Current research is aimed at providing technology that will improve the limb functions of individuals with limb deficiencies. Its focus is on the design, development, and use of state-of-the-art prosthetic hands that are controlled by muscle signals (specifically myoelectric signals) from the user's residual limb. With the use of electromyography (sEMG) sensors, this new concept hand transforms the muscle into a sense, providing the user with a natural and responsive movement experience. The report discusses the integration of biomechanics, signal processing, and robotics to achieve artificial and flexible devices. By combining these disciplines, the model not only restores limb function but also provides mobility and efficiency in use. Key points of this advancement include the integration of in situ electromyography sensors to capture and interpret electromyographic signals, the highest performance signal converting this into useful commands for prosthetic hands, and robotic engineering to convert these commands into signals clear, natural movement.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Design of Myoelectric Hand Controlled by Muscle Bulge for the Amputees

  • Ch. Gayatri,
  • Sarvani Aripirala,
  • P. Terisa,
  • T. Sai Venkat Sujith,
  • D. Satya Durga Avinash,
  • N. Narendra

摘要

Current research is aimed at providing technology that will improve the limb functions of individuals with limb deficiencies. Its focus is on the design, development, and use of state-of-the-art prosthetic hands that are controlled by muscle signals (specifically myoelectric signals) from the user's residual limb. With the use of electromyography (sEMG) sensors, this new concept hand transforms the muscle into a sense, providing the user with a natural and responsive movement experience. The report discusses the integration of biomechanics, signal processing, and robotics to achieve artificial and flexible devices. By combining these disciplines, the model not only restores limb function but also provides mobility and efficiency in use. Key points of this advancement include the integration of in situ electromyography sensors to capture and interpret electromyographic signals, the highest performance signal converting this into useful commands for prosthetic hands, and robotic engineering to convert these commands into signals clear, natural movement.