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Exploring Uni-manual Around Ear Off-Device Gestures for Earables

Shaikh Shawon Arefin Shimon, Ali Neshati, Junwei Sun, Qiang Xu, Jian Zhao

TL;DR

The paper tackles the input space limitation of earables by investigating uni-manual around-ear gestures and segmenting the surrounding interaction space into multiple regions to enable gesture reuse. Through a 2-space (on-skin vs mid-air) × 3-region-count × 7-gesture within-subject study (n=18, 7,560 data points) collected with a Vicon system, it analyzes gesture time, path length, and accuracy, along with NASA-TLX workload and region-preference feedback. Key findings show a performance threshold at roughly 3 mid-air regions and 5 on-skin regions, with mid-air gestures being faster but generally less accurate as regions increase, while on-skin gestures offer higher accuracy aided by tactile feedback. The study provides practical design guidelines, recommending region placements near the cheekbone for on-skin and the temple-to-cheek area for mid-air, while cautioning against eyes and top/back-of-head regions, thereby informing future earable gesture vocabularies and commercialization efforts.

Abstract

Small form factor limits physical input space in earable (i.e., ear-mounted wearable) devices. Off-device earable inputs in alternate mid-air and on-skin around-ear interaction spaces using uni-manual gestures can address this input space limitation. Segmenting these alternate interaction spaces to create multiple gesture regions for reusing off-device gestures can expand earable input vocabulary by a large margin. Although prior earable interaction research has explored off-device gesture preferences and recognition techniques in such interaction spaces, supporting gesture reuse over multiple gesture regions needs further exploration. We collected and analyzed 7560 uni-manual gesture motion data from 18 participants to explore earable gesture reuse by segmentation of on-skin and mid-air spaces around the ear. Our results show that gesture performance degrades significantly beyond 3 mid-air and 5 on-skin around-ear gesture regions for different uni-manual gesture classes (e.g., swipe, pinch, tap). We also present qualitative findings on most and least preferred regions (and associated boundaries) by end-users for different uni-manual gesture shapes across both interaction spaces for earable devices. Our results complement earlier elicitation studies and interaction technologies for earables to help expand the gestural input vocabulary and potentially drive future commercialization of such devices.

Exploring Uni-manual Around Ear Off-Device Gestures for Earables

TL;DR

The paper tackles the input space limitation of earables by investigating uni-manual around-ear gestures and segmenting the surrounding interaction space into multiple regions to enable gesture reuse. Through a 2-space (on-skin vs mid-air) × 3-region-count × 7-gesture within-subject study (n=18, 7,560 data points) collected with a Vicon system, it analyzes gesture time, path length, and accuracy, along with NASA-TLX workload and region-preference feedback. Key findings show a performance threshold at roughly 3 mid-air regions and 5 on-skin regions, with mid-air gestures being faster but generally less accurate as regions increase, while on-skin gestures offer higher accuracy aided by tactile feedback. The study provides practical design guidelines, recommending region placements near the cheekbone for on-skin and the temple-to-cheek area for mid-air, while cautioning against eyes and top/back-of-head regions, thereby informing future earable gesture vocabularies and commercialization efforts.

Abstract

Small form factor limits physical input space in earable (i.e., ear-mounted wearable) devices. Off-device earable inputs in alternate mid-air and on-skin around-ear interaction spaces using uni-manual gestures can address this input space limitation. Segmenting these alternate interaction spaces to create multiple gesture regions for reusing off-device gestures can expand earable input vocabulary by a large margin. Although prior earable interaction research has explored off-device gesture preferences and recognition techniques in such interaction spaces, supporting gesture reuse over multiple gesture regions needs further exploration. We collected and analyzed 7560 uni-manual gesture motion data from 18 participants to explore earable gesture reuse by segmentation of on-skin and mid-air spaces around the ear. Our results show that gesture performance degrades significantly beyond 3 mid-air and 5 on-skin around-ear gesture regions for different uni-manual gesture classes (e.g., swipe, pinch, tap). We also present qualitative findings on most and least preferred regions (and associated boundaries) by end-users for different uni-manual gesture shapes across both interaction spaces for earable devices. Our results complement earlier elicitation studies and interaction technologies for earables to help expand the gestural input vocabulary and potentially drive future commercialization of such devices.
Paper Structure (33 sections, 15 figures, 9 tables)

This paper contains 33 sections, 15 figures, 9 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Gesture Recognition Support and Device Format for Earables
  4. Interaction Space Segmentation for Gestural Input Devices
  5. Methodology
  6. Research Questions
  7. Experimental Variables and Hypotheses
  8. Experiment
  9. Participants
  10. Apparatus
  11. Design
  12. Procedure
  13. Phase 1: Head Model Generation
  14. Phase 2: Gesture Data Collection
  15. Quantitative Results
  16. ...and 18 more sections

Figures (15)

  • Figure 1: Reusing gestures at different regions for off-device Earable interaction: (a) Off-device, around-ear and on-skin taps at 3 distinct gesture regions. (b) Potential gesture regions with highlighted boundaries.
  • Figure 2: Experimental setup with Vicon: the participant is performing gestural tasks shown on the screen
  • Figure 3: (a) Collection of original reference points on the face using GRDA for head reconstruction. (b) The location of 21 original reference points on the face. (c) Snapshot of GRDA with a reconstructed head model.
  • Figure 4: Performance metrics for mid-air and on-skin gestures with 95% confidence intervals. Number of regions around the ears have been ignored.
  • Figure 5: Performance metrics for mid-air and on-skin gestures across all numbers of gesture regions around the ear with 95% confidence intervals.
  • ...and 10 more figures