Portable AI device turns coughing sounds into health data for Flu & pandemic forecasting  | FluSense

Portable AI device turns coughing sounds into health data for Flu & pandemic forecasting | FluSense


Researchers from the University of Massachusetts
Amherst have invented a portable surveillance device powered by machine learning – called
FluSense – which can detect coughing and crowd size in real time, then analyze the data to
directly monitor flu-like illnesses and influenza trends. The FluSense creators say the new edge-computing
platform, envisioned for use in hospitals, healthcare waiting rooms and larger public
spaces, may expand the arsenal of health surveillance tools used to forecast seasonal flu and other
viral respiratory outbreaks. Models like these can be lifesavers by directly
informing the public health response during a flu epidemic. These data sources can help determine the
timing for flu vaccine campaigns, potential travel restrictions, the allocation of medical
supplies and more. The FluSense platform processes a low-cost
microphone array and thermal imaging data with a Raspberry Pi and neural computing engine. It stores no personally identifiable information,
such as speech data or distinguishing images The researchers placed the FluSense devices,
encased in a rectangular box about the size of a large dictionary, in four healthcare
waiting rooms at UMass’s University Health Services clinic. From December 2018 to July 2019, the FluSense
platform collected and analyzed more than 350,000 thermal images and 21 million non-speech
audio samples from the public waiting areas. The researchers found that FluSense was able
to accurately predict daily illness rates at the university clinic. Multiple and complementary sets of FluSense
signals “strongly correlated” with laboratory-based testing for flu-like illnesses and influenza
itself.