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Neuroergonomics Metrics to evaluate Exoskeleton based Gait Rehabilitation

机译:神经变动性指标评估基于外骨骼的步态康复

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To quantify mental effort and track neurophysiological changes due to powered-robotic-exoskeleton based gait training objectively, we investigated the feasibility of using functional connectivity and neural efficiency metrics obtained from functional near infrared spectroscopy to monitor neurophysiological changes during powered robotic exoskeleton-based gait training in two stroke and two spinal cord injury (SCI) patients. Increased functional connectivity between different brain regions were associated with improved gait performance in stroke patients but indicated increased mental workload with no gait changes in SCI patients. Neural efficiency provided cost of maintaining motor performance in all four patients. Both metrics show potential in tracking mental effort and gait training progress and may serve as valuable inputs to rehab exoskeleton brain computer interfaces and contribute to the development of personalized rehabilitation programs.
机译:为了量化精神努力和追踪神经生理学变化,由于有机动力机器人的步态训练,我们研究了使用近红外光谱的功能近红外光谱所获得的功能连接和神经效率度量的可行性,以监测动力机器人外屏幕的步态训练期间的神经生理学变化两次中风和两个脊髓损伤(SCI)患者。不同脑区之间的功能连接增加与卒中患者的步态性能提高,但表明了心理工作量增加,SCI患者没有步态变化。神经效率提供了在所有四名患者中维持电动机性能的成本。这两个指标都表明了跟踪心理努力和步态培训进展的潜力,并可作为康复脑脑脑电器界面的有价值的投入,并有助于开发个性化康复计划。

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