Asymmetric robotic gait training and asymmetric reaching training to induce both

我的博士工作主要集中在Lokomat机器人步态训练设备和测量病人的实际力量， 在这个装置中训练时产生的。作为一名博士后，我目前正在研究一种啮齿动物机器人的能力， 用于恢复颈脊髓损伤后地上运动的步态训练装置 中枢神经系统对训练的可塑性。在人类和动物机器人步态中 训练者，训练包括通过对称的健康步态模式主动引导肢体。作为 独立研究员我建议研究不同的训练模式，特别是在不对称训练中， 力场，以找到最佳的机器人训练。不对称训练也可以应用于其他任务， 比如熟练的伸手。因此，我打算表明，不对称训练的运动和 在各种任务中，延伸将导致更大的功能改善和更大的神经元可塑性， 传统的对称训练。通过在动物模型中发现最佳训练技术， 然后可以改进培训做法。

My PhD work focused on the Lokomat robotic gait training device and measuring the actual forces that patients exerted during training in this device. As a postdoc I am currently investigating the ability of a rodent robotic gait training device to restore overground locomotion following cervical spinal cord injury and the underlying plasticity of the central nervous system in response to the training. In both human and animal robotic gait trainers, the training consists of actively guiding the limbs through a symmetric healthy gait pattern. As an independent researcher I propose to study different training patterns, specifically training within asymmetric force fields, in order to find the optimal robotic training. Asymmetric training can also be applied to other tasks, such as skilled reaching. Therefore I intend to show that the asymmetric training of both locomotion and reaching will lead to greater functional improvements in a variety of tasks and greater neuronal plasticity than the conventional symmetric training. By uncovering the optimal training techniques in animal models, clinical training practices may then be improved.