Automated and Adaptive Lower Extremity Neuro-Rehabilitation for Stroke

描述（由申请人提供）：通过我们的研究，我们的目标是开发定量的方法来评估中风幸存者使用下肢康复Lokomat平台（Hocoma AG，瑞士）的运动学习。准确理解康复计划的结构如何影响运动技能的长期保留，对于确定治疗方法的疗效和比较不同策略的疗效至关重要。目前的方法对康复工作者来说也非常费力，在某些情况下，治疗师的压力可能成为每次治疗时间或每次治疗活动数量的限制因素。通过应用控制理论和信号处理领域的先进工程技术，我们希望为Lokomat平台等设备开发自动化和自适应策略，使康复工作者在提供技能的同时消除大部分压力。这些策略通过为患者提供他们的个人基线和改善率所规定的任务，而不需要治疗师的干预，可能会导致恢复速度的加快。

DESCRIPTION (provided by applicant): Through our research we aim to develop quantitative methods for the assessment of motor learning in stroke survivors using the lower extremity rehabilitation Lokomat platform (Hocoma AG, Switzerland). Accurate understanding of how the structure of a rehabilitation program affects the long-term retention of motor skills is essential for establishing the efficacy of therapeutic approaches and for comparing efficacy across strategies. Current methods are also very laborious for rehabilitation workers and in some situations strain on the therapist can be the limiting factor on the length of a session or on the number of activities conducted per session. By applying advanced engineering techniques from the fields of control theory and signal processing, we hope to develop automated and adaptive strategies for devices like the Lokomat platform that allow rehabilitation workers to provide their skills while removing much of the strain. These strategies may result in increased speed of recovery by providing patients with tasks dictated by their individual baseline and rate of improvement without the need for therapist intervention.