{ NeuroPhone: Brain-Mobile Phone Interface using a Wireless EEG Headset Andrew T. Campbell, Tanzeem Choudhury, Shaohan Hu, Hong Lu, Matthew K. Mukerjee ∗, Mashfiqui Rabbi, and Rajeev D. S. Raizada Dartmouth College, Hanover, NH, USA

Motivation

 Control your mobile device without touching or speaking  Make control easier in environment require less movement or silence  library  classroom The narrow version for mobile device

 Control many device in a more effortless way  Determent human emotion for many purpose The generalized version

Terminology

 Electroencephalography  Device that recording electrical activity of brain EEG

 P300 is a pattern of certain electrical brain activity  It is usually happened when people try to reacting to certain thing  Typical representation is the record of EEG have a “delay” for 300 to 600 ms P300

 A way to generalize data, to figure out a pattern. So that we can use the pattern to determent or predict new situation Machine Learning

Y = aX0 + bX1 + cX2 Classification Problem

Test Environment

iPhone

Emotiv EPOC EEG headset

Windows Laptop

Application

P300 Mode

 Similar to P300 mode, but user must winking their eyes Wink mode

Result

P300 Mode

Winking Mode

 The application take very little resource  Which means devices like smart phone could totally hand the brain control system  An acceptable Accuracy Shows

 Algorithm is not perfect yet  High battery consuming  EEG hardware not good enough Limitations

 Expensive  Very little company working in this field  A lot of noise in the information  Too big  Too ugly EEG

EEG

Conclusion

 It is a concept prove application  It proved that brain control on mobile device can be done  The compute unit is powerful enough already  The algorithm can be improve  EEG still need improve

 Question? Thank you