EEG Module and Arm Prosthesis V2

For this project we'll need to do a lot of things, since it's very complicated. It's the second version of my proshtetic hand. The first one had a lot of problems and right now it doens't even work! This time I've made everything more thoughtfully and even made a 3D model of the hand by myself. The prosthetic arm is controlled by your brainwaves! Isn't it cool, right? EEG reads you alpha braiwaves (but you can also read beta brainwaves and analize them on your own) and then an algorithm processes the signal and rotates servos. Right now, I'm still waiting for gears, so there would be updates in the future. But the main thing works, so you are free to start making this project. All videos of things working are in the "Results" step.

We need a lot of stuff. To make it simplier, I devided parts into sections, so, it'll be easier for you to navigate.

EEG:

Electrodes (I used Gold Cup electrodes), AD620ANZ, 2xTL084CN, resistors (560, 2x22k, 2x12, 2x270k, 220k, 47k, 2x180k, 3x100k, 220), 1k variable resistor, non polarized capacitors (5x220nF, 100nF, 10nF, 25nF), polarized capasitors (2x10uF, 1uF), 2xbattaries (9V).

Prosthetic arm:

LiPo battaries (11.1V, 2800mA*h), ESP32, 5xServos (MS-1.3-9), LM2594N, 1N5820, 63uH 3A inductor, 1uF non polarized capasitor, polarized capasitors (180uF 35V, 470uF 35V), gears (exact sizes will be a bit later).

Here's the circuit of the most important part - electroencephalography. I'll explain what's going on here.

We need alpha brainwaves, which have frequency from 8 to 13 Hz. I also made it possible to read beta brainwaves (12-30 Hz), since my EEG filters out the noise which is not between 7 and 31 Hz. Firstly, the signal is amplified 89 times. Then it goes to 60 Hz notch filter, which filters out the biggest noise due to power lines interference. The next one is 7Hz high pass filter. It filters out the noise made by skin. Then comes 31 low pass filter. It just gets rid of anything above our frequency range. Then there's 1 Hz high pass fiter just for extra attenuation of unwanted noise and resistor in parallel with capasitor, which provide extra filtering (~160 Hz low pass filter). Then comes another amplification, but this time with variable resistor. It gives 83-455 gain. The last filter is another 60 Hz notch filter to filter out the noise which is left.

Now about electrode placement. You have 3 electrodes (+, -, and GND). GND electrode is needed to be placed at A1 spot, which is at earlobe. Electrodes + and - should be placed at Fp2 and O2 areas (there shouldn't be any difference between placing + electrode at Fp2 and - O2 or otherwise).

Now a bit simpler circuit. This is the brain of my prosthetic - microcontroller. It operates stepper motors (which I used instead of servos, because the net angle of rotation after gaining torque was not enough).

The microcontroller gets output from EEG, processes it according to the algorithm above and then controls stepper motors. The code is very simple.

I've checked, everything works perfectly fine (I've attached the photo of this testing).

I'm planning to use 11.1 LiPo battery, which should be enough for more than 1 hour of working (if my calculations are right). It's not that much, but enough for a prototype.

Here I'll explain why I used 30:1 gearbox specifically. The length of one finger is ~25mm. My stepper motor has 0.02 Nm torque. We're aiming for ~40N grip strength, so we need to calculate our torque for the fingers. Strength of two fingers first fingers would be 0.02*27/0.025 = 21.6. The rest three fingers have the same gain, so other three fingers will have the same strength. As a result, the strength of the hand would be 21.6*2 = 43.2. That's what we've been aiming for.

Here's the finished design of the hand. It's a pretty reliable design. The best I've made so far. It took me three different versions before making this one. Now I can say that it has no flaws in design.

Here you can see that EEG work perfectly fine. You can also see, how gears should be placed. I'll share with other results as soon as possible.