A model for predicting pointing time in an eye-gaze input system using three basic phases of cursor movement...

Area of Science:

• Human-Computer Interaction (HCI)
• Human Factors Engineering
• Computer Science

Background:

• Eye-gaze input systems offer an alternative interaction method.
• Predicting pointing time is crucial for designing efficient and reliable human-computer interfaces (HCI).
• Existing models like Fitts' law have limitations in accurately predicting pointing time for eye-gaze systems.

Purpose of the Study:

• To propose a novel multi-part model for predicting pointing time in eye-gaze input systems.
• To enhance the accuracy of pointing time predictions by considering different movement phases.
• To provide a more effective tool for the design and evaluation of eye-gaze based HCI.

Main Methods:

• Classified cursor movement into three distinct phases: latency response, ballistic eye movement, and homing eye movement.
• Analyzed the influence of movement direction, target size, and movement distance on the duration of each phase.
• Developed a predictive model based on the identified characteristics of each movement phase.

Main Results:

• The latency response phase was influenced by movement direction but not target size or distance.
• The ballistic eye movement phase duration was independent of movement direction and target size.
• The homing eye movement phase was affected by both target size and movement direction.
• The proposed model achieved a prediction accuracy (R²) greater than 0.9, outperforming the traditional Fitts' model.

Conclusions:

• The proposed multi-part model accurately predicts pointing time in eye-gaze systems by accounting for distinct movement phases.
• This model offers a significant improvement over traditional methods, contributing to more effective HCI design and evaluation.
• The findings are essential for developing robust and user-friendly eye-gaze interaction technologies.