Qualcomm Tricorder XPrize goes to US team for device fusing AI, IoT, health

dxterweb.jpg

We’re getting closer to that Star Trek medical Tricorder concept.

special feature

How to Implement AI and Machine Learning

How to Implement AI and Machine Learning

The next wave of IT innovation will be powered by artificial intelligence and machine learning. We look at the ways companies can take advantage of it and how to get started.

First prize in the Qualcomm Tricorder XPrize was awarded to Final Frontier Medical Devices, a team in Pennsylvania. The team, led by brothers Dr. Basil Harris, an emergency medicine physician, and George Harris, a network engineer, created an artificial intelligence engine called DxtER that learns to diagnose medical conditions via data from emergency medicine and analyzing patients.

Final Frontier Medical Devices was awarded $2.6 million at the Qualcomm Tricorder XPrize ceremony on Wednesday.

Also: The business of XPrize: Scaling innovation contests

DxtER operates at the intersection of a few key trends such as artificial intelligence and the Internet of things. The concept of a medical Tricorder is also becoming more possible as use cases for the Internet of things–health, transportation, smart home, smart city and other areas–blend together.

More on health, IoT and AI: From heart attacks to fainting, this watch flags up health threats before they strike | IBM’s Watson does healthcare: Data as the foundation for cognitive systems for population health | Google’s DeepMind and the NHS: A glimpse of what AI means for the future of healthcare | AI that knows you’re sick before you do: IBM’s five-year plan to remake healthcare | Rebuilding the brain: Using AI, electrodes, and machine learning to bridge gaps in the human nervous system

Harris said that a device such as DxtER could address 90 percent of the cases in the emergency room without leaving the home. After all, people are really going for a diagnosis.

Here’s the quick overview of DxtER, which was basically cooked up in Harris’ den and house with his team in Paoli, PA:

  • The system includes a series of non-invasive sensors to collect vital signs, body chemistry and biological functions.
  • From there, data is used by the device’s diagnostic engine to make an assessment.
  • The device is designed to monitor health and diagnose illnesses in a home setting.
  • DxtER is autonomous, but can share information with healthcare providers if given permission.

Second prize in the challenge, good for $1 million, was given to Dynamical Biomarkers Group, a Taiwan-based outfit led by Medical School Associate Professor Chung-Kang Peng, Ph.D.

Dynamical Biomarkers Group paired algorithms and analytics in a device controlled by a smartphone. HTC Research helped with the prototype.

There were more than 300 teams vying for the Qualcomm-funded XPrize. The challenge revolved around creating a simple user experience that could diagnose 13 disease stats with their prototypes.

special feature

Digital Transformation: A CXO's Guide

Digital Transformation: A CXO’s Guide

Reimagining business for the digital age is the number-one priority for many of today’s top executives. We offer practical advice and examples of how to do it right.

Scroll to Top