34 citations · 42 across the 5 of their papers we have counts for
5 papers
Rare Life Event Detection via Mobile Sensing Using Multi-Task Learning
Arvind Pillai, Subigya Nepal, Andrew Campbell
Rare life events significantly impact mental health, and their detection in behavioral studies is a crucial step towards health-based interventions. We envision that mobile sensing…
Using Mobile Data and Deep Models to Assess Auditory Verbal Hallucinations
Shayan Mirjafari, Subigya Nepal, Weichen Wang +1
Hallucination is an apparent perception in the absence of real external sensory stimuli. An auditory hallucination is a perception of hearing sounds that are not real. A common for…
A Survey of Passive Sensing for Workplace Wellbeing and Productivity
Subigya K. Nepal, Gonzalo J. Martinez, Arvind Pillai +9
The modern workplace is undergoing a radical transformation, driven by technological advances that blur the boundaries between human capability and digital augmentation. At the for…
Patient-independent Schizophrenia Relapse Prediction Using Mobile Sensor based Daily Behavioral Rhythm Changes
Bishal Lamichhane, Dror Ben-Zeev, Andrew Campbell +9
A schizophrenia relapse has severe consequences for a patient's health, work, and sometimes even life safety. If an oncoming relapse can be predicted on time, for example by detect…
Routine Clustering of Mobile Sensor Data Facilitates Psychotic Relapse Prediction in Schizophrenia Patients
Joanne Zhou, Bishal Lamichhane, Dror Ben-Zeev +2
We aim to develop clustering models to obtain behavioral representations from continuous multimodal mobile sensing data towards relapse prediction tasks. The identified clusters co…