Zaw Lay Htoon
Papers
2
Total Citations
10
H-Index
2
About
Zaw Lay Htoon’s research lies at the intersection of rehabilitation robotics and neuromuscular assessment, with a focused expertise in quantifying upper limb muscle tone and impedance in post-stroke patients. His major contributions center on developing objective, data-driven methods to replace subjective manual evaluations used by occupational and physical therapists. In his 2016 work, “Assessment of upper limb muscle tone level based on estimated impedance parameters,” he pioneered a technique to continuously measure recovery progress, addressing a critical gap in traditional therapy. Complementing this, his study “Estimation of Upper Limb Impedance Parameters Using Recursive Least Square Estimator” introduced a real-time computational framework for estimating human arm impedance—a parameter therapists rely on but struggle to quantify. Though each paper has garnered 5 citations, their impact is notable for laying foundational algorithms that could enhance robot-assisted rehabilitation, enabling more personalized and adaptive therapy. Htoon’s work bridges engineering and clinical practice, offering a pathway toward smarter, feedback-driven neurorehabilitation tools that empower both clinicians and patients in the recovery journey.
Research Focus
Key Achievements
Top Papers
- 1
- 2