Klyde Penan
Papers
1
Total Citations
7
H-Index
1
About
Klyde Penan is a rising researcher in the fields of biomedical engineering and human-machine interaction, with a focus on myoelectric control systems and biomimetic robotics. His most cited work, "Myoelectric Control of a Biomimetic Robotic Hand Using Deep Learning Artificial Neural Network for Gesture Classification" (2022, 7 citations), introduces a novel control system that employs a deep learning algorithm to translate muscle signals into precise hand gestures. By integrating five servo motors to achieve 17 degrees of freedom in a 3D-printed robotic hand, Penan demonstrates a scalable, low-cost approach to prosthetic design. This contribution bridges artificial intelligence and rehabilitation technology, offering a pathway toward more intuitive and adaptive assistive devices. While his citation count is still growing, Penan’s work has already garnered attention for its practical application of deep neural networks in real-time gesture classification, marking him as an innovator in accessible robotic prosthetics. His research holds promise for advancing the quality of life for amputees and individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1