Similar sensorimotor transformations control balance during standing and walking.
Similar sensorimotor transformations control balance during standing and walking.
复制标题
类似的感觉运动转换控制站立和行走时的平衡。
DOI：
10.1371/journal.pcbi.1008369
复制
发表时间：
2021-06
影响因子：
4.3
通讯作者：
Jonkers I
中科院分区：
文献类型：
--
作者：
Afschrift M;De Groote F;Jonkers I
人类的站立和行走平衡控制依赖于将感觉信息转化为驱动肌肉的运动指令。在这里，我们评估了行走平衡控制背后的感觉运动转换是否可以通过类似于站立平衡控制的任务级质心运动学反馈来描述。我们发现，质心位置和速度的延迟线性反馈，而不是来自踝关节角度和角速度的延迟线性反馈，可以解释响应跨协议行走扰动的反应性踝关节肌肉活动和关节力矩（离散和连续平台平移和离散骨盆推动）。反馈增益在步态周期内进行调节，并随着步行速度而减小。因此，我们的结果表明，类似的任务级变量，即质心位置和速度，在站立和行走过程中受到控制，但反馈增益在步态期间进行调节，以适应步态周期期间身体配置的变化以及步行速度的稳定性。这些发现对于人体平衡控制的神经力学建模和可穿戴机器人设备的仿生控制具有重要意义。我们确定的反馈机制可用于扩展当前缺乏踝关节平衡控制机制的神经力学模型。当使用这些模型来控制可穿戴机器人设备时，我们相信这将有助于用户和机器人设备之间共享平衡控制。人类站立和行走的稳定性是显着的，因为从机械角度来看，站立和行走是高度不稳定的，因此需要中枢神经系统良好协调的控制动作。神经系统通过感觉输入不断接收有关身体状态的信息，这些信息经过处理后会向肌肉产生下行运动命令。然而，目前尚不清楚中枢神经系统如何利用多个传感器的信息来控制行走平衡。在站立平衡中，这种感觉运动转换已经被研究过。先前的研究表明，当站立平衡受到干扰时，中枢神经系统会估计整个身体质心的运动，以激活肌肉并控制平衡。在这里，我们研究了相同的感觉运动转换是否是步行平衡控制的基础。我们发现，由于步行平衡的扰动而导致的肌肉活动和踝关节力矩的变化确实与质心运动成正比。这些发现表明，共同的过程是控制站立和行走平衡的基础。我们的工作意义重大，因为它以身体质心运动和矫正关节力矩之间的简单关系捕获了复杂的基础神经过程的结果，可以在假肢和外骨骼的控制中实现，以类似人类的方式支持平衡控制。
Standing and walking balance control in humans relies on the transformation of sensory information to motor commands that drive muscles. Here, we evaluated whether sensorimotor transformations underlying walking balance control can be described by task-level center of mass kinematics feedback similar to standing balance control. We found that delayed linear feedback of center of mass position and velocity, but not delayed linear feedback from ankle angles and angular velocities, can explain reactive ankle muscle activity and joint moments in response to perturbations of walking across protocols (discrete and continuous platform translations and discrete pelvis pushes). Feedback gains were modulated during the gait cycle and decreased with walking speed. Our results thus suggest that similar task-level variables, i.e. center of mass position and velocity, are controlled across standing and walking but that feedback gains are modulated during gait to accommodate changes in body configuration during the gait cycle and in stability with walking speed. These findings have important implications for modelling the neuromechanics of human balance control and for biomimetic control of wearable robotic devices. The feedback mechanisms we identified can be used to extend the current neuromechanical models that lack balance control mechanisms for the ankle joint. When using these models in the control of wearable robotic devices, we believe that this will facilitate shared control of balance between the user and the robotic device. The stability of human standing and walking is remarkable, given that from a mechanical point of view standing and walking are highly unstable and therefore require well-coordinated control actions from the central nervous system. The nervous system continuously receives information on the state of the body through sensory inputs, which is processed to generate descending motor commands to the muscles. It remains, however, unclear how the central nervous system uses information from multiple sensors to control walking balance. In standing balance, such sensorimotor transformations have been studied. When standing balance is perturbed, previous studies suggest that the central nervous system estimates the movement of the whole body center of mass to activate muscles and control balance. Here, we investigated whether the same sensorimotor transformations underlie control of walking balance. We found that changes in muscle activity and ankle moments in response to perturbations of walking balance were indeed proportional to center of mass movement. These findings suggest that common processes underlie control of standing and walking balance. Our work is significant because it captures the result of complex underlying neural processes in a simple relation between the body’s center of mass movement and corrective joint moments that can be implemented in the control of prostheses and exoskeletons to support balance control in a human-like manner.
登录
查看更多内容
影响因子：
3.2
作者：
Song S;Geyer H
通讯作者：
Geyer H
影响因子：
2.5
作者：
Besomi, Manuela;Hodges, Paul W.;Tucker, Kylie
通讯作者：
Tucker, Kylie
影响因子：
4.6
作者：
Afschrift M;Pitto L;Aerts W;van Deursen R;Jonkers I;De Groote F
通讯作者：
De Groote F
影响因子：
2.5
作者：
Safavynia, Seyed A.;Ting, Lena H.
通讯作者：
Ting, Lena H.
影响因子：
2.4
作者：
De Groote F;Allen JL;Ting LH
通讯作者：
Ting LH