Myoelectric control of a computer animated hand: A new concept based on the combined use of a tree-structured artificial neural network and a data glove
Myoelectric control of a computer animated hand: A new concept based on the combined use of a tree-structured artificial neural network and a data glove
复制标题
DOI：
10.1080/03091900512331332546
复制
发表时间：
2006-01-01
影响因子：
--
通讯作者：
Laurell, T.
中科院分区：
文献类型：
--
作者：
Sebelius, F.;Eriksson, L.;Laurell, T.
本文提出了一种多功能手假体控制系统的新学习装置。两名单手创伤性截肢的男性受试者用健康手和幻手同时进行对称运动。健康手上的数据手套被用作训练系统执行自然动作的参考。代替具有有限自由度的物理假体，虚拟（计算机动画）手被用作目标工具。两名受试者都成功地用手指和手腕完成了七种不同的运动动作。为了减少系统的训练时间，设计了树形自组织人工神经网络。对于所使用的任何配置，训练时间都不会超过30秒，这比目前使用的大多数人工神经网络（ANN）架构快三到四倍。
This paper proposes a new learning set-up in the field of control systems for multifunctional hand prostheses. Two male subjects with a traumatic one-hand amputation performed simultaneous symmetric movements with the healthy and the phantom hand. A data glove on the healthy hand was used as a reference to train the system to perform natural movements. Instead of a physical prosthesis with limited degrees of freedom, a virtual (computer-animated) hand was used as the target tool. Both subjects successfully performed seven different motoric actions with the fingers and wrist. To reduce the training time for the system, a tree-structured, self-organizing, artificial neural network was designed. The training time never exceeded 30 seconds for any of the configurations used, which is three to four times faster than most currently used artificial neural network ( ANN) architectures.