Missiroli Francesco, Lotti Nicola, Xiloyannis Michele, Sloot Lizeth H, Riener Robert, Masia Lorenzo
Institut für Technische Informatik (ZITI), Heidelberg University, Heidelberg, Germany.
Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland.
Front Robot AI. 2020 Dec 17;7:595844. doi: 10.3389/frobt.2020.595844. eCollection 2020.
The growing field of soft wearable exosuits, is gradually gaining terrain and proposing new complementary solutions in assistive technology, with several advantages in terms of portability, kinematic transparency, ergonomics, and metabolic efficiency. Those are palatable benefits that can be exploited in several applications, ranging from strength and resistance augmentation in industrial scenarios, to assistance or rehabilitation for people with motor impairments. To be effective, however, an exosuit needs to synergistically work with the human and matching specific requirements in terms of both movements kinematics and dynamics: an accurate and timely intention-detection strategy is the paramount aspect which assume a fundamental importance for acceptance and usability of such technology. We previously proposed to tackle this challenge by means of a model-based myoelectric controller, treating the exosuit as an external muscular layer in parallel to the human biomechanics and as such, controlled by the same efferent motor commands of biological muscles. However, previous studies that used classical control methods, demonstrated that the level of device's intervention and effectiveness of task completion are not linearly related: therefore, using a newly implemented EMG-driven controller, we isolated and characterized the relationship between assistance magnitude and muscular benefits, with the goal to find a range of assistance which could make the controller versatile for both dynamic and static tasks. Ten healthy participants performed the experiment resembling functional daily activities living in separate assistance conditions: without the device's active support and with different levels of intervention by the exosuit. Higher assistance levels resulted in larger reductions in the activity of the muscles augmented by the suit actuation and a good performance in motion accuracy, despite involving a decrease of the movement velocities, with respect to the no assistance condition. Moreover, increasing torque magnitude by the exosuit resulted in a significant reduction in the biological torque at the elbow joint and in a progressive effective delay in the onset of muscular fatigue. Thus, contrarily to classical force and proportional myoelectric schemes, the implementation of an opportunely tailored EMG-driven model based controller affords to naturally match user's intention detection and provide an assistance level working symbiotically with the human biomechanics.
可穿戴柔性外骨骼这一不断发展的领域正逐渐占据一席之地,并在辅助技术中提出新的补充解决方案,在便携性、运动透明性、人体工程学和代谢效率方面具有诸多优势。这些好处很有吸引力,可应用于多种场景,从工业场景中的力量增强和阻力增加,到为运动障碍患者提供辅助或康复治疗。然而,要发挥效力,外骨骼需要与人体协同工作,并在运动学和动力学方面满足特定要求:准确及时的意图检测策略是至关重要的方面,对该技术的接受度和可用性起着根本性作用。我们之前提议通过基于模型的肌电控制器来应对这一挑战,将外骨骼视为与人体生物力学并行的外部肌肉层,因此由与生物肌肉相同的传出运动指令控制。然而,之前使用经典控制方法的研究表明,设备的干预水平与任务完成的有效性并非线性相关:因此,使用新实施的肌电驱动控制器,我们分离并表征了辅助幅度与肌肉益处之间的关系,目标是找到一系列辅助水平,使控制器在动态和静态任务中都具有通用性。十名健康参与者在不同辅助条件下进行了类似日常功能活动的实验:无设备主动支持以及外骨骼不同程度的干预。尽管相对于无辅助条件运动速度有所降低,但较高的辅助水平导致由套装驱动增强的肌肉活动大幅减少,且运动精度良好。此外,外骨骼增加扭矩幅度导致肘关节处的生物扭矩显著降低,并使肌肉疲劳的开始出现逐渐有效的延迟。因此,与经典的力和比例肌电方案相反,实施适当定制的基于肌电驱动模型的控制器能够自然地匹配用户的意图检测,并提供与人体生物力学共生的辅助水平。