Mechanical Energy Expenditure-based Comfort Evaluation Model for Gesture Interaction

Area of Science:

• Human-Computer Interaction (HCI)
• Ergonomics
• Biomechanics

Background:

• Gestures are a key interaction mode in HCI.
• Existing comfort prediction methods often rely on physical measurements like electromyography (EMG).
• There's a need for quantitative, non-invasive methods to assess gesture comfort.

Purpose of the Study:

• To propose a novel comfort evaluation model for gestures in HCI.
• To predict gesture comfort based on mechanical energy expenditure (MEE) and mechanical efficiency (ME).
• To provide an ergonomic indicator for potential joint and muscle fatigue or injury risk.

Main Methods:

• Developed a comfort evaluation model incorporating nineteen muscles and seven degrees of freedom.
• Simulated MEE and ME for both static and dynamic gestures.
• Calculated comfort scores (CSs) by normalizing and weighting MEE and ME.

Main Results:

• The model provides a quantitative comfort value without requiring EMG or other measurement devices.
• It offers an intuitive ergonomic indicator for fatigue and injury risk.
• The proposed model showed distinct results compared to Range of Motion (ROM) and Movement and Gesture Assessment (MMGA) models, particularly for dynamic gestures.

Conclusions:

• The proposed comfort evaluation model effectively predicts gesture comfort and associated ergonomic risks.
• It offers advantages over traditional measurement-based methods and existing models like ROM and MMGA.
• Designers can utilize this model for optimizing gesture design in HCI systems.