Open Seizure Detector

 

Latest News

About OpenSeizureDetector

Pebble_PhotoOpen Seizure Detector is a system to detect the shaking associated with a tonic-clonic epileptic seizure and raise an alarm to warn a carer that the user may need assistance.

It uses a Pebble Smart Watch to detect the shaking associated with a seizure, and an Android phone to initiate the alarms.   It can raise an alarm in several ways – connecting to the carer’s phone using wifi, via web browser, or by SMS text messages.

The system includes a continuous self testing system to provide reassurance that it is working as intended, and it will raise a fault warning alarm if something goes wrong.

The software is free and Open Source and does not require subscriptions to any web sites etc.   The apps are available for free on the Google Play Store and the Pebble App Store.

If you are using OpenSeizureDetector, please subscribe to email updates to this site (in the menu bar to the left), or the Facebook page so you can stay up to date with any issues or developments, otherwise there is no way I can get in touch with users of the system if I discover something you should be aware of!

Details of the system and installation instructions are provided on the Pebble Smart Watch Page.

diagram

If you have any comments, or queries, please email me at graham@openseizuredetector.org.uk

Project Aims

The aim of the OpenSeizureDetector project is to provide a free, Open Source set of tools intended to detect a tonic-clonic epileptic seizure and raise an alarm to alert a parent or carer that someone may need assistance.

Benjamin_PortraitIt has been developed primarily for our Son, Benjamin, but I hope that the tools will be useful to others, and am happy to support other people in using or developing them.  More details can be found on the Purpose of Project  and Project Goals pages.rg.uk.

I developed a number of other prototype detectors before settling on the Pebble Smart Watch version.  The list of prototypes is:

Pebble Smart Watch (using the accelerometers in the watch).

Microsoft Kinect (using the depth camera to sense movement)

Video Motion Tracking (use video camera to track movement)

Audio (listen for the noises associated with the movement).

There is additional information available on the project github pages.

Leave a Reply