Yuichiro Honda

A training system for the MyoBock hand in a virtual reality environment

This paper proposes a novel EMG-based MyoBock training system that consistently provides a variety of functions ranging from EMG signal control training to task training. Using the proposed training sytem, a trainee controls a virtual hand (VH) in a 3D virtual reality (VR) environment using EMG signals and position/posture information recorded from the trainee. The trainee can also perform tasks such as holding and moving virtual objects using the system. In the experiments of this study, virtual task training developed with reference to the Box and Block Test (BBT) used to evaluate myoelectric prostheses was conducted with two healthy subjects, who repeatedly performed 10 one-minute tasks involving grasping a ball in one box and transporting it to another. The BBT experiments were also conducted in a real environment before and after the virtual training, with results showing an improvement in the number of tasks successfully completed. It was therefore confirmed that the proposed system could be used for myoelectric prosthesis control training.

A Human Reaching Movement Model for Myoelectric Prosthesis Control

This work was partially supported by a Grant-in-Aid for Young Scientists B Number 26730111.

A virtual myoelectric prosthesis training system capable of providing instructions on hand operations

This article proposes a virtual hand and a virtual training system for controlling the MyoBock—the most commonly used myoelectric prosthetic hand worldwide. As the virtual hand is controlled using the method also adopted for the MyoBock hand, the proposed system provides upper-limb amputees with operation sensibilities similar to those experienced in MyoBock control. It can also display an additional virtual hand for the provision of instructions on hand operation, such as the recommended posture for object grasping and the trajectory desirable to reach a target. In virtual hand control experiments conducted with an amputee to evaluate the proposed virtual hand’s operability, the subject successfully performed stable opening and closing with high discrimination rates (89.3±6.65%), thanks to the virtual hand’s incorporation of the MyoBock’s operational characteristics. A training experiment using the proposed system was also conducted with eight healthy participants over a period of 5 days. The participants were asked to perform the box and block test using the MyoBock hand in a real environment on the first and final days. The results showed that the number of blocks transported in 1 min significantly increased and that the participants using the instruction virtual hand changed the orientation of the hand approaching blocks from vertical to lateral. The outcomes of the experiment indicate that the proposed system can be used to improve MyoBock hand control operation both quantitatively and qualitatively.