4 papers
DySTAN: Joint Modeling of Sedentary Activity and Social Context from Smartphone Sensors
Aditya Sneh, Nilesh Kumar Sahu, Snehil Gupta +1
Accurately recognizing human context from smartphone sensor data remains a significant challenge, especially in sedentary settings where activities such as studying, attending lect…
Fairness-Aware Few-Shot Learning for Audio-Visual Stress Detection
Anushka Sanjay Shelke, Aditya Sneh, Arya Adyasha +1
Fairness in AI-driven stress detection is critical for equitable mental healthcare, yet existing models frequently exhibit gender bias, particularly in data-scarce scenarios. To ad…
HCFSLN: Adaptive Hyperbolic Few-Shot Learning for Multimodal Anxiety Detection
Aditya Sneh, Nilesh Kumar Sahu, Anushka Sanjay Shelke +2
Anxiety disorders impact millions globally, yet traditional diagnosis relies on clinical interviews, while machine learning models struggle with overfitting due to limited data. La…
Real-World Receptivity to Adaptive Mental Health Interventions: Findings from an In-the-Wild Study
Nilesh Kumar Sahu, Aditya Sneh, Snehil Gupta +1
The rise of mobile health (mHealth) technologies has enabled real-time monitoring and intervention for mental health conditions using passively sensed smartphone data. Building on…