An Adaptive Muscular Force Generation Mechanism Based on Prior Information of Handling Object

Abstract

Evaluating the influences of human-machine interface (HMI) visual information is vital to developing the user-oriented and human-friendly equipment, robots, etc. We define HMI visual information as prior information, such as size, color, shape, etc. The relationship between prior information and the Kansei feeling is evaluated by surface electromyogram (sEMG). This study deals with object-grasping motion and measures sEMG signals during the motion. Prediction on object-grasping motion is predicted from sEMG signals and defined as Force Prediction (FP). Differences between prediction of HMI operation and actual results are assumed to influence on Kansei feeling concerning the operation. Subjects given different prior information calculate FP about plastic bottles when grasping them. Experimental results show that the FP differs even though the plastic bottles have the same weight. The influence of prior information on FP is visually plotted in a three-dimensional map which is called Size-Color-iEMG map, and its application is to HMI design.

A refinement of Sándor-Tóth's inequality

“…Such applications include solutions to optimal control problems [15], stability analysis [16,17], robotics [18], fuzzy logic [19,20], difference inequalities [21] or differential equations [22], as far as positive integers are concerned.…”