collaborators

10 papers

cs.LG2025

Investigating the Generalizability of ECG Noise Detection Across Diverse Data Sources and Noise Types

Sharmad Kalpande, Nilesh Kumar Sahu, Haroon Lone

Electrocardiograms (ECGs) are vital for monitoring cardiac health, enabling the assessment of heart rate variability (HRV), detection of arrhythmias, and diagnosis of cardiovascula…

cs.CL2025

Leveraging language models for summarizing mental state examinations: A comprehensive evaluation and dataset release

Nilesh Kumar Sahu, Manjeet Yadav, Mudita Chaturvedi +2

Mental health disorders affect a significant portion of the global population, with diagnoses primarily conducted through Mental State Examinations (MSEs). MSEs serve as structured…

cs.CL2025

An Offline Mobile Conversational Agent for Mental Health Support: Learning from Emotional Dialogues and Psychological Texts with Student-Centered Evaluation

Vimaleswar A, Prabhu Nandan Sahu, Nilesh Kumar Sahu +1

Mental health plays a crucial role in the overall well-being of an individual. In recent years, digital platforms have increasingly been used to expand mental health and emotional…

cs.HC2025

Exploring Heart Rate Variability and Heart Rate Dynamics Using Wearables Before, During, and After Speech Activity: Insights from a Controlled Study in a Low-Middle-Income Country

Nilesh Kumar Sahu, Snehil Gupta, Haroon R. Lone

Conventional methods for diagnosing Social Anxiety Disorder (SAD), such as clinical interviews and self-reported questionnaires, often face accessibility barriers and subjective bi…

eess.SP2025

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…

cs.LG2025

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…