Transforming Patient Care with Ardas' AI-Powered Stethoscope
Thanks to our Silver Sponsor Ardas for this thought leadership article outlining best practices for startup development:
Ardas’ case on data-driven patient care:
AI-powered stethoscope system
AI has entered and drastically changed all areas of our life, and healthcare is not an exception. The telemedicine boom, wearable devices, smart IoT solutions, and data-driven solutions—these are just some of the key trends in healthtech in 2024. You may now be thinking: how to create a healthcare product that will fit the market well?
In this article, Ardas healthtech professionals will share the results of one of their impact projects—an AI-powered IoT stethoscope system for healthcare providers.
This piece follows Ardas' previous article on how AI is transforming the startup ecosystem.
How it Works: an AI-powered IoT Stethoscope System
In 2021, the team took on a challenge to create an AI-powered stethoscope system, benefitting both patients and healthcare specialists. Here is the story behind the project:
About IoT Device
A Smart Stethoscope is a portable medical device designed for auscultation. It allows healthcare providers to record, store, play, and analyze sounds from patient organs. It also features heart rate measurement capabilities. The device's functionality can be extended by connecting it to a mobile app and the cloud.
Packed with AI, the Smart IoT Stethoscope uses a neural network algorithm that processes a range of data to identify auscultation sounds. When the AI feature is enabled, the system displays the recognition result on the screen once the auscultation is completed. The result is also announced through the headset.
The device also seamlessly connects to mobile apps and the cloud, offering enhanced features. It uses WiFi as its communication channel, functioning as a WiFi access point.
Team’s Role
Ardas' role was to develop a comprehensive software solution and AI model and ensure their seamless integration with an IoT stethoscope device created by an external team. This included a mobile app for data synchronization and AI analysis, a web app for secure data management, and a real-time AI model for sound analysis. Ardas provided a cloud-based backend for secure data storage. Through close collaboration with the device team, Ardas delivered a secure solution to enhance diagnostic accuracy and uplift patient care for healthcare professionals.
This AI stethoscope system is set to become a comprehensive healthtech IoT solution that facilitates collaborative care.
The Goal of the Project
The client wanted to create an AI-powered stethoscope system that modernizes patient diagnostics. This IoT healthcare solution was meant to leverage AI to analyze heart and lung sounds to support early detection of potential diseases and enhance care.
Ardas’ Core Challenges
The team navigated a couple of critical challenges for the project to succeed:
Regulatory compliance. The system was designed to comply with FDA Class II, HIPAA, and GDPR standards, ensuring the highest levels of regulatory adherence. Healthcare data interoperability is maintained through HL7 FHIR standards.
Data security. Ardas offered to implement end-to-end encryption and secure data storage. However, the client chose a different approach—anonymizing patient data (instead of storing full names, we only store a patient ID, which the doctor separately records in their medical log).
Performance. The project achieved fast response times and 99.9% uptime, with built-in scalability to support up to 10,000 concurrent users without performance degradation.
Adaptability. Ardas ensured the solution was adaptable to a wide range of healthcare environments, including offline functionality for areas with limited or no connectivity.
Noise filtering and model refinement. The project's AI model relies on diverse, high-quality data. A key challenge Ardas faced was that the device records constantly modified sounds (such as heartbeats overlaid with external noise). The team is training the system to filter out extraneous sounds and provide accurate diagnoses, even with a heterogeneous dataset. That’s why the machine learning model is constantly being refined to meet the target accuracy rate of over 85%.
The Team & Stack
Ardas’ journey with this project started in 2021, leading to product development in 2022, followed by a pause. Work resumed in 2024 to allow time for FDA certification. Plus, during this time, Ardas assembled a skilled hardware team with hands-on expertise.
The team consisted of backend, frontend, mobile, DevOps, UI/UX, QA, data scientists, business analysts, and project managers. They collaborated with external hardware experts to create an end-to-end IoT healthcare solution.
The technical stack included React Native, React.js, Node.js, TensorFlow, and PyTorch.
System’s Key Solutions
The AI-powered stethoscope system is equipped with all the modern features healthcare providers require. Let’s review them in brief: …
Read the rest of this article at STARTUPEVENTS.ORG…
Want to share your news or advice for startup entrepreneurs? Submit a Guest Post here.
Ready for more startup news, free expert advice, and events? Choose from 7 free email newsletters to help grow your business and join the Startup Council FREE here now: https://StartupCouncil.org/joinsc