Systems Engineering Institute, Academy of Military Science, Beijing, 100091, People's Republic of China.
Department of Mechanics, School of Aerospace Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Beijing, 100081, People's Republic of China.
Sci Rep. 2023 Mar 14;13(1):4251. doi: 10.1038/s41598-023-29887-0.
Wearable robots have been growing exponentially during the past years and it is crucial to quantify the performance effectiveness and to convert them into practical benchmarks. Although there exist some common metrics such as metabolic cost, many other characteristics still needs to be presented and demonstrated. In this study, we developed an integrated evaluation (IE) approach of wearable exoskeletons of lower limb focusing on human performance augmentation. We proposed a novel classification of trial tasks closely related to exoskeleton functions, which were divided into three categories, namely, basic trial at the preliminary phase, semi-reality trial at the intermediate phase, and reality trial at the advanced phase. In the present study, the IE approach has been exercised with a subject who wore an active power-assisted knee (APAK) exoskeleton with three types of trial tasks, including walking on a treadmill at a certain angle, walking up and down on three-step stairs, and ascending in 11-storey stairs. Three wearable conditions were carried out in each trial task, i.e. with unpowered exoskeleton, with powered exoskeleton, and without the exoskeleton. Nine performance indicators (PIs) for evaluating performance effectiveness were adopted basing on three aspects of goal-level, task-based kinematics, and human-robot interactions. Results indicated that compared with other conditions, the powered APAK exoskeleton make generally lesser heart rate (HR), Metabolic equivalent (METs), biceps femoris (BF) and rectus femoris (RF) muscles activation of the subject at the preliminary phase and intermediate phase, however, with minimal performance augmentation at advanced phase, suggesting that the APAK exoskeleton is not suitable for marketing and should be further improved. In the future, continuous iterative optimization for the IE approach may help the robot community to attain a comprehensive benchmarking methodology for robot-assisted locomotion more efficiently.
在过去的几年中，可穿戴机器人呈指数级增长，因此量化其性能效果并将其转化为实际基准至关重要。尽管存在一些常见的指标，如代谢成本，但仍需要提出和展示许多其他特性。在这项研究中，我们开发了一种针对下肢可穿戴外骨骼的综合评估 (IE) 方法，重点是增强人体性能。我们提出了一种与外骨骼功能密切相关的试验任务的新分类，将其分为三个类别，即初步阶段的基本试验、中间阶段的半现实试验和高级阶段的现实试验。在本研究中，使用穿着主动助力膝（APAK）外骨骼的受试者进行了 IE 方法的练习，进行了三种类型的试验任务，包括在一定角度的跑步机上行走、上下三层楼梯以及在 11 层楼梯上爬升。在每个试验任务中，进行了三种可穿戴条件，即无动力外骨骼、动力外骨骼和无外骨骼。基于目标水平、基于任务的运动学和人机交互三个方面，采用了 9 个性能指标（PI）来评估性能效果。结果表明，与其他条件相比，在初步阶段和中间阶段，动力 APAK 外骨骼使受试者的心率（HR）、代谢当量（METs）、股二头肌（BF）和股直肌（RF）肌肉激活通常更小，而在高级阶段的性能增强最小，表明 APAK 外骨骼不适合市场推广，应进一步改进。在未来，IE 方法的持续迭代优化可能有助于机器人社区更有效地实现机器人辅助运动的全面基准测试方法。
