Heung Kelvin H L, Li Heng, Wong Thomson W L, Ng Shamay S M
Department of Building and Real Estate, Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
Department of Rehabilitation Sciences, Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
Front Bioeng Biotechnol. 2023 Jul 5;11:1188996. doi: 10.3389/fbioe.2023.1188996. eCollection 2023.
Soft wearable robotic hand can assist with hand function for the performance of activities of daily living (ADL). However, existing robotic hands lack a mathematical way to quantify the grip force generated for better controlling the grasp of objects during the performance of ADL. To address this issue, this article presents a soft wearable robotic hand with active control of finger flexion and extension through an elastomeric-based bi-directional soft actuator. This actuator bends and extends by pneumatic actuation at lower air pressure, and a flex sensor embedded inside the actuator measures the angles of the fingers in real-time. Analytical models are established to quantify the kinematic and tip force for gripping of the actuator in terms of the relationship between the input pressure and the bending angle, as well as the output force, and are validated experimentally and by the finite element method. Furthermore, the ability of the soft robotic hand to grasp objects is validated with and without being worn on a human hand. The robotic hand facilitates hand opening and closing by the wearer and successfully assists with grasping objects with sufficient force for ADL-related tasks, and the grip force provided by the actuator is further estimated by the analytical models on two healthy subjects. Results suggest the possibility of the soft robotic hand in providing controllable grip strength in rehabilitation and ADL assistance.
柔软的可穿戴机器人手可以辅助手部功能,以完成日常生活活动(ADL)。然而,现有的机器人手缺乏一种数学方法来量化所产生的握力,以便在进行ADL时更好地控制对物体的抓握。为了解决这个问题,本文提出了一种柔软的可穿戴机器人手,它通过基于弹性体的双向软致动器对手指的屈伸进行主动控制。该致动器在较低气压下通过气动驱动弯曲和伸展,并且嵌入在致动器内部的柔性传感器实时测量手指的角度。根据输入压力与弯曲角度以及输出力之间的关系,建立了分析模型来量化致动器抓握时的运动学和尖端力,并通过实验和有限元方法进行了验证。此外,在佩戴和不佩戴在人手上的情况下,都对软机器人手抓握物体的能力进行了验证。该机器人手便于佩戴者进行手部的张开和闭合,并成功地辅助以足够的力量抓握物体以完成与ADL相关的任务,并且通过分析模型对两名健康受试者进一步估计了致动器提供的握力。结果表明,软机器人手在康复和ADL辅助中提供可控握力的可能性。