Sign sentence recognition with smart watches

We present a smartwatch application that recognizes important sign sentences. We make use of modern smart watches like Samsung Gear that are equipped with inbuilt sensors including accelerometer, gyroscope and magnetometer. We show how well a smartwatch can recognize important sign sentences. We have implemented a smartwatch app that collects 3d accelerometer and 3d gyroscope data from the watch. We have recorded 8 questions and 13 sentences from 5 people who are fluent in sign language. We use dynamic time warping to compute the distances between the gestures and templates in all data dimensions. The resulting distances serve as input for discriminating the gestures. We evaluated the discriminative ability of logistic regression. In person-independent evaluations, we achieve discrimination accuracies between 85.7% and 97.6%.