Recognizing social gestures with a wrist-worn smartband

摘要

The ability to recognize social gestures opens the door for the development of enhanced pervasive computing applications that are responsive to users' social interactions. In this paper, we explore the feasibility of using a smartband for social gesture recognition. We apply logistic regression, a supervised machine learning technique, to accelerometer data collected in a study of 32 users performing 12 social gestures. Our experimental results show promise for recognizing social gestures with a smartband; our simple approach achieves an average accuracy of 86% for classification of social gestures.