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A step-by-step approach for perfecting intelligent myoelectric controller algorithms

机译:完善智能磁电控制器算法的逐步方法

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The evolution of the intelligent algorithm that is capable of preferentially reallocating the action selection times in a myoelectric controller for multiple degree of freedom prosthesis, is the theme of this paper. Here thirteen algorithms, their advantages and disadvantages are discussed and the reasons for modifying them leads us to improved versions of the algorithms, which takes us closer to the ideal algorithm for intelligent myoelectric controllers. The need for self preferential time allocation arises because of two prime reasons. Firstly, the programmer of the myoelectric controller is not going to be around while the user uses the prosthesis and hence will not be able to reprogram the device. Secondly, application specific myoelectric controllers cannot be manufactured for every customer in reality. The embedded intelligence allocates the least time to those actions that are performed the most number of times. This is done with a combination of spatial and temporal coding, so that temporal priorities can be reassigned preferentially to spatially coded signals. By using intelligence embedded algorithms in the place of the existing ones which have to be allocated the action selection pulse times beforehand, we eliminate the need for individually programmed myoelectric controllers.
机译:能够优先重新分配在多重自由假体的肌电控制器中的动作选择时间的智能算法的演变是本文的主题。这里讨论了13个算法,它们的优点和缺点以及修改它们的原因导致我们改进了算法的改进版本,这使我们更接近智能磁电控制器的理想算法。由于两个主要原因,因此出现了对自我优先时间分配的需求。首先,在用户使用假肢的同时,肌电控制器的程序员不会在围绕,因此将无法重新编程设备。其次,可以为每个客户实际制造应用特定的肌电控制器。嵌入式智能将最少的时间分配给执行最多次数的那些操作。这是用空间和时间编码的组合完成的,从而可以优先地重新分配到空间编码信号的时间优先级。通过使用智能嵌入算法以前必须预先分配动作选择脉冲时间的现有算法,我们消除了对单独编程的肌电控制器的需求。

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