Low Power Ultrasonic Gesture Recognition for Mobile Handsets

Abstract

A novel approach for gesture recognition on mobile handsets which does not require any additional transducers is presented. The method is based on transmitting ultrasonic pulses from the earpiece and the loudspeaker and receiving with two microphones, usually located at the top and the bottom of the handset. Signal to Noise Ratio estimates are computed from the reflected signals on each microphone from which statistical moments are extracted and used for training a Support Vector Machine classifier along with hyperparameter optimization. The accuracy achieved is 77.5% on a database of 400 observations using 5-fold cross-validation.