论文标题
I-Myo：基于眼睛跟踪，增强现实和肌电信号的混合假肢控制系统
i-MYO: A Hybrid Prosthetic Hand Control System based on Eye-tracking, Augmented Reality and Myoelectric signal
论文作者
论文摘要
灵巧的假肢比传统的手术更好。但是，患者仍然发现没有合适的控制系统很难使用这些手。提出并评估了一种称为I-Myo的新型混合肌电控制系统，以解决此问题。 I-Myo的核心组成部分是一种基于眼睛跟踪和增强现实（AR）的新颖的抓紧型切换界面，称为I-GSI。使用I-GSI，用户可以通过凝视凉亭来轻松切换抓地力（六个）作为假肢。 I-GSI是用AR头盔实现的，并将作为单个模块集成到I-Myo系统中。在i-myo系统中，使用肌电信号来按比例地控制手开 /关闭。对I-Myo的操作进行了对九个健康受试者进行测试，他们在触手可及的任务中戴上HIT-V手在前臂和操纵物体上进行了测试。还对一名肌电信号较低的患者进行了测试，并需要控制HIT-V手以抓住物体。结果表明，在91.6％的试验中，缺乏经验的健康受试者在5.9 s内完成了任务，并且大多数失败的试验是由于缺乏精细掌握的经验而引起的。此外，在大约1.5％的试验中，受试者还成功地转移了对象，但具有非最佳的掌握类型。在97.0％的试验中，受试者花费了〜1.3 s切换最佳掌握类型。由于进行了更多的试验，已经观察到了未经训练的患者的GRASP类型（99.1％）的更高成功率（99.1％）。在98.7％的试验中，患者只需要2 s即可控制手，以切换到最佳掌握类型后。这些测试证明了新系统在多道假肢中的控制能力，并且所有经验不足的受试者都能够在几个培训中快速掌握I-Myo的操作，并轻松地应用它。
Dexterous prosthetic hands have better grasp performance than traditional ones. However, patients still find it difficult to use these hands without a suitable control system. A new hybrid myoelectric control system, termed i-MYO, is presented and evaluated to solve this problem. The core component of the i-MYO is a novel grasp-type switching interface based on eye-tracking and augmented reality (AR), termed i-GSI. With the i-GSI, the user can easily switch a grasp type (six total) for a prosthetic hand by gazing at a GazeButton. The i-GSI is implemented in an AR helmet and is integrated, as an individual module, into the i-MYO system. In the i-MYO system, the myoelectric signal was used to control hand opening /closing proportionally. The operation of the i-MYO was tested on nine healthy subjects who wore HIT-V hand on the forearm and manipulated objects in a reach-and-grasp task. It was also tested on one patient who had an inferior myoelectric signal and was required to control the HIT-V hand to grasp objects. Results showed that in 91.6% of the trials, inexperienced healthy subjects accomplished the task within 5.9 s, and most failed trials were caused by a lack of experience in fine grasping. In addition, in about 1.5% of trials, the subjects also successfully transferred the objects but with a non-optimal grasp type. In 97.0% of the trials, the subjects spent ~1.3 s switching the optimal grasp types. A higher success rate in grasp type (99.1%) for the untrained patient has been observed thanks to more trials conducted. In 98.7 % of trials, the patient only needed another 2 s to control the hand to grasp the object after switching to the optimal grasp type. The tests demonstrate the control capability of the new system in multi-DOF prosthetics, and all inexperienced subjects were able to master the operation of the i-MYO quickly within a few pieces of training and apply it easily.
