Multimodal Inte-R-Action Lab, University of Bath, Bath BA2 7AY, UK.
Centre for Autonomous Robotics (CENTAUR), University of Bath, Bath BA2 7AY, UK.
Sensors (Basel). 2021 Oct 12;21(20):6751. doi: 10.3390/s21206751.
Wearable assistive robotics is an emerging technology with the potential to assist humans with sensorimotor impairments to perform daily activities. This assistance enables individuals to be physically and socially active, perform activities independently, and recover quality of life. These benefits to society have motivated the study of several robotic approaches, developing systems ranging from rigid to soft robots with single and multimodal sensing, heuristics and machine learning methods, and from manual to autonomous control for assistance of the upper and lower limbs. This type of wearable robotic technology, being in direct contact and interaction with the body, needs to comply with a variety of requirements to make the system and assistance efficient, safe and usable on a daily basis by the individual. This paper presents a brief review of the progress achieved in recent years, the current challenges and trends for the design and deployment of wearable assistive robotics including the clinical and user need, material and sensing technology, machine learning methods for perception and control, adaptability and acceptability, datasets and standards, and translation from lab to the real world.
可穿戴辅助机器人技术是一项具有广阔应用前景的新兴技术，它可以帮助感觉运动障碍者进行日常活动。这种辅助使个体能够在身体和社交方面保持活跃，独立完成活动，并恢复生活质量。这些对社会的好处促使人们研究了几种机器人方法，开发了从刚性到软机器人的系统，具有单模态和多模态传感、启发式和机器学习方法，以及从手动到自主控制的上肢和下肢辅助系统。这种可穿戴机器人技术与身体直接接触和相互作用，需要满足各种要求，使系统和辅助设备能够高效、安全和日常使用，并且便于个体使用。本文简要回顾了近年来取得的进展，讨论了设计和部署可穿戴辅助机器人技术的当前挑战和趋势，包括临床和用户需求、材料和传感技术、用于感知和控制的机器学习方法、适应性和可接受性、数据集和标准，以及从实验室到现实世界的转化。
