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Samsung at the MIT Grand Hack, Part 2: Insomniax


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In my previous post I covered Samsung’s partnership with the Massachusetts Institute of Technology (MIT) and the Department of Veterans Affairs to host and sponsor the MIT’s Medicine Grand Hack, to foster creativity to solve some of the problems in the health care system.

In this post I want to highlight one of the teams that participated in the hack: Insomniax. With the clarity of their focus, and how they integrated Samsung’s wearable devices in their pitch, they were able to stand out during the weekend’s activities and win the Department of Veteran’s Affairs award.

Insomniax-Winner.jpeg

The Insomniax team participated in the mental health and professional burnout track, and created an application that uses biometrics and self-reported data to develop personalized recommendations for veterans with mental illnesses, who have poor sleep quality.

Their prototype highlighted the importance of having an easily accessible device that helps you tracking your daily routine and, with the help of an Artificial Intelligence system, gives you relevant advice to improve your quality of life.

Insomniax-App-cropped.png

Insomniax showcasing their app

The concept of the application they were working on was a way to combine data already collected by the Samsung Watch’s multiple sensors (things like heart rate, sleep, stress) along with a nightly questionnaire on activities/pre-sleep habits. The combined collected data then would be sent to a server with a REST API, then the system would process the data and revise the user’s recorded medical history to provide personalized recommendations on how they can get better sleep.

Insomniax-full-team.png

The Insomniax Team

Their demo was developed as a web app using Tizen Studio, and it was deployed on the Galaxy Watches that were made available to the Hackathon’s attendees.

These kind of apps can take advantage of the advanced features included in the Samsung Watches, like the Human Activity Monitor, that gives you access to and record human activity data from various sensors and recorders on the device.

View the full blog at its source

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