1. Toward Subtle Intimate Interfaces for Mobile Devices Using an EMG Controller Enrico Costanza Media Lab Europe now at MIT Media Lab Samuel A. Inverso Media Lab Europe Rebecca Allen Media Lab Europe

2. Outline Motivation: Subtle and hands-free interaction EMG as a solution An EMG-based controller Design approach Formal user study Conclusion

3. Mobile interaction is often in public spaces Subtle interfaces: do not disrupt the environment Intimate interaction: only for the user Ringing vs. vibrating alert Importance of Subtlety in Mobile Interfaces

4. Speech recognition and evident gesturing can be inappropriate Importance of Subtlety in Mobile Interfaces

5. Design for Hands-free Interaction

6. Eyeglass displays Design for Hands-free Interaction

7. Electrical signal from muscle activity Can measure isometric activity: subtle or no movement Surface Electrodes (EKG-like) Non-contact sensing (future) Electromyogram (EMG) as a Novel Solution

8. Prosthesis control Input devices for disabled users Affect sensing Music expression EMG in CHI (Related Work)

9. EMG and movement are not always related Tanaka & Knapp report this as a limitation We think it is an advantage! EMG and Movement Limitation or Advantage?

10. EMG greatest potential for mobile HCI Sense subtle gestures Example: brief contraction of the bicep Motionless Gestures

11. Self-contained in armband Integration with Bluetooth devices (e.g. Phones and PDAs) No calibration for individual users EMG-based Controller

12. The gesture should be: Natural to perform Different from normal muscle activity User centered iterative approach: 1. Select muscle & generic gesture definition (non-detailed description to subjects) 2. Definition refinement, model and algorithm 3. Tuning Design Process

13. Realistic controlled environment: subjects walked around obstacles in trafficked walkway 10 subjects Audio stimuli and feedback Is training avoidable? (minimal feedback) Push the limit: short and long contractions Formal User Study

14. 96% correct recognition No false positives No training necessary in 7 out of 10 cases Cannot distinguish short and long contractions across different subjects Results

15. EMG can be successfully used (96%) Generally no training required No calibration across users Discussion

16. Cannot distinguish short and long contractions Subjective definition of “short” and “long” Discussion

17. Test in more complex scenarios Measure subtleness Improve algorithm Use more muscles (alphabet definition) Future Work

18. Subtle interaction for mobile devices New reason to use EMG in CHI Motionless gestures It works (96% correct recognition no false positives) Summary and Conclusion