I've built a system using an Arduino microcontroller and an accelerometer that can be used, 24/7, to measure some of the key symptoms of PD. In itself, this approach is not new, such equipment already exists, and similar functionality can be got by using tablet apps. But my approach has a number of nice features:

- it can take readings as frequently as every 0.02 sec;
- it can collect and hold data 24/7 (the data is stored on a micro-SD card);
- it is small enough (68X45x18 mm) to wear on the arm;
- it can be built easily - no more than 20 solders;
- the components cost only about £25;
- once it is on, it does not require the engagement of the person;
- the software is in the public domain and is free;
- the box can be repurposed by changing the software;
- the technology can be easily extended to be used to proactively reduce some of the symptoms of PD, e.g. good posture.

To show what it can do, I attach two graphs showing the results from a 60 second run with samples being taken of the magnitude of the acceleration every 0.02s (i.e. 1/50 sec). The first graph shows the trace of a "tremor attack". The second graph shows what frequencies are important: the peak is just below 5hz, common for PD. (The graphs and analysis are done using the free statistical programming language r.)

data60s20msTrace.png

data60s20msSpectrum.png

The next thing to do is to validate a measure of bradykinesia based on the different traces between boxes at different parts of the body. It will vary from person to person, but consider three boxes placed near:
A: the worst tremor (in my case the left hand);
B: the equivalent lesser affected place (the right hand);
C: the most static position (the upper chest).
A-B gives an estimate of the tremor;
C-B gives an estimate of the non-arm swing.
C-B will vary over the time of the effectiveness of a dose. The gap between the highs and the lows provide an estimate of the bradykinesia.

If anyone wants to get into this area, please get in touch.

John