A Gesture Elicitation Study of Nose-Based Gestures

Area of Science:

• Human-Computer Interaction
• Wearable Technology
• Biomedical Engineering

Background:

• Miniaturized sensors in wearables enable recognition of human body movements.
• Electrooculography sensors in smart glasses can detect finger movements on the nose.
• Nose-based gestures offer a novel interaction modality for wearable devices.

Purpose of the Study:

• To explore the interaction capabilities of nose-based gestures.
• To conduct a gesture elicitation study to identify user-preferred nose gestures for Internet-of-Things (IoT) tasks.
• To establish a taxonomy and consensus set of nose-based gestures for HCI research.

Main Methods:

• A between-subjects gesture elicitation study involving 24 participants (12 female, 12 male).
• Participants expressed preferred nose-based gestures for 19 IoT tasks.
• Gestures were classified, clustered into a taxonomy, and analyzed for agreement using Condorcet and de Borda count methods.

Main Results:

• 912 gestures were elicited, clustered into 53 unique gestures and 23 categories.
• A consensus set of 38 final gestures was established, forming a basis for design guidelines.
• Agreement scores and rates were consistent across different measurement methods.
• Inferential statistics revealed no significant gender differences in gesture agreement.

Conclusions:

• A comprehensive taxonomy and consensus set of 38 nose-based gestures were developed.
• Six design guidelines are provided for researchers and practitioners.
• The study confirms the viability of nose-based gestures for wearable HCI and demonstrates gender-neutral user preferences.