The Comfort and Measurement Precision-Based Multi-Objective Optimization Method for Gesture Interaction

As an advanced interaction mode, gestures have been widely used for human–computer interaction (HCI). This paper proposes a multi-objective optimization method based on the objective function [Formula: see text] to solve the inconsistency between the gesture comfort [Formula: see text] and measurement precision [Formula: see text] in the gesture interaction. The proposed comfort model [Formula: see text] takes seventeen muscles and six degrees of freedom into consideration based on the data from muscles and joints, and is capable of simulating the energy expenditure of the gesture motion. The [Formula: see text] can provide an intuitive indicator to predict which act has the higher risk of fatigue or injury for joints and muscles. The measurement precision model [Formula: see text] is calculated from the measurement error [Formula: see text] caused by calibration, that provides a means to evaluate the efficiency of the gesture interaction. The modeling and simulation are implemented to analyze the effectiveness of the multi-objective optimization method proposed in this paper. According to the result of the comparison between the objective function [Formula: see text] , based on the comfort model [Formula: see text] , and the objective function [Formula: see text] , based on the measurement precision models [Formula: see text] , the consistency and the difference can be found due to the variation of the radius [Formula: see text] and the center coordinates [Formula: see text]. The proposed objective function [Formula: see text] compromises the inconsistency between the objective function [Formula: see text] and [Formula: see text]. Therefore, the multi-objective optimization method proposed in this paper is applied to the gesture design to improve the ergonomics and operation efficiency of the gesture, and the effectiveness is verified through usability testing.