Child Seizure Monitor

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  This is a heart rate trace over 2.5mins with a seizure peak (blue) compared with smooth data (red)

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  The risk level of the heart rate data

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  Python code

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  Python code

Inspiration

We wanted to see how we could help parents who have children that suffer from seizures by having a warning system when their heart rate elevates above the normal level. Parents with children who have seizures have to be alert constantly and can suffer from sleep deprivation so we wanted to provide them with some peace of mind.

What it does

The child wears a FitBit which would track their heart rate and would work in conjunction with an app that would record this data. The app tracks the heart rate and works out whether the heart rate would be classed as a green, amber or red risk level. At the amber and red risk levels, the parent would receive a notification that their child's heart rate has spiked and that they should check on them. Sudden increase in heart rate is one of the warning factors that a seizure is about to occur.

How we built it

We have coded a prototype system in python in the hopes to move this plan onto an app in the future.

Challenges we ran into

We initially struggled with narrowing down exactly what we wanted to focus on and also then translating this idea into the code to achieve the outcome that we wanted.

Accomplishments that we're proud of

We are very proud that we managed to code the tiered warning system as this means that we can warn parents when there is some risk and a lot of risk, making this more reliable and provide more comfort for the parents. We are also proud that we came up with a viable solution to a problem that affects a lot of parents using existing technology.

What we learned

Expanded our knowledge of how to use web applications to process data and how to work in a team playing to everybody's strengths.

What's next for Child Seizure Monitor

We want to develop our app into a viable product and hopefully get FitBit on board with our idea. In the long term we want to extend the project so that parents can record lifestyle data such as food and activities to see if these have any effect on the frequency or severity of the child's seizures and use these to create more accurate predictions. A set towards personalised medicine.

Built With

• python