Powered prosthetic hands are becoming increasingly functional through sensory feedback. However, when using electrical stimulation as sensory feedback for electromyographic (EMG) prosthetics, stimulation artifacts may cause EMG data noise. Electrical stimulation and EMG measurements are therefore performed using time-division methods in rehabilitation facilities. Under time-division methods, EMG levels cannot be acquired at the stimulation time. Highly functional prosthetic hands that can estimate grip force, however, use advanced signal processing and require detailed EMG information. EMG measuring cycle expansion may make grip force estimation unstable. We therefore developed a grip force estimation system using muscle stiffness and EMG as the estimation source signals. The estimation system consists of a muscle stiffness sensor, an EMG sensor and an estimation algorithm. We chose a tray holding task for the system evaluation. A weight is dropped on the tray and subjects are expected to control the tray's attitude. Grip force, EMG, and muscle stiffness are measured, and the measured and estimated grip forces are compared. The proposed algorithm estimates grip force with an error of just 18[N], which is 30% smaller than in EMG-only methods. The system response time is lower than human mechanical reaction time, validating the effectiveness of the proposed method.

Surgical robots have undergone considerable improvement in recent years, but the intuitive operability, representing user inter-operability, has not been quantitatively evaluated. Thus, we propose a method for measuring brain activity to determine intuitive operability in order to design a robot with intuitive operability. The objective of this paper is to clarify the angle between the endoscope and the manipulator that facilitates users perceiving the manipulator as part of their body. In the experiments, while subjects controlled the hand controller to position the tip of the virtual slave manipulator on the target in the surgical simulator, we measured the brain activity through brain imaging devices. We carried out the experiment a number of times with the virtual slave manipulator configured in a variety of ways. The results show that activation of the brain is significant with the slave manipulator configured such that the angles are slanted with respect to the horizontal. We conclude that the body image affects hand-eye coordination, which is related to visual and somatic sense feedback.