首页> 外文期刊>Journal of NeuroEngineering Rehabilitation >Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand
【24h】

Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand

机译:探索多协同型软仿生手中的增强抓斗能力

获取原文
           

摘要

State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.e. postural synergies) in software and hardware architecture of artificial devices is opening new approaches for the design and control of upper-limb prostheses. Following these emerging principles, previous research on the SoftHand Pro, which embeds one physical synergy, showed promising results in terms of intuitiveness, robustness, and grasping performance. To explore these principles also in hands with augmented capabilities, this paper describes the SoftHand 2 Pro, a second generation of the device with 19 degrees-of-freedom and a second synergistic layer. After a description of the proposed device, the work explores a continuous switching control method based on a myoelectric pattern recognition classifier. The combined system was validated using standardized assessments with able-bodied and, for the first time, amputee subjects. Results show an average improvement of more than 30% of fine grasp capabilities and about 10% of hand function compared with the first generation SoftHand Pro. Encouraging results suggest how this approach could be a viable way towards the design of more natural, reliable, and intuitive dexterous hands.
机译:最先进的仿生手包含高科技设备,其尝试克服传统单个握把系统的限制。不幸的是,它们的复杂性通常会限制机械稳健性和直观的假体控制。最近,人工装置软件和硬件架构中的神经科学理论(即姿势协同效应)的翻译正在开辟了对上肢假体的设计和控制的新方法。在这些新兴原则之后,以前关于嵌入一个物理协同作用的Softhand Pro的研究表明,在直观,鲁棒性和掌握性能方面表现出有希望的结果。为了探索这些原则,也有通过增强能力,本文介绍了Softhand 2 Pro,第二代具有19度自由度和第二种协同层的装置。在所提出的设备的描述之后,该工作探讨了基于肌电图案识别分类器的连续交换控制方法。合并的系统使用具有能够体验的标准化评估进行验证,并且是第一次截肢者主题。结果显示,与第一代Softhand Pro相比,占精细掌握能力的30%以上的30%以上的30%,占手功能的约10%。令人鼓舞的结果表明,这种方法如何成为设计更自然,可靠和直观的手动设计的可行方式。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号