Castro Miguel Nobre, Dosen Strahinja
Neurorehabilitation Systems, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
Front Neurorobot. 2022 Mar 25;16:814973. doi: 10.3389/fnbot.2022.814973. eCollection 2022.
Modern myoelectric prostheses can perform multiple functions (e.g., several grasp types and wrist rotation) but their intuitive control by the user is still an open challenge. It has been recently demonstrated that semi-autonomous control can allow the subjects to operate complex prostheses effectively; however, this approach often requires placing sensors on the user. The present study proposes a system for semi-autonomous control of a myoelectric prosthesis that requires a single depth sensor placed on the dorsal side of the hand. The system automatically pre-shapes the hand (grasp type, size, and wrist rotation) and allows the user to grasp objects of different shapes, sizes and orientations, placed individually or within cluttered scenes. The system "reacts" to the side from which the object is approached, and enables the user to target not only the whole object but also an object part. Another unique aspect of the system is that it relies on online interaction between the user and the prosthesis; the system reacts continuously on the targets that are in its focus, while the user interprets the movement of the prosthesis to adjust aiming. Experimental assessment was conducted in ten able-bodied participants to evaluate the feasibility and the impact of training on prosthesis-user interaction. The subjects used the system to grasp a set of objects individually (Phase I) and in cluttered scenarios (Phase II), while the time to accomplish the task (TAT) was used as the performance metric. In both phases, the TAT improved significantly across blocks. Some targets (objects and/or their parts) were more challenging, requiring thus significantly more time to handle, but all objects and scenes were successfully accomplished by all subjects. The assessment therefore demonstrated that the system is indeed robust and effective, and that the subjects could successfully learn how to aim with the system after a brief training. This is an important step toward the development of a self-contained semi-autonomous system convenient for clinical applications.
现代肌电假肢可以执行多种功能(例如,几种抓握类型和手腕旋转),但其由用户进行直观控制仍然是一个有待解决的挑战。最近有研究表明,半自主控制可以让使用者有效地操作复杂的假肢;然而,这种方法通常需要在使用者身上放置传感器。本研究提出了一种用于肌电假肢半自主控制的系统,该系统只需要在手部背侧放置一个深度传感器。该系统会自动对手部进行预塑形(抓握类型、尺寸和手腕旋转),并允许用户抓握不同形状、尺寸和方向的物体,这些物体可以单独放置,也可以放置在杂乱的场景中。该系统会对物体靠近的方向做出“反应”,并使用户不仅能够瞄准整个物体,还能瞄准物体的一部分。该系统的另一个独特之处在于它依赖于用户与假肢之间的在线交互;系统会持续对其关注的目标做出反应,而用户则通过解读假肢的动作来调整瞄准。在十名身体健全的参与者身上进行了实验评估,以评估训练对假肢与用户交互的可行性和影响。受试者使用该系统分别在单独的场景(第一阶段)和杂乱的场景(第二阶段)中抓握一组物体,完成任务的时间(TAT)被用作性能指标。在两个阶段中,TAT在各个组块中都有显著改善。一些目标(物体和/或其部分)更具挑战性,因此需要显著更多的时间来处理,但所有受试者都成功完成了所有物体和场景的操作。因此,评估表明该系统确实强大且有效,并且受试者在经过简短训练后能够成功学会如何使用该系统进行瞄准。这是朝着开发便于临床应用的独立半自主系统迈出的重要一步。