Title: An Automated Tool to Teach Social Engagement Skills for Older Adults
Carefully-designed feedback on automatically-sensed human behavior has been effective in improving important social and cognitive skills. The United Nations estimates there are now 700 million people aged 60 years and over. By 2050 that figure will rise to over 2 billion. In this talk, I will describe a project called “Aging and Engaging,” a web-based conversational skills training system targeted to help the elderly (65+ years). The system allows users to practice conversations and receive feedback on eye contact, speaking volume, smiling, and speech content. Along with providing insights from our exploratory study, I will discuss how our approach could lay the foundation for applications to other healthcare problems.
Ehsan Hoque is an assistant professor of computer science at the University of Rochester, where he leads the Rochester Human-Computer Interaction, or ROC HCI, Group. His group’s research focuses on understanding and modeling unwritten rules of human communication with applications in mental health, business communication, and assessment technologies. Ehsan received his Ph.D. from the Massachusetts Institute of Technology in 2013. Ehsan and his group’s work has received a Best Paper Award at Ubiquitous Computing (UbiComp 2013), Best Paper Honorable Mentions in Automated Face and Gesture Recognition (FG 2011) and Intelligent Virtual Agents (IVA 2006), the MIT Technology Review TR35 Award in 2016, and the Google Faculty Research Award (2014, 2015). Follow the group’s work on Twitter at @rochci.