Advanced Real-Time Medical Diagnostics using AI and an IoT Medical Device

Study level


Topic status

We're looking for students to study this topic.


Dr Simon Denman
Senior Lecturer
Division / Faculty
Science and Engineering Faculty
Professor Clinton Fookes
Division / Faculty
Science and Engineering Faculty
Emeritus Professor Sridha Sridharan
Adjunct Professor
Division / Faculty
Science and Engineering Faculty

External supervisors

  • Dr Houman Ghaemmaghami , M3dicine Pty Ltd


M3dicine has developed a new digital and powerful stethoscope called Stethee. Stethee can capture heart, lung and other body sounds with incredible amplification, strong clarity and depth of sound.

This device can be used to capture vital signs of humans and animals and the resulting data can be used to detect, monitor, and diagnose a range of medical conditions and diseases.

In this project you will use Steethee to develop new artificial intelligence algorithms to capture and process medical vital signs of humans and animals.

Research activities

You will develop new machine learning approaches, especially those involving deep neural networks and recurrent neural networks, along with associated signal processing techniques to automatically process and interpret this new stream of medical information.

You will also address the development of new big data analytics techniques to capture patterns and trends across such large-scale medical data and visualize the information for the benefits of individual patients, attending physicians and the broader community


Case studies which will be examined in the PhD program may include:

  1. cardiac murmur detection in animals and humans using heart sounds, along with the specific detection of the type of murmur (systolic, diastolic, pan, etc) and predicting the grade of murmur
  2. blood pressure estimation
  3. pneumonia diagnosis
  4. heart tracking/condition-monitoring.

This research will help advance the capabilities of artificially-intelligent, Internet-of-Things medical devices more broadly.

Skills and experience

You are required to have a bachelor’s degree in electrical engineering and or computer science with 1st class honours.

It is desirable that you have a masters degree in a related area as well as expertise in:

  • signal processing
  • machine learning
  • deep learning.



Contact Emeritus Professor Sridha Sridharan for more information.