Nataraj Raviraj, Audu Musa L, Triolo Ronald J
Department of Orthopaedics, Case Western Reserve University, Cleveland, OH, USA.
Advanced Platform Technology Center, Cleveland Louis Stokes Veterans Affairs Medical Center, 10701 East Boulevard, Cleveland, OH, 44106, USA.
Med Biol Eng Comput. 2016 Jan;54(1):163-76. doi: 10.1007/s11517-015-1377-5. Epub 2015 Sep 1.
In this simulation study, we present and examine methods to develop a feedback controller for a neuroprosthesis that restores forward and side leaning function during standing following complete thoracic-level spinal cord injury. Achieving leaning postures away from erect stance with functional neuromuscular stimulation (FNS) would allow users to extend their reaching capabilities. Utilizing a 3-D computer model of human stance, an FNS control system based on total-body center of mass (CoM) kinematics (position, acceleration) is developed and tested in simulation. CoM kinematics drive an artificial neural network to modulate muscle excitations and reduce the upper extremity loading, presumably against a walker or similar support surface, required to resist the effects of postural perturbations. Furthermore, a novel method to robustly estimate the feedback kinematics for standing applications is also presented while assuming 3-D accelerometer signals at locations consistent with a proposed implantable networked neuroprosthesis system. For shifting and balance at leaning postures, respectively, center of mass position and acceleration could be approximated to within 20% of the maximum value, with strong correlations (R > 0.9) between values estimated by the proposed method and the true values derived from model dynamics. When utilizing the estimated feedback kinematics for FNS control, standing performance in terms of maximum upper extremity loading was still significantly reduced (p < 0.001) compared to conventionally applying constant and maximal stimulation. In the future, these simulation-based methods will be employed to develop experimental approaches for restoring leaning standing function by FNS.
在这项模拟研究中,我们提出并检验了为神经假体开发反馈控制器的方法,该神经假体可在完全胸段脊髓损伤后的站立过程中恢复向前和向侧倾斜功能。通过功能性神经肌肉刺激(FNS)实现从直立姿势到倾斜姿势,将使使用者能够扩展其够物能力。利用人体站立的三维计算机模型,开发了一种基于全身质心(CoM)运动学(位置、加速度)的FNS控制系统,并在模拟中进行了测试。CoM运动学驱动人工神经网络来调节肌肉兴奋,并减少抵抗姿势扰动影响所需的上肢负荷,推测是靠在助行器或类似支撑面上。此外,还提出了一种在假设与拟议的植入式联网神经假体系统一致的位置处有三维加速度计信号的情况下,稳健估计站立应用反馈运动学的新方法。对于倾斜姿势下的移位和平衡,质心位置和加速度分别可近似到最大值的20%以内,所提出方法估计的值与模型动力学得出的真实值之间有很强的相关性(R>0.9)。当将估计的反馈运动学用于FNS控制时,与传统上应用恒定和最大刺激相比,最大上肢负荷方面的站立性能仍显著降低(p<0.001)。未来,这些基于模拟的方法将用于开发通过FNS恢复倾斜站立功能的实验方法。