# Deep learning for algorithmic detection of pulmonary hypertension using a combined digital stethoscope and single-lead electrocardiogram

> **NIH NIH R44** · EKO DEVICES, INC. · 2022 · $786,974

## Abstract

Abstract
This SBIR Direct to Phase II project will develop a deep learning-based clinical decision support
algorithm for screening and detecting pulmonary hypertension (PH) using phonocardiogram and
electrocardiogram data recording using the Eko DUO Digital Stethoscopes. The screening tool
will help to decrease the number of patients with pulmonary hypertension that remain
undertreated simply because their condition is not diagnosed. The gold standard diagnostic for
pulmonary hypertension is right heart catheterization which is costly, invasive, and requires
specialized personnel.To address these challenges, Eko developed the DUO, a digital
stethoscope in a handheld form factor with built-in single lead electrocardiogram. The DUO is
designed to stream digitized phonocardiograms and electrocardiograms to a smartphone, tablet
or personal computer. There, the signal can be analyzed with the decision support algorithm we
developed as part of this project. The specific aims of this study are : (1) build a database of
matched ECG/PCG recording labeled against right heart catheterization and echocardiograms,
and (2) develop and clinically test a deep learning algorithm that can detect PH and stratify its
severity. By integrating this deep learning algorithm into Eko’s mobile and cloud software
platform, we anticipate this algorithm will enable more accurate screening for pulmonary
hypertension in adult patients, leading to earlier diagnosis and better patient outcomes.

## Key facts

- **NIH application ID:** 10547726
- **Project number:** 1R44HL166025-01
- **Recipient organization:** EKO DEVICES, INC.
- **Principal Investigator:** Gaurav Choudhary
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $786,974
- **Award type:** 1
- **Project period:** 2022-09-15 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10547726

## Citation

> US National Institutes of Health, RePORTER application 10547726, Deep learning for algorithmic detection of pulmonary hypertension using a combined digital stethoscope and single-lead electrocardiogram (1R44HL166025-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10547726. Licensed CC0.

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