# Bilateral Acoustic Sensing and Automated Breathing Segmentation for Remote Monitoring of Patients with COPD: A Longitudinal Study

> **NIH NIH R44** · LASARRUS CLINIC AND RESEARCH CENTER, INC. · 2024 · $498,638

## Abstract

Bilateral Acoustic Sensing and Automated Breathing Segmentation for Remote
 Monitoring of Patients with COPD: A Longitudinal Study
Abstract: This SBIR Fast-Track project complies with NIH NOSI number NOT-OD-21-100, focusing on a
novel mobile health system for remote monitoring of chronic obstructive pulmonary disease (COPD) using a
wearable multimodal sensor. COPD is the third leading cause of death globally, with over 3 million fatalities and
an annual cost of $52 billion in the U.S. In partnership with the Johns Hopkins Clinical Research Network
(JHCRN), this project aims to provide innovative technology to underserved patients in the Mid-Atlantic region.
Aligning with the NIH's emphasis on improving patient adherence, the project centers on enhancing adherence to
remote monitoring and early symptom recognition to reduce COPD readmissions and healthcare costs.
 COPD symptoms include dyspnea, coughing, and sputum production. The current 23% readmission rate
poses a significant burden on the healthcare system. Early symptom detection can facilitate home treatment,
reducing readmissions and costs. Standard lung function assessments require medical expertise and are not suited
for continuous, remote monitoring. Early detection of deteriorating lung function enables timely intervention and
management of COPD severity.
 This project extends our Intel award-winning, patented wireless WearME system to capture physiologic
baselines and potential acute changes in COPD patients. WearME uses a body area sensor network with
multimodal sensing capabilities, such as digital stethoscope, body kinematics, and electrocardiogram. We will
explore our sensing modalities to capture bilateral biomarkers and changes in lung function, respiration period,
and user activity.
 In Phase I, we will assess lung function and user respiration in real-time during activities of daily living
(ADL), like walking and stair climbing, in an in-clinic cross-sectional study. The goal is to evaluate patients'
physical function and ability to perform ADL for the Phase II longitudinal study. In Phase II, we will validate our
WearME system through remote monitoring, usability, and adherence studies, associating changes in biomarkers
with ADL. To ensure high adherence rates, strategies such as push notifications, patient engagement programs,
and incentives will be implemented. For patients who do not own a suitable smartphone, we are prepared to
provide a loaner device for the duration of their participation in the study. The revised proposal emphasizes the
unique advantages of the WearME-Pro system over traditional hand-held spirometers. Unlike hand-held
spirometers that provide only intermittent data, our wearable device provides a more comprehensive picture of a
patient's respiratory health over time. The device also captures cough frequency, a known precursor to
exacerbations. Such continuous monitoring enables healthcare providers to track changes in the patient's
respiratory condition...

## Key facts

- **NIH application ID:** 10917640
- **Project number:** 1R44HL172444-01A1
- **Recipient organization:** LASARRUS CLINIC AND RESEARCH CENTER, INC.
- **Principal Investigator:** Lloyd Emokpae
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $498,638
- **Award type:** 1
- **Project period:** 2024-09-20 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10917640

## Citation

> US National Institutes of Health, RePORTER application 10917640, Bilateral Acoustic Sensing and Automated Breathing Segmentation for Remote Monitoring of Patients with COPD: A Longitudinal Study (1R44HL172444-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10917640. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*