{"id":162644,"date":"2012-01-01T00:00:00","date_gmt":"2012-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/affectaura-an-intelligent-system-for-emotional-memory\/"},"modified":"2020-04-03T13:13:59","modified_gmt":"2020-04-03T20:13:59","slug":"affectaura-an-intelligent-system-for-emotional-memory","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/affectaura-an-intelligent-system-for-emotional-memory\/","title":{"rendered":"AffectAura: An Intelligent System for Emotional Memory"},"content":{"rendered":"
We present AffectAura, an emotional prosthetic that allows users to reflect on their emotional states over long periods of time. We designed a multimodal sensor set-up for continuous logging of audio, visual, physiological and contextual data, a classification scheme for predicting user affective state and an interface for user reflection. The system continuously predicts a user’s valence, arousal and engagement, and correlates this with information on events, communications and data interactions. We evaluate the interface through a user study consisting of six users and over 240 hours of data, and demonstrate the utility of such a reflection tool. We show that users could reason forward and backward in time about their emotional experiences using the interface, and found this useful.<\/p>\n","protected":false},"excerpt":{"rendered":"
We present AffectAura, an emotional prosthetic that allows users to reflect on their emotional states over long periods of time. We designed a multimodal sensor set-up for continuous logging of audio, visual, physiological and contextual data, a classification scheme for predicting user affective state and an interface for user reflection. The system continuously predicts a 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