# HomePal: Developing a Smart Speaker-Based System for In-Home Loneliness Assessment for Older Adults

> **NIH NIH R21** · VIRGINIA COMMONWEALTH UNIVERSITY · 2024 · $22,602

## Abstract

Project Abstract
 Experiences of loneliness are prevalent among older adults. Loneliness is a painful and pernicious
state occurring when there is a perceived discrepancy between one’s optimal levels of social interactions and
actual social relationships. Given that loneliness has been associated with negative health outcomes, detection
measures are imperative to identify both lonely and at-risk individuals early enough to intervene before adverse
health outcomes occur. However, the assessment of loneliness is challenging due to the stigma of being
labeled as lonely and the lack of integration of loneliness assessments into primary care or community-based
services. To tackle the problem, we will use smart speakers and passive sensing data to automatically assess
older adults’ level of loneliness as correlates of self-report scores on the UCLA Loneliness Scale. Our goal in
this project is to develop, deploy, and validate a smart speaker-based system for in-home loneliness
assessment that integrates Internet of Things (IoT) devices to gather both speech (acoustic and prosodic
features) and behavioral data (e.g., smart speaker use patterns, in-home mobility, sleep) from older adults. We
will enroll 70 individuals (age 65+) living alone in the community to collect digital biomarker data continuously
for 3 months. The specific aims are to: (1) Develop an innovative remote loneliness assessment system that
allows passive and unobtrusive capture of speech and behavioral data in the home setting; (2) Using a train-
test approach, develop and evaluate the performance of novel multi-class machine learning (ML) algorithms—
semi-supervised type of Generative Adversarial Networks (SGANs) — to estimate older adults’ loneliness
scores. The UCLA Loneliness Scale will be completed by participants every two weeks for 3 months to collect
ground truth data; and (3) Identify potential implementation barriers to the effective use of the system among
older adults (n=30). In particular, we will assess potential privacy and security concerns, social influence,
cultural values, and the level of personification of virtual agents that could influence the adoption and use of the
system. The novel ML models will allow us to identify not only “already” lonely individuals but also “at-risk”
individuals. The proposed research seeks to provide preliminary evidence that digital biomarkers from smart
speakers and IoT devices can be used for automatic loneliness assessment in the community. Results from
this study will support our long-term goal of implementing the system longitudinally as a platform for real-time
loneliness assessment and detection. This work will provide an opportunity to examine associations between
digital speech and behavioral data and self-report measures of loneliness to identify modifiable risk factors that
will inform the design of interventions to prevent adverse health impacts of loneliness and improve social well-
being among the older adult population.

## Key facts

- **NIH application ID:** 10911363
- **Project number:** 5R21AG083414-02
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** Jane Chung
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $22,602
- **Award type:** 5
- **Project period:** 2023-09-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10911363

## Citation

> US National Institutes of Health, RePORTER application 10911363, HomePal: Developing a Smart Speaker-Based System for In-Home Loneliness Assessment for Older Adults (5R21AG083414-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10911363. Licensed CC0.

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