Chai Guohong, Wang Han, Li Guangye, Sheng Xinjun, Zhu Xiangyang
IEEE Trans Neural Syst Rehabil Eng. 2022;30:1310-1320. doi: 10.1109/TNSRE.2022.3173329. Epub 2022 May 26.
Current myoelectric hands are limited in their ability to provide effective sensory feedback to the users, which highly affects their functionality and utility. Although the sensory information of a myoelectric hand can be acquired with equipped sensors, transforming the sensory signals into effective tactile sensations on users for functional tasks is a largely unsolved challenge. The purpose of this study aims to demonstrate that electrotactile feedback of the grip force improves the sensorimotor control of a myoelectric hand and enables object stiffness recognition. The grip force of a sensorized myoelectric hand was delivered to its users via electrotactile stimulation based on four kinds of typical encoding strategies, including graded (G), linear amplitude (LA), linear frequency (LF), and biomimetic (B) modulation. Object stiffness was encoded with the change of electrotactile sensations triggered by final grip force, as the prosthesis grasped the objects. Ten able-bodied subjects and two transradial amputees were recruited to participate in a dual-task virtual eggs test (VET) and an object stiffness discrimination test (OSDT) to quantify the prosthesis users' ability to handle fragile objects and recognize object stiffnesses, respectively. The quantified results showed that with electrotactile feedback enabled, the four kinds of encoding strategies allowed subjects to better able to handle fragile objects with similar performance, and the subjects were able to differentiate four levels of object stiffness at favorable accuracies (>86%) and high manual efficiency. Strategy LA presented the best stiffness discrimination performance, while strategy B was able to reduce the discrimination time but the discrimination accuracy was not better than the other three strategies. Electrotactile feedback also enhanced prosthesis embodiment and improved the users' confidence in prosthetic control. Outcomes indicate electrotactile feedback can be effectively exploited by the prosthesis users for grip force control and object stiffness recognition, proving the feasibility of functional sensory restoration of myoelectric prostheses equipped with electrotactile feedback.
目前的肌电手在向用户提供有效感官反馈方面能力有限，这严重影响了它们的功能和实用性。尽管可以通过配备的传感器获取肌电手的感官信息，但将感官信号转化为用户在功能任务中有效的触觉感受，在很大程度上仍是一个未解决的挑战。本研究的目的旨在证明握力的电触觉反馈可改善肌电手的感觉运动控制，并实现物体硬度识别。一个装有传感器的肌电手的握力通过基于四种典型编码策略的电触觉刺激传递给用户，这四种策略包括分级（G）、线性幅度（LA）、线性频率（LF）和仿生（B）调制。当假肢抓住物体时，物体硬度通过最终握力触发的电触觉感受变化进行编码。招募了10名身体健全的受试者和2名经桡骨截肢者，分别参与双任务虚拟鸡蛋测试（VET）和物体硬度辨别测试（OSDT），以量化假肢使用者处理易碎物体的能力和识别物体硬度的能力。量化结果表明，启用电触觉反馈后，四种编码策略使受试者能够以相似的表现更好地处理易碎物体，并且受试者能够以良好的准确率（>86%）和较高的操作效率区分四个物体硬度级别。策略LA表现出最佳的硬度辨别性能，而策略B能够减少辨别时间，但辨别准确率并不优于其他三种策略。电触觉反馈还增强了假肢的实体感，并提高了用户对假肢控制的信心。结果表明，假肢使用者可以有效地利用电触觉反馈进行握力控制和物体硬度识别，证明了配备电触觉反馈的肌电假肢功能感官恢复的可行性。
