Department of Computer Science, George Mason University, Fairfax, VA, 22030, USA.
Department of Bioengineering, George Mason University, Fairfax, VA, 22030, USA.
Sci Rep. 2019 Jul 1;9(1):9499. doi: 10.1038/s41598-019-45459-7.
Technological advances in multi-articulated prosthetic hands have outpaced the development of methods to intuitively control these devices. In fact, prosthetic users often cite "difficulty of use" as a key contributing factor for abandoning their prostheses. To overcome the limitations of the currently pervasive myoelectric control strategies, namely unintuitive proportional control of multiple degrees-of-freedom, we propose a novel approach: proprioceptive sonomyographic control. Unlike myoelectric control strategies which measure electrical activation of muscles and use the extracted signals to determine the velocity of an end-effector; our sonomyography-based strategy measures mechanical muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Therefore, our sonomyography-based control is congruent with a prosthetic user's innate proprioception of muscle deformation in the residual limb. In this work, we evaluated proprioceptive sonomyographic control with 5 prosthetic users and 5 able-bodied participants in a virtual target achievement and holding task for 5 different hand motions. We observed that with limited training, the performance of prosthetic users was comparable to that of able-bodied participants and thus conclude that proprioceptive sonomyographic control is a robust and intuitive prosthetic control strategy.
多关节假肢的技术进步已经超过了直观控制这些设备的方法的发展。事实上,假肢使用者经常将“使用困难”作为放弃假肢的一个关键因素。为了克服目前普遍存在的肌电控制策略的局限性,即对多个自由度的非直观比例控制,我们提出了一种新的方法:本体感受肌声图控制。与肌电控制策略不同,肌电控制策略测量肌肉的电激活,并使用提取的信号来确定末端执行器的速度;我们的基于肌声图的策略使用超声波直接测量机械肌肉变形,并使用提取的信号来对末端执行器的位置进行比例控制。因此,我们的基于肌声图的控制与假肢使用者对残肢肌肉变形的固有本体感觉相一致。在这项工作中,我们在虚拟目标实现和握持任务中,用 5 名假肢使用者和 5 名健全参与者评估了本体感受肌声图控制,用于 5 种不同的手部运动。我们观察到,经过有限的训练,假肢使用者的表现可与健全参与者相媲美,因此得出结论,本体感受肌声图控制是一种强大且直观的假肢控制策略。