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首页> 外文期刊>IEEE Transactions on Medical Robotics and Bionics >Using Generic Upper-Body Movement Strategies in a Free Walking Setting to Detect Gait Initiation Intention in a Lower-Limb Exoskeleton
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Using Generic Upper-Body Movement Strategies in a Free Walking Setting to Detect Gait Initiation Intention in a Lower-Limb Exoskeleton

机译:在自由行走设置中使用通用上身运动策略,以检测低肢前骨骼中的步态启动意图

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摘要

In recent years, lower-limb exoskeletons have been marketed to become a possible alternative to wheelchairs for people with walking impairments or paralysis. However, most assistive exoskeletons rely on constraining control strategies based on remote controls or torso tilting events. One approach to build more intuitive control interfaces would be to exploit knowledge on human motor control, and the coordination between upper and lower limb movements during gait events, such as the anticipatory postural adjustments that precede gait initiation. In this study, it was hypothesized that generic trunk and arm movements preceding gait in a free walking setting in able-bodied users can still be retrieved while wearing an assistive lower-limb exoskeleton that constrains their leg movements. This was evaluated on a group of eight unimpaired participants, and analysis of upper-body wearable IMU signals showed similarity of postural adjustments between the free and exoskeleton-constrained settings. Additionally, a classification architecture showed that the walking state of the robot can be correctly triggered based on free-walking data gathered from all participants with an accuracy rate of 95%. This suggests that interlimb coordination still exists in a constrained setting, and could pave the road towards the elaboration of more natural controls for assistive lower-limb exoskeletons.
机译:近年来,下肢外骨骼已被销售,以便成为携带行走障碍或瘫痪的人的轮椅可能的替代方案。然而,大多数辅助外骨骼依赖于基于遥控器或躯干倾斜事件的限制控制策略。构建更直观的控制界面的一种方法是利用人机控制的知识,并且在步态事件期间上下肢体运动之间的协调,例如在步态启动之前的预期姿势调整。在这项研究中,假设可以在佩戴辅助低肢前骨骼的辅助下肢外骨骼中,在能够施加的辅助下肢外骨骼中,静止步态穿着步态穿着步态的通用躯干和臂运动。这是在一组八个未受害的参与者中评估的,并且上体可穿戴IMU信号的分析显示出自由和外骨骼受约束的环境之间的姿势调整的相似性。另外,分类架构表明,可以基于从所有参与者收集的自由行走数据正确触发机器人的步行状态,精度率为95%。这表明InterlaMB协调仍然存在于约束的环境中,并且可以挖掘道路朝着辅助下肢外骨骼进行更多的自然对照。

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