robotics with early mobilization strategies in intensive care settings. This work addresses a significant gap in critical care rehabilitation, where definitive treatment strategies have remained elusive despite growing clinical awareness of the condition. By designing a self-controlled randomized controlled trial framework, Huang demonstrates a rigorous methodological approach to evaluating emerging rehabilitation technologies in vulnerable patient populations. Though early in their citation trajectory with 3 citations accumulated since 2025, Huang's research represents an important and timely contribution to improving functional recovery outcomes for critically ill patients, positioning them as a researcher to watch in the rapidly evolving field of ICU rehabilitation medicine.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Early efficacy observation of suspended lower-limb rehabilitation robot-assisted therapy in patients with intensive care unit-acquired weakness: a study protocol for a self-controlled randomised controlled trial
3 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: University of Shanghai for Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago