In this research, a precise on-machine line-profile measuring system that compensates for the motion-error from the linear-guide, which can influence the accuracy of the measurement of the profile was developed. For this purpose, the principle of measuring the system model was used to analyze the compensating motion error component for line-profile and 3 types of MPES method (Integration-Method, the Fourier-Model-Method, and the Sequential-Method). The multi-probe-error-separation-method (MPES) was applied to calculate the motion-error, which in turn was used to compensate for the measured linear-profile of the specimen. Lastly, the simulation conditions involving a multi-probe measurement system consisting of a reference-artifact, capacitive-sensor, and three displacement-sensors were designed and Monte-Carlo simulation was implemented for the evaluation of the 3 types of MPES method. Also, the simulation results obtained from the conventional measuring system and the proposed system were compared for the verification of the performance of the latter. Consequently, efficient compensation of the motion error appeared as possible and the applicability of the multi-probe measurement system was confirmed.

This paper proposes a myoelectric hand prosthesis with an easy control strategy to apply more conveniently with just two EMG sensors. The myoelectric hand prosthesis is composed of a multi-DOF finger mechanism, a controller, and an intuitive control algorithm. The developed hand prosthesis has 6-DOFs and can perform eight hand motions using the intuitive control algorithm. The proposed intuitive control algorithm classifies four grip motions and four gesture motions; we used the thumb position of the hand prosthesis and three EMG signals (Co-contraction, flexion, and extension) generated from the two EMG sensors. From the experimental results, we demonstrated that the proposed myoelectric hand prosthesis is applicable to amputees as a hand prosthesis.