Machine Learning, Medical Wearables That Can Detect And Analyze Troubling Coughs. (Wearable USA 2017)

Medical electronics have often been associated mainly with instrumentation. Large equipment like CT scanner, MRI scanners, Robotic surgery stations, or prenatal incubators. But electronics have been shrinking and we can see the impact of pace makers or insulin pump. These were the early medical wearables, which then gave way to the fitness tracker craze a few years ago. Technology has advanced a lot from the fitness trackers - we now have machine learning capabilities, which have now ushered a new age of medical wearables. Devices that now can help treat Asthma or COPD by monitoring a patient's cough and cough patterns. Come learn how the combination of microphone technology, machine learning algorithms and real medical science have create the next generation of medical wearables. This presentation will describe how the Quvium device's sensors are arrayed and processed, and will discuss other potential applications for sensors in medical products and health trackers, such as breathing detection, crying detection in babies, and fall and impact alerts.

Steve is the parent of an asthmatic child, as well as a medicinal chemist who worked on Zyflo®, an asthma drug. Steve has 25 years experience building health and life sciences software with simple user interfaces controlling complex solutions. Prior to founding Quvium, Steve served as CIO of Vertex and held senior positions at Abbott Labs & Park-Davis Pharmaceutical Research. Steve holds a B.S. degree in Chemistry from the University of Wisconsin and an M.S. in Chemistry from San Diego State University.

Quvium UK is a technology and data company specialising in intelligent management of respiratory disease.

 

It's innovative initial product is Sonasure™, a compact wearable medical device which monitor coughs and notifies of changes in cough frequency.