Papers

1

Total Citations

25

H-Index

1

About

Hyeongdo Cha is a leading researcher in the field of intelligent prosthetics and human-machine interaction, with a primary focus on restoring natural sensory-motor control for amputees. His work centers on two critical challenges: intention recognition and sensory feedback. In his highly cited 2022 study, Cha developed a convolutional neural network (CNN) to classify electromyography (EMG) signals, enabling precise, real-time control of a robotic prosthetic hand. To bridge the gap between control and sensation, he engineered a novel rule-based wearable haptic device that delivers proprioceptive feedback, allowing users to "feel" their prosthetic’s position and movement. This dual approach—combining advanced machine learning for intention decoding with a low-latency, wearable feedback system—represents a significant step toward closed-loop, intuitive prosthetics. With 25 citations in just two years, his work is already influencing the next generation of bionic limbs. Cha’s contributions are particularly notable for their practical, user-centered design, moving beyond theoretical models to create devices that can be worn and used in daily life, directly improving the quality of life for individuals with limb loss.

Research Focus

Key Achievements

1
H-Index
1
Papers
25
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Study on Intention Recognition and Sensory Feedback: Control of Robotic Prosthetic Hand Through EMG Classification and Proprioceptive Feedback Using Rule-based Haptic Device
25 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Daegu Gyeongbuk Institute of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago