Design and Development of Biomimetic Hand: Integrating Biological Principles for Enhanced Dexterity and Natural Functionality

Dear Colleagues,

Humanoid robots and prosthetic hands aim to mimic a variety of human-like behaviors, such as moving, grasping, lifting, and more. In recent decades, researchers have attempted to build humanoid robots and prosthetic hands capable of replacing human hands. However, despite prosthetics being a means of improving disability, activity difficulties, and health-related quality of life, many arm amputees rely on outdated devices.

Researchers need more diverse methods based on the collection and processing of biological signals to recreate all the different functions of the human hand, as it remains a challenge because of its complexity. Advances in neural signal acquisition, computer decoding and encoding methods of neural/biological signals, robotics for robotic hands, and computer vision using deep learning are relevant. These areas have the potential to provide standards to support robotic/prosthetic hand strategies.

There are several requirements in this area. One of the basic requirements is that the design should be as close as possible to replacing the natural hand. Another requirement is that, if used in prosthetics, the alternative control method should be flexible, such as muscles that can collect and process biological signals. A further requirement are innovative applications with new technologies, such as deep learning, IoT, and 5G.

We invite investigators to contribute original research articles and review articles addressing robotic/prosthetic hands that facilitate advances in rehabilitation/humanoids, such as brain–machine interfaces, neuroprosthetics, rehabilitation robots, humanoids, and human support robots.

Prof. Dr. Duk Shin
Guest Editor

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• new design as close as possible to the natural hand
• control methods for motor or sensory function
• neuroprosthetics and rehabilitation systems
• engineering technologies for humanoids
• personalized rehabilitation interfaces for adapted physical activity
• new sensors and actuator techniques