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Asymmetric robotic gait training and asymmetric reaching training to induce both

不对称机器人步态训练和不对称到达训练诱导两者

基本信息

批准号：
8904908
负责人：
NATHAN DANIEL NECKEL
金额：
$ 24.76万
依托单位：
GEORGETOWN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-08-15 至 2017-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8904908
关键词：
Address Affect Animal Experimentation Animal Model Animals Asses Behavior Cervical Cervical spinal cord injury Clinical Corticospinal Tracts Devices Diffusion Magnetic Resonance Imaging Doctor of Philosophy Effectiveness Ensure Environment Fiber Forelimb Gait Health Hindlimb Human Individual Injury Intervention Lead Learning Limb structure Locomotion Locomotor Recovery Measures Methods Monitor Movement Nervous System Trauma Neuraxis Neuronal Plasticity Neurorehabilitation Outcome Patients Pattern Performance Postdoctoral Fellow Proteins Rattus Recovery Recovery of Function Research Research Personnel Resistance Robot Robotics Rodent Rodent Model Running Staining method Stains Stroke Structure of rubrospinal tract Synapses Techniques Tracer Trainers Training Training Training Technics Translating Viscosity Walking Western Blotting Work arm central nervous system injury clinical practice design experience functional improvement functional restoration grasp hemiparesis improved injured meter novel relating to nervous system research study response robotic device treadmill training

项目摘要

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.

我的博士工作重点是Lokomat机器人步态训练设备和测量患者在训练过程中使用这种装置进行训练。作为博士后，我目前正在研究一种啮齿动物机器人的能力颈髓损伤后恢复地面活动的步态训练器及其基础中枢神经系统对训练的可塑性。在人类和动物的机器人步态中对于训练者来说，训练包括积极引导肢体通过对称的健康步态模式。作为一种独立研究员我建议研究不同的培训模式，特别是不对称内的培训力场，从而找到最优的机器人训练方案。非对称训练也可以应用于其他任务，比如熟练的伸展。因此，我想要证明，运动和运动的不对称训练在各种任务中，触觉将导致更大的功能改善和更大的神经元可塑性常规的对称训练。通过在动物模型中揭示最佳训练技术，临床然后，培训做法可能会得到改进。