Hunt Grace, Hood Sarah, Lenzi Tommaso
Department of Mechanical Engineering and Utah Robotics CenterUniversity of Utah Salt Lake City UT 84112 USA.
IEEE Open J Eng Med Biol. 2021 Aug 11;2:267-277. doi: 10.1109/OJEMB.2021.3104261. eCollection 2021.
Emerging robotic knee and ankle prostheses present an opportunity to restore the biomechanical function of missing biological legs, which is not possible with conventional passive prostheses. However, challenges in coordinating the robotic prosthesis movements with the user's neuromuscular system and transitioning between activities limit the real-world viability of these devices. Here we show that a shared neural control approach combining neural signals from the user's residual limb with robot control improves functional mobility in individuals with above-knee amputation. The proposed shared neural controller enables subjects to stand up and sit down under a variety of conditions, squat, lunge, walk, and seamlessly transition between activities without explicit classification of the intended movement. No other available technology can enable individuals with above-knee amputations to achieve this level of mobility. Further, we show that compared to using a conventional passive prosthesis, the proposed shared neural controller significantly reduced muscle effort in both the intact limb (21-51% decrease) and the residual limb (38-48% decrease). We also found that the body weight lifted by the prosthesis side increased significantly while standing up with the robotic leg prosthesis (49%-68% increase), leading to better loading symmetry (43-46% of body weight on the prosthesis side). By decreasing muscle effort and improving symmetry, the proposed shared neural controller has the potential to improve amputee mobility and decrease the risk of falls compared to using conventional passive prostheses.
新兴的机器人膝盖和脚踝假肢为恢复缺失生物腿的生物力学功能提供了机会,而传统的被动假肢则无法做到这一点。然而,在将机器人假肢运动与用户的神经肌肉系统进行协调以及在不同活动之间进行转换方面存在挑战,限制了这些设备在现实世界中的可行性。在此,我们表明,一种将来自用户残肢的神经信号与机器人控制相结合的共享神经控制方法,可提高膝上截肢个体的功能移动性。所提出的共享神经控制器使受试者能够在各种条件下站立和坐下、蹲下、弓步、行走,并在不同活动之间无缝转换,而无需对预期动作进行明确分类。没有其他现有技术能使膝上截肢个体达到这种移动水平。此外,我们表明,与使用传统被动假肢相比,所提出的共享神经控制器显著降低了健全肢体(减少21%-51%)和残肢(减少38%-48%)的肌肉用力。我们还发现,在使用机器人腿部假肢站立时,假肢侧承受的体重显著增加(增加49%-68%),从而实现了更好的负重对称性(假肢侧承受43%-46%的体重)。通过减少肌肉用力并提高对称性,与使用传统被动假肢相比,所提出的共享神经控制器有潜力提高截肢者的移动性并降低跌倒风险。