Toward Subtle Intimate Interfaces for Mobile Devices Using an EMG Controller

Toward Subtle Intimate Interfaces for Mobile Devices

Using an EMG Controller

Enrico CostanzaMedia Lab Europenow at MIT Media Lab

Samuel A. InversoMedia Lab Europe

Rebecca AllenMedia Lab Europe

Outline

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

• 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

• Speech recognition and evident gesturing can be inappropriate

Importance of Subtlety in Mobile Interfaces

Design for Hands-free Interaction

Eyeglass displays

Design for Hands-free Interaction

• 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

• Prosthesis control• Input devices for disabled users• Affect sensing• Music expression

EMG in CHI(Related Work)

• EMG and movement are not always related • Tanaka & Knapp report this as a limitation• We think it is an advantage!

EMG and MovementLimitation or Advantage?

• EMG greatest potential for mobile HCI• Sense subtle gestures• Example: brief contraction of the bicep

Motionless Gestures

• Self-contained in armband• Integration with Bluetooth devices

(e.g. Phones and PDAs)• No calibration for individual users

EMG-based Controller

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 algorithm3. Tuning

Design Process

• 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

• 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

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

Discussion

• Cannot distinguish short and long contractions• Subjective definition of “short” and “long”

Discussion

• Test in more complex scenarios• Measure subtleness• Improve algorithm• Use more muscles (alphabet definition)

Future Work

• 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