Budi Liswanto
Papers
1
Total Citations
2
H-Index
1
About
Budi Liswanto is a researcher at the forefront of assistive robotics and neural signal processing, with a focused expertise in brain-computer interfaces (BCI) for prosthetic control. His most cited work, "Brain-Computer Interface based on Neural Network with Dynamically Evolved for Hand Movement Classification" (2022), addresses the critical challenge of translating neural commands into precise prosthetic actions. Liswanto’s major contribution lies in developing a dynamically evolved neural network framework that classifies hand movements from brain signals, enabling prosthetic robots to respond as natural extensions of the human body. This innovation is designed to empower individuals with disabilities by creating intuitive, signal-driven control systems that predict desired movements in real time. Although his citation count is currently modest—with 2 citations on his leading paper—his work represents a foundational step toward seamless human-robot integration. By focusing on the intersection of adaptive neural networks and assistive technology, Liswanto is advancing the field of rehabilitation robotics, offering a promising pathway for more responsive and personalized prosthetic devices that improve quality of life.
Research Focus
Key Achievements
Top Papers
- 1