Safe Slumber

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Inspiration

Millions of patients suffer from nighttime breathing issues such as sleep apnea and asthma. In fact, healthcare providers have been seeing a rise in breathing problems as a result of the Covid-19 pandemic.

What it does

This device tracks user breathing sound to detect abnormal breathing. When abnormal breathing is detected, the device beeps and lights up to alerts the user. The device also sends the information to the app interface as an alert and displays user breathing and sleep data in the app for the user to examine.

How we built it

We calibrated a sound sensor from the Arduino Grove Beginner Kit to detect loud breathing sounds. Then we coded in Arduino to sound a buzzer, blink an LED and display a message on the OLED when abnormal breathing is detected. We then wrote Python code to read from the Serial line in Arduino and convert the data from the sound sensor into a CSV file. We then used the data in the CSV file to create a plot of user breathing data from Arduino, then embedded that plot into our app interface. We used Figma to create a user-friendly IOS app interface, that allows users to easily track sleep and breathing data.

Challenges we ran into

We struggled with creating visualizations of the data from the breathing monitor, as the data that came directly from the serial monitor was not clean. So we had to work to clean it.

Accomplishments that we're proud of

We are proud that we created something that will help people heal and recover from the long-lasting effects of the Covid-19 pandemic. We never thought we would be able to produce a user-friendly device.

What we learned

We learned that to make our project successful, we needed people from different backgrounds. Additionally, seemingly impossible tasks become possible when you break them up into parts and share the load.

What's next for Nighttime Breathing Monitor

We hope to work with more sensitive sound sensors, as our current one only detects the volume, but a more precise sensor will detect frequency. this more sensitive sensor will improve our product as it will be better able to distinguish unhealthy breathing. Additionally, we hope to improve the integration of user data into the app interface, to make cleaner visualizations.