@inproceedings{ghandeharioun2019emma,
author = {Ghandeharioun, Asma and McDuff, Daniel and Czerwinski, Mary and Rowan, Kael},
title = {EMMA: An Emotion-Aware Wellbeing Chatbot},
booktitle = {International Conference on Affective Computing and Intelligent Interaction},
year = {2019},
month = {September},
abstract = {The delivery of mental health interventions via ubiquitous devices has shown much promise. A conversational chatbot is a promising oracle for delivering appropriate just-in-time interventions. However, designing emotionally-aware agents, specially in this context, is under-explored. Furthermore, the feasibility of automating the delivery of just-in-time mHealth interventions via such an agent has not been fully studied. In this paper, we present the design and evaluation of EMMA (EMotion-Aware mHealth Agent) through a two-week long human-subject experiment with N=39 participants. EMMA provides emotionally appropriate micro-activities in an empathetic manner. We show that the system can be extended to detect a user's mood purely from smartphone sensor data. Our results show that our personalized machine learning model was perceived as likable via self-reports of emotion from users. Finally, we provide a set of guidelines for the design of emotion-aware bots for mHealth.},
url = {http://approjects.co.za/?big=en-us/research/publication/emma-an-emotion-aware-wellbeing-chatbot/},
}