# SCH: INT: AURA - Connecting Audio and Radio Sensing Systems to lmprove Care at Home

> **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $309,026

## Abstract

An effective care transition from hospital to home is crucial to ensure optimal care for high-risk patients
 and to reduce the cost of avoidable readmissions that burdens the healthcare system. A common practice
in technology-assisted care transition is to train and guide patients and family caregivers through the web
and mobile phone-based systems for symptom reporting, vital signs monitoring, and providing feedback.
Although effective, these systems have three major limitations: (a) the patient or caregiver has to actively
 measure and enter data into the system-which is error-prone, subjective, and often forgotten; (b) web or
mobile-based interactions can be cumbersome and demanding-tasks like entering data, knowing health
 status, or getting and responding to an alert require typing and clicking through a series of forms/web
pages; and (c) feedback from the system through messages and notifications is often ineffective and
 unnoticed. To overcome these limitations, this project employs a data-driven approach to develop a
voice-enabled, context-aware, post-treatment self-care system in home settings. The proposed system
 will (a) monitor specific activities of a patient at home using advanced WiFi radio signal-based human
 activity recognition algorithms; (b) tailor natural language responses of voice assistants like Amazon
Echo/Alexa based on the patient's location, activity, and health history; and (c) automate data-entry and
reporting to reduce patient or caregiver burden. The system will be deployed in 40 colorectal and bladder
 cancer patients' homes for assessing usability, feasibility, and preliminary magnitude of benefits.
The overarching goals of this project are aligned with the NLM's 10-year strategic plan for 2017-2027.
Through automated collection, linking, curation, and modeling of voice and WiFi radio sensor data, this
project will create an interconnected ecosystem of digital biomarkers that explain, influence, and predict
health outcomes during care transition. By using low-cost voice assistants (less than $50) and ubiquitous
home WiFi, it maximizes the dissemination and engagement of data-powered health to mass population.
To foster the development of a data-ready workforce for the future, three Ph.D. students will work in this
multidisciplinary project, a new mHealth course will be developed, and open science practices will be
applied during the development, deployment, and dissemination phases of the project.

## Key facts

- **NIH application ID:** 10409196
- **Project number:** 3R01LM013329-03S1
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Shahriar Nirjon
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $309,026
- **Award type:** 3
- **Project period:** 2019-09-10 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10409196

## Citation

> US National Institutes of Health, RePORTER application 10409196, SCH: INT: AURA - Connecting Audio and Radio Sensing Systems to lmprove Care at Home (3R01LM013329-03S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10409196. Licensed CC0.

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