Alerte Digital Health | Health Early Warning Systems
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Sleep Monitoring

Intelligent wearable systems for automated detection of sleep quality and disorders including sleep apnoea.

Cardiac Monitoring

Continuous cardiac monitoring systems for prevention of stroke and cardiac arrest.

Alerte Echo IQ

Access to the world’s largest repository of echocardiograms for training automated cardiac diagnostic systems.

Mobile Health Platform

Mobile app combining live streaming technology with artificial intelligence for continuous real time monitoring.

Winner: Start Up of the Year 2019

We are so proud to announce Alerte Digital Health are the 2019 winners of the ‘Start Up of the Year’ Incite Award. This is a testament to the hard work and commitment the Alerte Team continue to display. On Friday, 14 June 2019, WA’s ICT Industry assembled at the Perth Convention & Exhibition Centre for the Awards Presentation of the 28th Annual WA Information Technology and Telecommunications Alliance Awards. Alerte is honoured to receive this commendation and to become a National iAwards Finalist 2019. We will continue to update you with our ongoing progress.

We are so honoured and excited to announce Alerte has been chosen as an Emerging Innovation Category finalist in the 2019 WA Innovator of the Year program. Our application is one of Emerging Innovation Category finalists selected to be advanced to the next stage of evaluation. Congratulations to the Alerte team and our fellow competitors, we wish you all the best for the next stage of the evaluation process!

Alerte’s Dynamic Application of Artificial Intelligence

Alerte’s mobile health platform provides a framework for the dynamic application of artificial intelligence technologies at a large scale. The platform allows for devices to be easily integrated into the system, providing a toolset to train new algorithms from any 3rd party application. AI models can be deployed to mobile applications, allowing for real time monitoring without the need for connection to the internet

Large amounts of historical data are aggregated with new data generated by an associated device. The system learns and evolves over time to develop a sophisticated understanding of complex health applications.

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