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A comparison of the real-time controllability of pattern recognition to conventional myoelectric control for discrete and simultaneous movements

机译:模式识别的实时可控性与常规肌电控制的离散和同时运动比较

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摘要

Myoelectric control has been used for decades to control powered upper limb prostheses. Conventional, amplitude-based control has been employed to control a single prosthesis degree of freedom (DOF) such as closing and opening of the hand. Within the last decade, new and advanced arm and hand prostheses have been constructed that are capable of actuating numerous DOFs. Pattern recognition control has been proposed to control a greater number of DOFs than conventional control, but has traditionally been limited to sequentially controlling DOFs one at a time. However, able-bodied individuals use multiple DOFs simultaneously, and it may be beneficial to provide amputees the ability to perform simultaneous movements. In this study, four amputees who had undergone targeted motor reinnervation (TMR) surgery with previous training using myoelectric prostheses were configured to use three control strategies: 1) conventional amplitude-based myoelectric control, 2) sequential (one-DOF) pattern recognition control, 3) simultaneous pattern recognition control. Simultaneous pattern recognition was enabled by having amputees train each simultaneous movement as a separate motion class. For tasks that required control over just one DOF, sequential pattern recognition based control performed the best with the lowest average completion times, completion rates and length error. For tasks that required control over 2 DOFs, the simultaneous pattern recognition controller performed the best with the lowest average completion times, completion rates and length error compared to the other control strategies. In the two strategies in which users could employ simultaneous movements (conventional and simultaneous pattern recognition), amputees chose to use simultaneous movements 78% of the time with simultaneous pattern recognition and 64% of the time with conventional control for tasks that required two DOF motions to reach the target. These results suggest that when amputees are given the ability to control multiple DOFs simultaneously, they choose to perform tasks that utilize multiple DOFs with simultaneous movements. Additionally, they were able to perform these tasks with higher performance (faster speed, lower length error and higher completion rates) without losing substantial performance in 1 DOF tasks.
机译:肌电控制已用于控制动力上肢假体数十年。传统的基于幅度的控制已被用于控制单个假体的自由度(DOF),例如手的闭合和张开。在过去的十年中,已经构造了能够驱动众多自由度的新型和先进的手臂和手部假肢。已经提出了模式识别控制来控制比传统控制更多的自由度,但是传统上已经被限制为一次顺序地控制一个自由度。但是,身体健全的人会同时使用多个自由度,因此,为截肢者提供同时进行运动的能力可能会有所帮助。在这项研究中,四个接受过肌电假体训练并经过定向运动神经支配(TMR)手术的截肢者被配置为使用三种控制策略:1)传统的基于幅度的肌电控制; 2)顺序(一自由度)模式识别控制,3)同时模式识别控制。通过让截肢者将每个同时运动作为单独的运动类别进行训练,可以实现同时模式识别。对于只需要控制一个自由度的任务,基于顺序模式识别的控制以最低的平均完成时间,最低的完成率和长度误差表现最佳。对于需要控制2个自由度的任务,与其他控制策略相比,同时模式识别控制器以最低的平均完成时间,完成率和长度误差表现最佳。在用户可以采用同时动作(常规和同时模式识别)的两种策略中,截肢者选择在需要两次DOF动作的任务中,同时使用78%的时间同时进行模式识别和64%的时间进行常规控制时使用同时移动达到目标。这些结果表明,当截肢者被赋予同时控制多个自由度的能力时,他们选择执行同时利用多个自由度的任务。此外,他们能够以更高的性能(更快的速度,更低的长度错误和更高的完成率)执行这些任务,而不会在1个DOF任务中失去实质性的性能。

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