USA, 2019 - Present
the team: 5 developers, PM, QA, BA

Smart Stethoscope With AI Usage [Development Case Study]

Smart Stethoscope is the first medical assessment tool of the respiratory and cardiac system that provides immediate, precise-feedback of its findings in a user-friendly way.


Technical stack includes:

Java ReactJS ReactNativeGit AWS PostgreSQL

The history

In 2019, we embarked on an ambitious project to create an AI-powered stethoscope capable of recognizing cardiac and pulmonary sounds. Our journey began with a proof of concept (PoC) that demonstrated the potential of integrating advanced AI models into medical devices. The goal was to revolutionize how doctors interact with and interpret stethoscope data, ultimately improving diagnostic accuracy and patient outcomes.

Our role

Our team played a critical role in every phase of this project, from initial concept to the development of a functional prototype. We focused on building a robust AI model, developing the necessary software for medical professionals to interact with the device, and ensuring compliance with FDA certification requirements. Our comprehensive approach drastically reduced the time and cost associated with bringing this innovative product to market.


Industry: Healthcare




Improved ?

Services Used

marketing automation

Phase 1: Proof of Concept

The initial phase involved creating a basic prototype of the stethoscope, complete with a simple AI model and a mobile application. Our hardware engineers developed a rudimentary device, essentially a box with wires, while the AI model was integrated into a smartphone application.

The stethoscope connected to the mobile app via Bluetooth, allowing doctors to receive real-time analysis of heart and lung sounds directly on their phones. This prototype was used to demonstrate the technology to potential investors.

Phase 2: Product Development

Building on the success of the PoC, we moved to the second phase, which focused on refining the device and its software. Key developments included:

  • Hardware Enhancement: We redesigned the stethoscope, making it more ergonomic and aesthetically pleasing. The AI model was embedded directly into the stethoscope, allowing it to function independently of the mobile app for immediate results.
  • Software Development: We developed two applications – a mobile app and a web app. The mobile app allowed doctors to view AI-generated results, listen to recordings, and edit diagnoses. The web app provided similar functionalities, enabling doctors to upload results from the mobile app and manage patient data more efficiently.

Phase 3: AI Model Improvement

The third phase focused on enhancing the AI model. We faced the challenge of collecting sufficient data to train the model effectively. Our strategy included:

  • Data Collection: We created two distinct models for heart and lung sounds. The heart model needed to categorize sounds into five categories: normal, defect C3, defect C4, murmur, and other anomalies. Each category required 1,000 validated recordings, totaling 5,000 samples.
  • Model Training: We proposed using the smart stethoscope system to gather the necessary data, with validation provided by medical professionals. This iterative process ensured that the dataset remained accurate and comprehensive.

Certification and Compliance

Navigating the FDA certification process was a crucial component of our project. We collaborated with a vendor specializing in FDA compliance to ensure our product met all necessary standards. Key considerations included:

  • Data Validation: We ensured that all recordings used for training the AI model were validated by qualified doctors, even if they were not collected directly by the stethoscope.
  • Documentation: Comprehensive documentation was prepared to demonstrate compliance with FDA requirements, facilitating a smoother certification process.

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