Continuous sweep versus discrete step protocols for studying effects of wearable robot assistance magnitude.

Continuous sweep versus discrete step protocols for studying effects of wearable robot assistance magnitude.
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DOI:
10.1186/s12984-017-0278-2
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发表时间:
2017-07-12
影响因子:
5.1
通讯作者:
Walsh CJ
Walsh CJ
中科院分区:
工程技术2区
文献类型:
--
作者:
Malcolm P;Rossi DM;Siviy C;Lee S;Quinlivan BT;Grimmer M;Walsh CJ

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不同的团队开发了用于步行辅助的可穿戴机器人,但仍然需要快速调整每个机器人和群体甚至有时甚至单个用户的驱动参数的方法。参数保持恒定多分钟的协议传统上用于评估对参数变化(例如代谢率或步行对称性)的反应。然而,这些离散协议非常耗时。最近,已经提出了参数以连续方式改变的协议。本研究的目的是比较连续变化的辅助幅度与软外装在离散步骤条件下的效果。七名参与者穿着有助于跖屈和髋部屈曲的柔软外骨骼在跑步机上行走。在连续向上中,峰值外装护踝力矩在 10 分钟内从生物力矩的约 0% 线性增加到 38%。连续下跌则相反。在离散模式中,参与者经历了五个 5 分钟的阶段,稳定的峰值力矩水平分布在与连续上升和连续下降相同的范围内。我们计算了整个连续向上和连续向下条件以及每个离散力水平的最后 2 分钟的代谢率。我们通过曲线拟合与峰值时刻比较了不同条件下的运动学、动力学和代谢率。在大多数峰值时刻水平,与断电相比,连续上升中的代谢率降低幅度小于连续下降中的变化,这是由于生理动力学导致连续上升和连续下降中的代谢测量值落后于稳态测试期间的预期值。当评估整个峰值时刻范围内代谢减少的平均斜率时,连续下降和离散之间没有显着差异。尝试通过取连续上升和连续下降的平均值来纠正代谢的滞后,消除了与离散相比的所有显着差异。对于运动学和动力学参数,所有条件之间没有差异。所有条件之间的生物力学参数没有差异的发现表明,可以用最短的协议条件(即单个连续方向)记录生物力学参数。连续扫描协议的更短时间和更高分辨率的数据为人类与可穿戴机器人交互的未来研究带来了希望。本文的在线版本 (doi:10.1186/s12984-017-0278-2) 包含补充材料,可供授权用户使用。
Different groups developed wearable robots for walking assistance, but there is still a need for methods to quickly tune actuation parameters for each robot and population or sometimes even for individual users. Protocols where parameters are held constant for multiple minutes have traditionally been used for evaluating responses to parameter changes such as metabolic rate or walking symmetry. However, these discrete protocols are time-consuming. Recently, protocols have been proposed where a parameter is changed in a continuous way. The aim of the present study was to compare effects of continuously varying assistance magnitude with a soft exosuit against discrete step conditions. Seven participants walked on a treadmill wearing a soft exosuit that assists plantarflexion and hip flexion. In Continuous-up, peak exosuit ankle moment linearly increased from approximately 0 to 38% of biological moment over 10 min. Continuous-down was the opposite. In Discrete, participants underwent five periods of 5 min with steady peak moment levels distributed over the same range as Continuous-up and Continuous-down. We calculated metabolic rate for the entire Continuous-up and Continuous-down conditions and the last 2 min of each Discrete force level. We compared kinematics, kinetics and metabolic rate between conditions by curve fitting versus peak moment. Reduction in metabolic rate compared to Powered-off was smaller in Continuous-up than in Continuous-down at most peak moment levels, due to physiological dynamics causing metabolic measurements in Continuous-up and Continuous-down to lag behind the values expected during steady-state testing. When evaluating the average slope of metabolic reduction over the entire peak moment range there was no significant difference between Continuous-down and Discrete. Attempting to correct the lag in metabolics by taking the average of Continuous-up and Continuous-down removed all significant differences versus Discrete. For kinematic and kinetic parameters, there were no differences between all conditions. The finding that there were no differences in biomechanical parameters between all conditions suggests that biomechanical parameters can be recorded with the shortest protocol condition (i.e. single Continuous directions). The shorter time and higher resolution data of continuous sweep protocols hold promise for the future study of human interaction with wearable robots. The online version of this article (doi:10.1186/s12984-017-0278-2) contains supplementary material, which is available to authorized users.
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