5 papers
MoodCam: Mood Prediction Through Smartphone-Based Facial Affect Analysis in Real-World Settings
Rahul Islam, Tongze Zhang, Sang Won Bae
MoodCam introduces a novel method for assessing mood by utilizing facial affect analysis through the front-facing camera of smartphones during everyday activities. We collected fac…
MoodPupilar: Predicting Mood Through Smartphone Detected Pupillary Responses in Naturalistic Settings
Rahul Islam, Tongze Zhang, Priyanshu Singh Bisen +1
MoodPupilar introduces a novel method for mood evaluation using pupillary response captured by a smartphone's front-facing camera during daily use. Over a four-week period, data wa…
FacePsy: An Open-Source Affective Mobile Sensing System -- Analyzing Facial Behavior and Head Gesture for Depression Detection in Naturalistic Settings
Rahul Islam, Sang Won Bae
Depression, a prevalent and complex mental health issue affecting millions worldwide, presents significant challenges for detection and monitoring. While facial expressions have sh…
Revolutionizing Mental Health Support: An Innovative Affective Mobile Framework for Dynamic, Proactive, and Context-Adaptive Conversational Agents
Rahul Islam, Sang Won Bae
As we build towards developing interactive systems that can recognize human emotional states and respond to individual needs more intuitively and empathetically in more personalize…
PupilSense: Detection of Depressive Episodes Through Pupillary Response in the Wild
Rahul Islam, Sang Won Bae
Early detection of depressive episodes is crucial in managing mental health disorders such as Major Depressive Disorder (MDD) and Bipolar Disorder. However, existing methods often…