BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Sci Robot. 2024 Sep 11;9(94):eadp3260. doi: 10.1126/scirobotics.adp3260.
The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the patient and the ability to carry out daily work and social activities. Recent years have witnessed a rapid evolution of surgical techniques and technologies aimed at restoring dexterous motor functions akin to those of the human hand through bionic solutions, mainly relying on probing of electrical signals from the residual nerves and muscles. Here, we report the clinical implementation of an interface aimed at achieving this goal by exploiting muscle deformation, sensed through passive magnetic implants: the myokinetic interface. One participant with a transradial amputation received an implantation of six permanent magnets in three muscles of the residual limb. A truly self-contained myokinetic prosthetic arm embedding all hardware components and the battery within the prosthetic socket was developed. By retrieving muscle deformation caused by voluntary contraction through magnet localization, we were able to control in real time a dexterous robotic hand following both a direct control strategy and a pattern recognition approach. In just 6 weeks, the participant successfully completed a series of functional tests, achieving scores similar to those achieved when using myoelectric controllers, a standard-of-care solution, with comparable physical and mental workloads. This experience raised conceptual and technical limits of the interface, which nevertheless pave the way for further investigations in a partially unexplored field. This study also demonstrates a viable possibility for intuitively interfacing humans with robotic technologies.
手的丧失破坏了大脑和手之间复杂的神经通路,严重影响了患者的独立性水平和进行日常工作和社会活动的能力。近年来,手术技术和技术取得了快速发展,旨在通过仿生解决方案恢复类似于人手的灵巧运动功能,主要依赖于探测残留神经和肌肉的电信号。在这里,我们报告了一种接口的临床实施情况,该接口通过利用肌肉变形来实现这一目标,这些变形通过无源磁植入物来感应:运动学接口。一名桡骨截肢患者接受了在残肢的三块肌肉中植入六个永久磁铁的手术。开发了一种真正的自包含运动学假肢手臂,将所有硬件组件和电池嵌入假肢插座中。通过通过磁铁定位检索自愿收缩引起的肌肉变形,我们能够实时控制灵巧的机器人手,既可以采用直接控制策略,也可以采用模式识别方法。在仅仅 6 周的时间里,参与者成功地完成了一系列功能测试,得分与使用肌电控制器(一种标准护理解决方案)时相似,而身体和精神的工作量相当。这一体验提高了界面的概念和技术限制,但为在部分未开发领域进行进一步研究铺平了道路。这项研究还证明了人类与机器人技术进行直观交互的一种可行可能性。