arXiv subjects

Poorvesh Dongre

Publications and source records attributed to Poorvesh Dongre.

5 recordsLinked to original sources

arXiv2026

Exploring Expert Perspectives on Wearable-Triggered LLM Conversational Support for Daily Stress Management

Wearable devices increasingly support stress detection, while LLMs enable conversational mental health support. However, designing systems that meaningfully connect wearable-triggered stress events with generative dialogue remains underexplored, particularly from a design perspective. We present EmBot, a functional mobile application that combines wearable-triggered stress detection with LLM-based conversational support for daily stress management. We used EmBot as a design probe in semi-structured interviews with 15 mental health experts to examine their perspectives and surface early design tensions and considerations that arise from wearable-triggered conversational support, informing the future design of such systems for daily stress management and mental health support.

cs.HC↗

arXiv2025

Wearable Meets LLM for Stress Management: A Duoethnographic Study Integrating Wearable-Triggered Stressors and LLM Chatbots for Personalized Interventions

We use a duoethnographic approach to study how wearable-integrated LLM chatbots can assist with personalized stress management, addressing the growing need for immediacy and tailored interventions. Two researchers interacted with custom chatbots over 22 days, responding to wearable-detected physiological prompts, recording stressor phrases, and using them to seek tailored interventions from their LLM-powered chatbots. They recorded their experiences in autoethnographic diaries and analyzed them during weekly discussions, focusing on the relevance, clarity, and impact of chatbot-generated interventions. Results showed that even though most events triggered by the wearable were meaningful, only one in five warranted an intervention. It also showed that interventions tailored with brief event descriptions were more effective than generic ones. By examining the intersection of wearables and LLM, this research contributes to developing more effective, user-centric mental health tools for real-time stress relief and behavior change.

cs.HC↗

arXiv2024

Systematic Review of Extended Reality for Smart Built Environments Lighting Design Simulations

This systematic literature review paper explores the use of extended reality {(XR)} technology for smart built environments and particularly for smart lighting systems design. Smart lighting is a novel concept that has emerged over a decade now and is being used and tested in commercial and industrial built environments. We used PRISMA methodology to review 270 research papers published from 1968 to 2023. Following a discussion of historical advances and key modeling techniques, a description of lighting simulation in the context of extended reality and smart built environment is given, followed by a discussion of the current trends and challenges.

cs.HC↗

arXiv2024

Integrating Physiological Data with Large Language Models for Empathic Human-AI Interaction

This paper explores enhancing empathy in Large Language Models (LLMs) by integrating them with physiological data. We propose a physiological computing approach that includes developing deep learning models that use physiological data for recognizing psychological states and integrating the predicted states with LLMs for empathic interaction. We showcase the application of this approach in an Empathic LLM (EmLLM) chatbot for stress monitoring and control. We also discuss the results of a pilot study that evaluates this EmLLM chatbot based on its ability to accurately predict user stress, provide human-like responses, and assess the therapeutic alliance with the user.

eess.SP↗

arXiv2023

A Conceptual Framework for Designing Interactive Human-Centred Building Spaces to Enhance User Experience in Specific-Purpose Buildings

Human/User interaction with buildings are mostly restricted to interacting with building automation systems through user-interfaces that mainly aim to improve energy efficiency of buildings and ensure comfort of occupants. This research builds on the existing theories of Human-Building Interaction (HBI) and proposes a novel conceptual framework for HBI that combines the concepts of Human-Computer Interaction (HCI) and Ambient Intelligence (AmI). The proposed framework aims to study the needs of occupants in specific-purpose buildings, which is currently undermined. Specifically, we explore the application of the proposed HBI framework to improve the learning experience of students in academic buildings. Focus groups and semi-structured interviews were conducted among students who are considered primary occupants of Goodwin Hall, a flagship smart engineering building at Virginia Tech. Qualitative coding and concept mapping were used to analyze the qualitative data and determine the impact of occupant-specific needs on the learning experience of students in academic buildings. The occupant-specific problem that was found to have the highest direct impact on learning experience was finding study space and highest indirect impact was Indoor Environment Quality (IEQ). We discuss new ideas for designing Intelligent User Interfaces (IUI), e.g. Augmented Reality (AR), increase the perceivable affordances for building occupants and considering a context-aware ubiquitous analytics-based strategy to provide services that are tailored to address the identified needs.

cs.HC↗