June 21, 2022
Use Cases

How Ademen will use streaming data to revolutionize patient monitoring

Ademen aims to empower community clinical teams to screen for and monitor health problems using the smart stethoscope it built on streaming data with Quix.

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Quix Streams combines an Apache Kafka client with a stream processing library, offering a feature-rich pure Python alternative to the kafka-python library. Deploy on your stack or on Quix Cloud for scalable, stateful and fault-tolerant ETL without the headache of cross-language debugging.

👉 Star the repo on GitHub and pip install quixstreams to get started.

Building a smart stethoscope that uses data for diagnosis

When a small team of four founded Ademen in 2020 to create life-saving products built on streaming data, they knew they’d need some help with data architecture and engineering.

The Warwickshire-based company is at the forefront of a shift in medical technology to “software as a medical device” in which sensor data is processed to identify and report clinical findings. Ademen aims to deliver a smart stethoscope that uses high-frequency streamed data and real-time data processing. The stethoscope ingests the sounds of a patient’s body as data and delivers it to the connected application, which transforms audio into visual information and supports a medical diagnosis.

“We’re taking a familiar medical tool and using new data technologies to empower nurses and doctors to, for example, quickly and correctly triage patients, reducing the number of referrals to specialists,” Dr. Alistair Foster, director of Ademen, says.

Auscultation — the act of diagnosing a patient by listening to their body — can determine information about the heart, lungs, bowel, and, in some instances, blood flow around the body. The problem is that for many conditions, stethoscopes are only effective when used by physicians who have the training and experience to interpret subtle differences in sound. Empowering community clinical teams to screen for and monitor health problems means specialists’ time is better used, and there can be improved communication between patients, nurses, doctors and specialists.

Developing a smart stethoscope requires streaming data and real-time data transformation. A typical data stream may:

  1. Continually acquire data from the smart sensor worn by the patient.
  2. Push the data up to the cloud for processing.
  3. Transform data into clinically relevant findings.
  4. Deliver findings to the medical team’s connected devices.

Medical sensors as IoT devices

The smart sensor works on the same principle as many IoT systems. A device monitors the patient and connects to an app, which brings data to the cloud.

Ademen medical solution diagram.

As soon as the data arrives in the cloud, the Quix platform processes it using Ademen’s digital signal processing and data science models. In the future, these models could even be based on machine learning trained on historic data persisted within Quix.

The results of the transformation from device data to visualizations, and the results from the applied algorithms, are then returned to the app via the Quix API. The app also allows users to listen to the audio signal locally from the device, in much the same way as a traditional stethoscope.

Ademen is understandably tight-lipped when it comes to trials of their technology, but the team did reveal they are working with several clinical groups to detect and monitor conditions that would otherwise require patients to have x-ray or ultrasound scans. During this time, Quix is working with Ademen toward meeting the regulatory standards of the medical sector.

Read about other ways the Quix team sees real-time predictive algorithms as a transformative technology in medicine.

Healthcare for the people: fast, inexpensive and scalable

While collecting data and processing audio signals with algorithms and artificial intelligence in a lab environment is interesting and novel, it won’t have a real-world impact unless it’s economical, timely and guarantees sustainable efficacy.

Ademen aims to ensure the cost of using its products is negligible compared with the benefits the modern data tools bring to healthcare, which means data optimization and management become priority technology enablers. Quix’s stream processing architecture, which takes away the demands of a database, allows Ademen to keep financial and time investments incredibly low.

“Quix has been a really fast way to show people concept scalability.”
Dr. Alistair Foster, director of Ademen

Ademen is ready to scale with Quix, thanks to the modularity, flexibility and reliability of the architecture it supports. Quix’s data integration features also mean a multitude of data sources can be combined to provide more exact and a larger range of diagnoses — and give patients the opportunity to act immediately.

"The Quix platform has been a key enabler for us to demonstrate our vision without the time, cost and risk of developing a streaming application in-house.”
Dr. Alistair Foster, director of Ademen

The Quix team is ready to help

Quix not only operates at the center of Ademen’s architecture but also in its development process. Engineers at Quix helped to build the Android app and provided a record of all data collected and processed during product development so that Ademen could refine its models during the next stage of development.

If you’re working on a new data project and don’t know how you’ll build it or get it all done, give Quix a ring.

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