Papers
2
Total Citations
5
H-Index
2
About
Yoha Hwang is a researcher focused on advancing rehabilitation robotics through intuitive human-robot interaction, particularly for individuals with neurological impairments. Their key research areas include intent recognition using electromyogram (EMG) signals, gait rehabilitation, and assistive robotic control for lower-limb mobility. Hwang’s major contributions center on developing methods to decode user movement intentions from muscle activity, enabling robots to respond naturally to patients’ needs. In their 2017 study on walking speed intention, they demonstrated how soleus EMG signals from both nondisabled and post-stroke hemiparetic patients could predict gait speed, paving the way for patient-driven robotic gait training. Their 2015 work on sit-to-stand and stand-to-sit transitions introduced a novel framework using just two EMG channels and linear discriminant analysis, achieving efficient classification for overground rehabilitation robots. While citation counts for these papers are modest (3 and 2 respectively), the work represents foundational steps in creating more responsive, user-centered rehabilitation technologies. Hwang’s focus on practical, low-channel EMG solutions highlights a commitment to accessible, real-world applications that empower patients to actively participate in their recovery.
Research Focus
Key Achievements
Top Papers
- 1
- 2