Towards successful user interaction with systems: focusing on user-derived gestures for smart home systems

Area of Science:

• Human-Computer Interaction
• Usability Engineering
• Gesture Recognition

Background:

• Previous gesture command research often uses frequency ratios to identify popular user gestures.
• This method may be limited as users select from a constrained set of imagined gestures.
• The selected gesture might not represent the truly optimal or most intuitive choice.

Purpose of the Study:

• To investigate if users maintain their initially selected gestures after exposure to others' gestures.
• To determine the reliability of frequency-based methods in identifying optimal gesture commands.
• To explore the dynamic nature of user gesture preferences.

Main Methods:

• Conducted two experiments with the same participants to observe gesture maintenance after viewing other gestures.
• Performed a third experiment with new participants to validate gesture changes observed between the first two experiments.
• Analyzed gesture selection patterns and frequency ratios across experiments.

Main Results:

• A significant 66% of top-ranked gestures differed between the first two experiments involving the same participants.
• Gestures selected in the third experiment, with new participants, showed similarity to those from the second experiment.
• This suggests user gesture preferences are not static and can be influenced by external observation.

Conclusions:

• Frequency-based selection alone is insufficient to guarantee the most popular or optimal gesture commands.
• User gesture selection is dynamic and influenced by exposure to alternative gestures.
• Future gesture command design should consider iterative refinement and user observation to identify truly preferred gestures.