A suite of open source and open hardware projects designed to detect and
alert people to someone suffering from an epileptic seizure (fit).
This is a work in progress at the moment, and four different technologies
are being developed to see which work best:
- Acceleration Detection
- Audio Detection
- Video Detection
- Microsoft Kinect (depth camera) Detection
It is based on an accelerometer monitoring movement. It uses a fourier transform to extract the frequency spectrum of the movement, and monitors movements in a given frequency band. The idea is that it will detect the rhythmic movements associated with a seizure, but not normal day to day activities.
If the acceleration within the given frequency band is more than a threshod value, it starts a timer. If the acceleration remains above the threshold for a given period, it issues a warning beep. If it remains above the threshold for a longer specified period, the unit alarms (continuous tone rather than beep).
This is a development version so it contains a real time clock and SD card to record the measured spectra to help optimise the device.
My initial intention is to mount this on a floor board on which our son sleeps (he will not sleep in a bed...). It may not be sensitive enough to pick up the movement through the floor, so it may have to be turned into a wearable device.
No working prototype yet....
Getting there. See http://nerdytoad.blogspot.co.uk/2013/03/first-go-at-video-based-epileptic.html.
This is the most promising looking option at the moment - the depth camera can eliminate background noise very well, leaving just the image of the subject to analyse. It also looks as though it is possible to detect breathing movements in the depth camera image. The thing that is missing at the moment is analysis of the image intensities to calculate rate of breathing. See http://nerdytoad.blogspot.co.uk/search/label/Kinect for examples of images etc.
Graham Jones, 03 January 2014. (grahamjones139+sd@gmail.com)