Neosensory’s second developers contest has concluded and the winners are in! Our judges were thrilled with the many inventive entries leveraging Buzz to create devices ranging from smart snoring correctors to echolocators. In this ongoing series, we’ll be showcasing these submissions. To see all winners, click here.
Sachin Singh Bhadoriya and Dishant Shat felt inspired by the COVID-19 pandemic to make remote patient monitoring more accessible. Reflecting on the current status of the industry, the two felt “healthcare monitoring is not cheap and most health monitors measure very few vital stats which does not cover the overall health of a person.”
So they set out to develop a device that measures four key parameters:
- Body temperature (BT)
- SpO2 levels (oxygen saturation)
- Heart rate (HR)
- Heart rate variability (HRV)
A device to monitor patients remotely
The patient puts his/her finger into the client device in order to obtain a reading. Bhadoriya and Shat say taken together, they can detect symptoms like hypoxemia (low SpO2 levels), arrhythmia (irregular heartbeat) and many others.
This client device, using a server and an Edge Impulse model, then sends this information to the Buzz wristband worn by a healthcare provider, who feels the vibrations created by Buzz’s four motors. An app Bhadoriya and Shat specifically created for this purpose displays the vitals. The two developers chose Buzz since it allows to transmit information quickly and it’s easily noticeable in the case of an emergency.
“Another problem faced during patient monitoring is carelessness. When we perform a certain activity on a regular basis, we start exhibiting a certain amount of carelessness towards it. It is important that we show a very quick response to any potential health risk scenario. For this very reason, I have used the Neosensory Buzz in this project. While it is very difficult to notice minor changes in the vitals using just vibrations, it is more than enough to get a rough idea of the value of each vital and make the doctor or overseer alert in case of any emergency,” they write.
Collecting patient data
Bhadoriya and Shat wanted to make their device as accurate as possible. In order to collect patient data to train the Edge Impulse model, the two asked participants to wear their client device while exercising, deep breathing, and in other situations. They had also asked physicians for input.
Going this extra mile of entering a hospital in the middle of a pandemic to obtain real-world data especially impressed the judges and audience. No wonder BuzzBeat won the Audience Favorite!
Read more about the development, coding and the future of the device here.