The SSJ framework: Augmenting social interactions using mobile signal processing and live feedback

Abstract

Thanks to recent technological advancements, powerful computers and versatile sensor arrays can now be integrated in small wearable devices. This paper introduces the Android framework SSJ, which makes use of such devices to augment social interaction. To this end, sensor data is first used to analyze the user's behavior in realtime. Based on the analysis, SSJ then sends live multimodal feedback to the user while they participate in a social interaction. With the help of advanced feedback strategies, SSJ can minimize the disruption of the social interaction while still helping the user improve the quality of their behavior.