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 JCP to solve the inconsistency between the gesture comfort JCS and measurement precision JPH in the gesture interaction. The proposed comfort model CS 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 CS 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 ∆PH is calculated from the measurement error (∆XH,∆YH,∆ZH) 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 JCS, based on the comfort model CS, and the objective function JPH, based on the measurement precision models ∆PH, the consistency and the difference can be found due to the variation of the radius rB_RHO and the center coordinates PB_RHOxB_RHO,yB_RHO,zB_RHO. The proposed objective function JCP compromises the inconsistency between the objective function JCS and JPH. 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.
Keywords: comfort; gesture interaction; measurement precision; multi-objective optimization.