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

Area of Science:

• Human-Computer Interaction (HCI)
• Ergonomics
• Biomechanical Modeling

Background:

• Gestures are a key interaction mode in HCI.
• Existing gesture interaction methods face challenges balancing user comfort and measurement precision.
• Optimizing gestures is crucial for improving user experience and efficiency.

Purpose of the Study:

• To propose a multi-objective optimization method to resolve the conflict between gesture comfort and measurement precision.
• To develop a comfort model (CS) that simulates energy expenditure and predicts fatigue/injury risk.
• To introduce a measurement precision model (ΔPH) to evaluate interaction efficiency.

Main Methods:

• Developed a multi-objective optimization method using the objective function JCP.
• Created a comfort model (CS) considering 17 muscles and 6 degrees of freedom.
• Calculated a measurement precision model (ΔPH) based on calibration errors.
• Performed modeling and simulation to analyze the optimization method's effectiveness.

Main Results:

• The proposed comfort model (CS) effectively simulates energy expenditure and identifies high-risk movements.
• The measurement precision model (ΔPH) provides an evaluation of gesture interaction efficiency.
• The objective function JCP successfully compromises inconsistencies between comfort (JCS) and precision (JPH).

Conclusions:

• The multi-objective optimization method improves gesture design by enhancing ergonomics and operational efficiency.
• Usability testing confirmed the effectiveness of the proposed gesture optimization approach.
• This method offers a valuable tool for designing more comfortable and precise gesture interactions.