Raspberry Pi devices are often used by scientists, especially in biology to capture and analyse data, and a particularly striking – and sobering – project has made the news this week. Researchers at UMass Amherst have created FluSense, a dictionary-sized piece of equipment comprising a cheap microphone array, a thermal sensor, an Intel Movidius 2 neural computing engine, and a Raspberry Pi. FluSense monitors crowd sounds to forecast outbreaks of viral respiratory disease like seasonal flu; naturally, the headlines about their work have focused on its potential relevance to the COVID-19 pandemic.
Forsad Al Hossain and Tauhidur Rahman with the FluSense device. Image courtesy of the University of Massachusetts Amherst
The device can distinguish coughing from other sounds. When cough data is combined with information about the size of the crowd in a location, it can provide an index predicting how many people are likely to be experiencing flu symptoms.
It was successfully tested in in four health clinic waiting rooms, and now, PhD student Forsad Al Hossain and his adviser, assistant professor Tauhidur Rahman, plan to roll FluSense out in other large spaces to capture data on a larger scale and strengthen the device’s capabilities. Privacy concerns are mitigated by heavy encryption, and Al Hossain and Rahman explain that the emphasis is on aggregating data, not identifying sickness in any single patient.
The researchers believe the secret to FluSense’s success lies in how much of the processing work is done locally, via the neural computing engine and Raspberry Pi: “Symptom information is sent wirelessly to the lab for collation, of course, but the heavy lifting is accomplished at the edge.”
Image courtesy of the University of Massachusetts Amherst
FluSense offers a different set of advantages to other tools, such as the extremely popular self-reporting app developed by researchers at Kings College Hospital in London, UK, together with startup Zoe. Approaches like this rely on the public to sign up, and that’s likely to skew the data they gather, because people in some demographic groups are more likely than others to be motivated and able to participate. FluSense can be installed to capture data passively from groups across the entire population. This could be particularly helpful to underprivileged groups who are less likely to have access to healthcare.
Makers, engineers, and scientists across the world are rising to the challenge of tackling COVID-19. One notable initiative is the Montreal General Hospital Foundation’s challenge to quickly design a low-cost, easy to use ventilator which can be built locally to serve patients, with a prize of CAD $200,000 on offer. The winning designs will be made available to download for free.
There is, of course, loads of chatter on the Raspberry Pi forum about the role computing has in beating the virus. We particularly liked this PSA letting you know how to free up some of your unused processing power for those researching treatments.
Screenshot via @deeplocal on Instagram
And to end on a cheering note, we *heart* this project from @deeplocal on Instagram. They’ve created a Raspberry Pi-powered soap dispenser which will play 20 seconds of your favourite song to keep you at the sink and make sure you’re washing your hands for long enough to properly protect yourself.
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