Development Log

PsyLink is experimental hardware for reading muscle signals and using them to e.g. control the computer, recognize gestures, play video games, or simulate a keyboard. PsyLink is open source, sEMG-based, neural-network-powered, and can be obtained here.

This blog details the steps of building it and shows recent developments. Subscribe to new posts with any RSS reader, and join the community on the Matrix chatroom.


We don't have to drill a hole into skull to get access to your nerve signals. Muscles naturally amplify them, allowing us to easily read them through skin, and use them for useful things like controlling a computer or an artificial limb.

This is not science fiction, check out what's out there already:

You could argue that we use our nerves/muscles to control keyboards already (and pretty much anything else). And for the time being, there are clearly superior human input devices. But there are reasons to do this:

  • Bandwidth: Keyboards are limited to ~120wpm (~84 bit/s). Hopefully we can squeeze out some more by sapping the nerves directly.
  • Hands: Not everybody has them. You also may not want to use them, e.g. due to injury, or because they're occupied with other tasks.
  • Cyberpunk: The books predicted there will be neural interfaces in the future, therefore we must create them.

This page documents my process of building one. Note that I'm no expert and I neither have a plan, nor do I know what I'm doing. I just thought, how hard can it be? If the architect of the Internet Exploder can build one, surely I can do it to.

The Idea

On this day, I got the idea and started researching EMG design and signal processing, motor neurology basics, as well as existing projects.

Soon I realized that I will need a microcontroller to record and process the signals. I considered the Raspberry Pi Pico and Arduino Nano 33 BLE Sense, and chose the Arduino because:

  • Bluetooth
  • More analog-to-digital converter inputs
  • TensorFlow Lite support, which would allow me to leverage neural networks for signal processing. This is a bit of a stretch, can't wait to get disappointed by this :)

I wish there was a decent battery/UPS shield, couldn't find one so far.

Baby Steps

The Arduino arrived. I have no electrodes though. But what are electrodes, just some pieces of metal taped to your skin, right? Let's improvise that:


There are two pieces of aluminum foil taped to my skin, held together with blue medical wrap.

The educational material about electromyographs that I've seen described a chain of hardware elements to process and clean up the signal:

  • amplification
  • filtering
  • rectification
  • antialiasing
  • smoothing
  • averaging
  • etc.

But I thought, let's focus on the MVP. Why not simply hook the electrodes straight to the analog input pins of the Arduino with some alligator clamps? Worked fine. I did minimal signal processing in software though, you can find the source code here.

This video shows the myoelectric signal on Arduino IDE's built-in signal plotter:


The look of the first device was way too unprofessional, so I pulled out my sewing machine and made a custom tailored sleeve from comfortable modal fabric.


On the inside, I attached some recycled studs that served as electrodes. Who needs that expensive stuff they sell as electrodes when a piece of iron suffices?


This time it had 4 electrodes. I targeted the middle and the distal end of two muscles, the Brachioradialis and the Extensor carpi radialis longus. I picked those muscles at random, because I honestly don't know what the fuck I am doing.

Software-wise, I played around with moving average and got reasonable signals, but it was clear that there was too much noise.

How to filter, though? I'm not going to solder some bandpass filter, that's too slow and inflexible. There are simple algorithms for doing it in software (link 1, link 2), but something seemed off about this method. In the end, I decided to learn how to do a Fourier transform on the Arduino.

With this code (inspired by this post), I took 64 samples at a sampling rate of 1kHz, performed the Fourier transform, cut out anything under 30% and over 50% of my frequency range, and then summed up the amplitudes of the remaining frequencies to generate the output.

Still very crude, but it allowed me to get distinctive signal patterns for various positions of my arm:


I was genuinely surprised that I got information of this fidelity and usefulness from just hooking up 4 ADC's to semi random places of my forearm and a software bandpass filter. This was good enough to use it as a basic input device!

I wondered, can I control a racing car game with this?

To test that, I built this program to read out the signals and convert certain ranges of values to keyboard presses of the keys Left and Right. The value ranges need to be calibrated before each use: I held my left arm like I'm grabbing an invisible steering wheel, moved it left and right, and looked hard at the signal values to find correlations like "signal A is always below X if and only if I steer left". Once the calibration is done, the invisible steering wheel turned into a magical keyboard with 2 keys =D

Right away I tried it out to steer in my favorite racing game, F-Zero:

Note that in addition to the steering wheel, I used my other hand to accelerate.

I loved it, but there is still a lot of work to be done. The calibration is a pain, especially since it needs to be repeated if the electrodes move too much, which happens a lot with this kind of sleeve. Also I want more electrodes, better signal processing, and data transfer via Bluetooth so I can run it off a battery.

Adding some AI

Most neural interfaces I've seen so far require the human to train how to use the machine. Learn unintuitive rules like "Contract muscle X to perform action Y", and so on. But why can't we just stick a bunch of artificial neurons on top the human's biological neural network, and make the computer train them for us?

While we're at it, why not replace the entire signal processing code by a bunch of more artificial neurons? Surely a NN can figure out to do a bandpass filter and moving averages, and hopefully come up with something more advanced than that. The more I pretend that I know anything about signal processing, the worse this thing is going to get, so let's just leave it to the AI overlords.

The Arduino Part

The Arduino Nano 33 BLE Sense supports TensorFlow Lite, so I was eager to move the neural network prediction code onto the microcontroller, but that would slow down the development, so for now I just did it all on my laptop.

The Arduino code now just passes through the value of the analog pins to the serial port.

Calibrating with a neural network

For this, I built a simple user interface, mostly an empty window with a menu to select actions, and a key grabber. (source code)

The idea is to correlate hand/arm movements with keys that should be pressed when you perform those hand/arm movements. To train the AI to understand you, perform the following calibration steps:

  1. Put on the device and jack it into your laptop
  2. Start the Calibrator
  3. Select the action "Start/Resume Recording" to start gathering training data for the neural network
  4. Now for as long as you're comfortable (30 seconds worked for me), move your hand around a bit. Hold it in various neutral positions, as well as positions which should produce a certain action. Press the key on your laptop whenever you intend your hand movement to produce that key press. (e.g. wave to the left, and hold the left arrow key on the laptop at the same time) The better you do this, the better the neural network will understand wtf you want from it.
    • Holding two keys at the same time is theoretically supported, but I used TKinter which has an unreliable key grabbing mechanism. Better stick to single keys for now.
    • Tip: The electric signals change when you hold a position for a couple seconds. If you want the neural network to take this into account, hold the positions for a while during recording.
  5. Press Esc to stop recording
  6. Save the recordings, if desired
  7. Select the action "Train AI", and watch the console output. It will train it for 100 epochs by default. If you're not happy with the result yet, you can repeat this step until you are.
  8. Save the AI model, if desired
  9. Select the action "Activate AI". If everything worked out, the AI overlord will now try to recognize the input patterns with which you associated certain key presses, and press the keys for you. =D


I used this to walk left and right in and it worked pretty well. With zero manual signal processing and zero manual calibration! The mathemagical incantations just do it for me. This is awesome!

Some quick facts:

  • 8 electrodes at semi-random points on my forearm
  • Recorded signals for 40s, resulting in 10000 samples
  • I specified 3 classifier labels: "left", "right", and "no key"
  • Trained for 100 epochs, took 1-2 minutes.
  • The resulting loss was 0.0758, and the accuracy was 0.9575.
  • Neural network has 2 conv layers, 3 dense, and 1 output layer.

Video demo:

Still a lot of work to do, but I'm happy with the software for now. Will tweak the hardware next.

Now I'm wondering whether I'm just picking low hanging fruits here, or if non-invasive neural interfaces are really just that easy. How could CTRL-Labs sell their wristband to Facebook for $500,000,000-$1,000,000,000? Was it one of those scams where decision-makers were hypnotized by buzzwords and screamed "Shut up and take my money"? Or do they really have some secret sauce that sets them apart? Well, I'll keep tinkering. Just imagine what this is going to look like a few posts down the line!

Cyber Gauntlet +1

So if you ever worked with electromyography, this will come to no surprise to you, but OMG, my signal got so much better once I added a ground electrode and connected it to the ground pin of the Arduino. I tried using a ground electrode before, but connected it to AREF instead of GND, which had no effect, so I prioritized other branches of pareto improvement.

I am once again confused and surprised that I got ANY useful results before.

For prototype #3, I moved the electodes further down towards the wrist in hope that I'll be able to track individual finger movements. It had 17 electrodes, 2x8 going around the wrist, as well as a ground electrode at the lower palm. Only 9 of the 17 electrodes are connected, 8 directly to the ADC pins, and one to 1.65V, which I created through a voltage divider using two 560kΩ resistors between the 3.3V and GND pins of the Arduino, so that the electrode signals will nicely oscillate around the middle of the input voltage range.

It all started out like a piece of goth armwear:


Photo from the testing period:


Soldering wires to the electrodes:


The "opened" state shows the components of the device:


But it can be covered by wrapping around a layer of cloth, turning it into an inconspicuous fingerless glove:


If you look hard at this picture, you can see the LED of the Arduino glowing through the fabric, the voltage divider to the right of it, appearing like a line pressing through the fabric, the ground electrode on the lower right edge of my palm, and the food crumbs on my laptop :)

The signal seems to be much better, and as I move my arm and hand around, I can see distinct patterns using the Arduino IDE signal plotter, but for some reason the neural network doesn't seem to process it as well. Will need some tinkering. I hope it was not a mistake to leave out the electrodes at the upper forearm.

I already ordered parts for the next prototype. If all goes well, it's going to have 33 'trodes using analog multiplexers. The electrodes will be more professional & comfortable as well. Can't wait!

Data Cleaning

The arduino code now produces samples at a consistent 1kHz. I also moved the serial read operations of the calibrator software into a separate thread so that it doesn't slow down on heavy load, causing the buffer to fill up, and the labeling to desynchronize. I am once again confused and surprised that I got ANY useful results before.

I disconnected analog input pin 7 from any electrode, and used it as a baseline for the other analog reads. By subtracting pin 7 from every other pin, the noise that all reads had in common was cancelled out. Hope this doesn't do more harm than good.

I also connected the ground line to one of the wrist electrodes rather than to the palm, since the palm electrode tended to move around a bit, rendering all the other signals unstable.

And did you know that the signals looks much cleaner when you unplug the laptop from the power grid? :p


I'll finish with a video of me trying to play the frustrating one-button jumping game Sienna by flipping my wrist. This doesn't go so well, but maybe this game isn't the best benchmark :D My short-term goal is to finish level 1 of this game with my device.


The analog multipexers (5x DG409DJZ) and other stuff arrived! I almost bought a digital multiplexer, because I didn't know there were various types... But I think that these will work for my use case. The raw signal that I get out of it looks a little different, but when I filter out the low & high frequencies with TestMultiplexer2.ino, the direct signal and the one that goes through the multiplexer looks almost identical =D.


I have the feeling that before building the next prototype, I should figure out some way of enhancing the signal in hardware before passing it to the microcontroller. It's fun to hook the 'trodes straight to the ADC and still get results, but I don't think the results are optimal. So these days I'm mostly researching and tinkering with OpAmps.

First Amplifier Circuit

I had my head stuck in electronics lectures, datasheets, and a breadboard to figure out a decent analog circuit for amplifying the signal. It sounds so straight forward, just plug the wires into the + and - pin of an operational amplifier, add a few resistors to specify the gain of the OpAmp, and feed the output to the analog input pin of the Arduino... But reality is messy, and it didn't quite work out like that.

Here's a list of problems:

  • The voltage I measured from the electrodes seemed incredibly fragile. As soon as I wanted to do something with it, it seemed to change. This could be due to the high impedance of the skin, causing a drop in voltage as soon as one draws any current.
  • One electrode may have a DC voltage offset compared of the other electrode. When this gets large (~50mV+), the amplified voltage difference gets off the scale.
  • The OpAmp amplifies not just the signal but also the noise, like:
  • I ordered a part that requires min. +/-2.25V. The Arduino supplies 3.3V, so all is well, right? Nope. It means that I need negative 2.25V as well as positive 2.25V.
    • Solution: Increased the voltage of the entire circuit to 5V, which the Arduino conveniently supports by changing a solder jumper. The middle-ground reference voltage rose from 1.65V to 2.5V, leaving enough room for the required +/-2.25V. I don't actually use the part yet, but I wanted to prepare for it.
  • The 2.5V reference voltage from the voltage divider strongly fluctuated, messing up the output from the OpAmp.
  • The LM324N OpAmp that I used has an output voltage limit of 3.6V (at a supply voltage of 5V.) That cuts off a good chunk of the signal.
    • Solution: I added a second reference voltage at 1.66V so the output centers around that. (Conveniently, the output limit of 3.6V is close to the Arduino's ADC reference voltage of 3.3V.)
  • Should I even do any of this? I'm limiting the neural network by introducing my bias about what a clean signal looks like. Any circuit will invariably filter out certain information, enhance other information, and add irrelevant noise. How do I know that the information that I filter out (e.g. the DC offset voltage between electrodes, or even what I consider irrelevant noise) isn't useful to the neural network?
    • Solution: Keep the signal processing reasonably minimal

I also connected the electrode signal to ground with a 1MΩ resistor which greatly improved the signal, and I have no idea why.

One peculiar thing I noticed was that the signal seemed stronger when my laptop was connected to the power supply. It superimposed noise, but also seemed to increase differences in electrode voltages. I don't quite understand this yet, but 2 things follow from that:

  • For replication purposes, I'm using a Lenovo Thinkpad T460p switched to the Intel GPU, which creates it's own particular noise patterns, even when unplugged from the grid.
  • I should try out modulating the ground electrode voltage with a controlled low frequency pattern to see if this improves signal to noise ratio. Ideally <30Hz or >500Hz so I can easily filer it out later.

Some of the references I used:

The resulting circuit:

Circuit schematic

And the signals look like:

Signal image 1 Signal image 2

Yellow and green are two electrodes, right after their respective OpAmp, and purple is (yellow-green)*20.

This should be good enough to move forward, but I bought some INA128 instrumentation amplifiers and perhaps I will tinker some more to get an even better signal. Can't wait for the next prototype though :).

In other news, I watched Dr. Gregory House explain forearm muscles, so next time my electrode placement will be better than random!

And since I learned KiCad for creating the above schematic, I thought I'd add schematics for the previous models as well, see circuits.

Going Wireless

I've been battling with reducing the power line noise for too long, so I thought screw it, let's go off the power line entirely. I put the circuit on two 3V CR2032 coin cells and wrote some code to transmit the signals via BLE (Bluetooth Low Energy) using the ArduinoBLE library.

Since I can not plot the signals via the Arduino IDE plotter anymore, I switched to GNURadio and wrote a plugin that establishes the BLE connection and acts as a signal source in the GNURadio companion software

My new "electrodes" also arrived: Simple prong snap buttons. They don't have sharp edges like the pyramidal studs I used before, and allow me to easily remove the wires from the electrodes and plug them in somewhere else as needed.

photo of the breadboard

I also employed INA128 instrumentation amplifiers, drastically reducing the complexity of the circuit. It's a tiny SMD chip, which I plan to embed in hot glue, along with the 3-4 capacitors and 3-5 resistors required for processing/de-noising, and place 8 of these processing units across the glove/wristband, connected to two electrodes each.

Circuit schematic

Now I'm battling the problem that I can only get about 1kB/s across the ether. How am I supposed to put 12kB/s worth of signal in there? (8 channels, 1k samples/s, 12 bit per sample) Let's see if I can find some nice compression method, but I fear that it's going to be lossy. :-/

Soldering the Processing Units

The plan was to split the circuit into:

  • 1 central part including the Arduino, power supply and the OpAmp that generates the signal ground, and
  • 8 distributed signal processing units, embedded in hot glue for stability and electrical insulation, consisting of an instrumentation amplifier and related components, close to the electrodes to avoid signal degradation.

Here's my try to solder one of those units:


This took me over an hour, during which I began questioning various life choices, started doubting this whole project, poured myself a Manhattan cocktail, wondered how long it would take to complete all eight of these, whether it will even be robust enough to withstand regular usage of the device (NO, IT WON'T), and how I'm going to fix the inevitable broken solder joints when the entire thing is in fucking hot glue...

I gave up, and now my plan is to get PCBs for this instead. I have little experience with this, so I've been putting it off, but how hard can it be?

First draft:


Updated schematic:


I removed the decouplying capacitor between ground and GNDS (signal ground) by the REF pin of the INA128 because mysteriously it made the signal worse, not better. Also removed the 1K resistors between electrodes 1+2 and the respective capacitors, because they served no apparent purpose.

Also, I was frustrated that GNURadio doesn't allow you to get a "rolling" view of a signal. The plot widget buffers as many samples as it can show, and only when the buffer is full, it updates the graph, clears the buffer and waits again. I wanted instant updates as soon as new samples are in, and as a quick&dirty workaround I wrote a GNURadio shift block which keeps filling up the buffer of the plotting widgets.

I'll finish with a nice picture of a finger snap, as recorded with one electrode pair on my dorsal wrist. Click to enlarge and view the frequency domain as well. (Just one electrode pair because that's all I can squeeze out of the poor bluetooth low energy bandwidth so far)

screenshot of EMG of a finger snap

PCB Time

Today I made a new version of the PCB that processes the signals from one electrode pair:

pcb picture

Actually, several versions. This is the 4th iteration, and let's not even look at the previous ones because they were just plain wrong. I stared at this design for a long time though and couldn't find another problem, so I went ahead and ordered 30 pieces of it. Can't wait to find out in what way I messed up :'D And hey, maybe it'll actally work.

Main features:

  • Dimensions: 20x17x1.6mm, rounded corners
    • Tiny enough to fit between 2 electrodes!
  • 2 connectors for electrodes, at the middle top & bottom
  • 1 connector for the output at the bottom right corner (on the front side. The back side is mirrored)
  • 3 power line connector ports on the other corners, with 3 pins each:
    1. The signal reference voltage
    2. Ground
    3. +6V from the battery
  • 3 capacitors, 3 resistors, 1 integrated circuit

To avoid having a kilogram of cables on the device, this board supports wiring in a mesh network topology, where the boards share the power lines amongst each other using the redundant power line connector ports. One board can power two other boards, which in turn can power 4, and so on.

The bypass capacitor between ground and V+ will hopefully keep the voltage stable, though I'm a bit worried about the reference signal. If necessary, I can "abuse" the reference signal pin of the power line connector ports to add extra ground electrodes. I considered adding an extra opamp on every board to generate a fresh reference voltage but that would make the circuit too big for my taste.

Higher Bandwidth, new UI

Hah, I managed to raise the Bluetooth bandwidth from ~1kB/s to 6-7kB/s with this one magic line:

BLE.setConnectionInterval(8, 8);

It raises the power consumption by 4% (3.5mW), but that's totally worth it. I can now get all 8 channels in 8-bit resolution at 500Hz across the aehter. Eventually I should aim for 10-bit at 1kHz, but I think that can wait.

signals gnuradio flowgraph

This is the GNURadio flowgraph and the resulting output. (I only have hardware for 2 electrode pairs, so even-numbered and odd-numbered signals are wired to the same input. Still waiting for the PCBs.)

Power ratings:

  • No Bluetooth connection: 86.9mW (16.9mA x 5.14V)
  • Transmitting at 1-2kB/s: 88.9mW (17.3mA x 5.14V)
  • Transmitting at 6-7kB/s: 92.5mW (18.0mA x 5.14V)

Surprisingly to me, the LEDs were draining a good chunk of the power, and I saved 16mW by removing the external power LED (see previous photo) and by PWM-dimming the blue LED that indicated Bluetooth connections. It gives me approximately 15 hours run time with 2x CR2032 coin cells.

Also I'm in the process of rewriting the UI:

MyocularUI screenshot

The colorful column graph is a live visualization of the signal. The columns correspond to electrode pairs, while the rows are time frames. The top row shows the amplitude of the signal at the current time, and the rows flow downward, allowing you to view changes back in time, as well as correlations between signals.

You'll also be able to change settings on the fly, view the status of e.g. key recordings or machine learning processes, and more. All of this is in a modular library that will also be usable from e.g. GNURadio.

I was thinking of changing the graphical user interface toolkit from Tkinter to a more modern one, because Tkinter looks a little shabby, and it has problems determining which keys are currently pressed, but I decided against it, because I made the experience of being unable to run my own software several years after writing it because the exact version of the GUI toolkit, along with all dependencies, was too annoying to set up. Tkinter has been around for decades and will probably stay, so I'll stick with it for now. Also, I can easily solve the key pressing issue with an external key tracking library like pynput.

Can't wait to try out the new UI with 8 individual electrode pairs, once the PCBs arrive! (assuming they work :'D)

Finished new UI

The new user interface now supports all previous features!

  • Capturing muscle signals
  • Capturing the keys that the user is pressing
  • Training a neural network to predict key presses from given signals
  • Auto-pressing keys based on incoming signals using said neural network to predict which keys the user wants to press

MyocularUI screenshot

It's sooo much more pleasant to have a direct view on the state of the application and an instant visualization of the signals. The previous version was literally just a blank window, with a single menu called "File" that contained all the actions. :D I never even bothered to upload a screenshot, but here's one for documentation purposes:

screenshot of old 'Calibrator' tool

Also, this time I used clean & efficient data structures to make the code easier to work with, a more reliable key capturing library (pynput), and threads to prevent one activity from blocking the others. The signals obviously go via Bluetooth instead of a wired serial connection.

I'm also thinking of changing the name for the project, since people are reading it as "my ocular" rather than recognizing the neologism made of "myo" (for "muscle") and "ocular" (from "eye"). But all the good names are taken, of course. -_-

New Name

After some brainstorming, I changed the working title of this project from Myocular to ✨PsyLink✨. The close second favorite was FreeMayo (thanks to Vifon for the suggestion). Free as in free speech/software/hardware, and mayo as a play on myo (ancient greek for "muscle"). But somehow I liked PsyLink more. It's inspired by the Psionic Abilities from the 1999's game System Shock 2.

FYI, this is the list of words that I considered, although unfortunately many of the coolest combinations were taken:

  • axon
  • coil
  • cortex
  • cyber
  • free
  • gauntlet
  • glove
  • link
  • loop
  • magic
  • mana
  • mayo
  • myo
  • open
  • pipe
  • plug
  • psi
  • psionic
  • psy
  • psyber
  • scan
  • surge
  • tron
  • ware
  • wave
  • wear

Power Supply Module

I made an updated schematic (circuit 6) that shows more clearly how the modules are connected. Also corrected an error with the feedback of the voltage follower, and changed values of some resistors/capacitors:

Schematic image

I also constructed the power supply module:

Photo of power module #1

but for some reason it didn't work. All the parts seemed to have been connected the right way, I couldn't find a short circuit, but the output voltage was ~0.5V instead of ~5V, and the reference voltage was just 0. I blame a possibly broken opamp.

Well, I didn't like the design and length of the circuit board anyway, so it didn't hurt trashing the thing and building this beauty instead:

Photo of power module #2

I'll use female-to-female jumper wires to connect V+ and GND to the arduino, and 3 more wires to bootstrap the power supply of the mesh network of the signal processing modules.


  • Yep, that's 2 coin cells in there
  • Outputs: Black=Ground, Red=V+, Green=V+/2 (reference signal)
  • There's an optional second green pin for the ground electrode
  • If you're wondering why I'm using a big ass quad opamp when I just need a single output: I don't have a smaller one atm.
  • I totally need to move this to a SMD PCB in the long run, this is still too bulky, but will do for now. It's about the dimensions of a 9V battery.

I wonder if some 深圳人 will read this, shake their head, and view me as a primate struggling to make fire with sticks. That's what it felt like to construct this thing anyway. Nevertheless, I'm one step closer to the next prototype :)

Wireless Prototype

Hell yeah! The PCBs arrived:

pcb photo

Soldering & Sewing

I never soldered such tiny SMD parts before, and didn't have proper tools, way too thick soldering tin and solder iron tip. I was also too impatient to order some, so after hours of torture, I produced this batch:

photo of 8 soldered pcbs for signal processing

The new prototype was to be a forearm sleeve of modal fabric once again, with snap buttons for electrodes which will also hold the signal processing PCBs in place.

But how to attach the Arduino and the power supply module to the sleeve? I thought, "why not Velcro?" (hook-and-loop fastener) and started sewing it to the circuit boards:

photo of me sewing velcro to the power supply module

(Yes, doing it felt as weird as it looks)

So I sewed the sleeve, assembled one electrode pair along with its processing PCB, and wired everything together. Here's me being overly excited about the first wireless test run:

Electrode Placement

Then there was the question of where to put the electrodes. Using an improvised muscle map along with two flexible electrodes on individual straps, I could find spots whose electrical activity correlated with turning the arm, twisting the wrist, or pressing individual fingers onto the table:

photo of me mapping my forearm

Flexor Digitorum Superficialis was particularly interesting; I found 3 areas over that muscle which map to the index, middle and ring finger each. For turning the arm and wrist, the muscles with "Carpi" in their name (e.g. Extensor carpi ulnaris) worked pretty good.) A huge disappointment was Extensor Digitorum, which is supposed to be active when fingers move up, but I could not find such correlation. Then again, I use snap buttons for electrodes, so I'm not that surprised.

The final layout of the electrodes:

electrode map

This piece is fully separable from the electronics and therefore machine washable.

Here are additional pictures of the inner side, the separated electronics, as well as everything combined. This nicely shows the tree topology of the green signal processing modules that pass through the power supply among each other to reduce the volume of wiring.

inside electronics only everything combined

I could have had 8 electrode pairs, but only added electrodes for 7. On these pictures, the electrode pair for the middle finger is also missing the circuitry. That's mostly a testament to my laziness.

Actually I regret where I placed the Arduino, since there would be some great spots for electrodes, but I noticed that too late. Will try to remove the Velcro and maybe add an 8th electrode pair there.

The final cyb3rware:

photo of the final product

While the signal was quite strong with the test straps, I found that the amplitude of the signal went way down once I had everything attached to the sleeve. Maybe there was some kind of interference from the Arduino or the power supply being closer to my skin, or maybe the modal fabric messes with the signal somehow. I hope I can compensate for this by increasing the signal amplification multiplier, but I leave that for later.

This issue occurred with a single electrode pair already, but was aggravated when attaching more of them. It might help if I add some flux capacitors to the power supplies to prevent cross-interference.

Test Drive

I drove F-Zero with Prototype #2 before, but back then I cheated a little bit. It only recognized 2 keys, left and right, and I accelerated with the keyboard using my other hand.

This time I hoped I could do better, and trained the AI to recognize 3 different keys (left, right, accelerate) from my muscle signals. It even kinda worked!

This was after recording ~2000 muscle signal samples over 1-2 minutes and training a convolutional neural network for 25-50 epochs (<1 minute) on the data using the PsyLink UI. I used 4 electrode pairs, all of which are on the dorsal side of the forearm.


In the racing game, I didn't make it to the finish line yet, and it does look pretty clumsy, but I blame it on the software still having some obvious flaws. It doesn't even account for packet loss or packet duplication when handling the Bluetooth packets yet. Hope it will go better once I fixed them. Also, the test drive was with only 4 electrode pairs.

The raw values as visualized with the GNURadio flowgraph while randomly moving my forearm/wrist/hand show that the correlations between the signals are low enough to be theoretically useful:

graphs of signals

If you enlarge this image, you'll see that especially the black line is considerably different, which I suppose is because it's the only electrode pair that spans across several muscles. And that makes me wonder: Am I doing too much pre-processing in hardware before I feed the data into the AI? Sure, the differential amplification of this new prototype enhances small signals that the previous prototypes might have not detected, but a lot of information is lost too, like the voltage differences between electrodes from different electrode pairs.

Maybe I can compensate for this by simply adding some more electrode pairs that span muscles. I'm also thinking of switching to a design with 32-64 randomly placed electrodes -> buffer amplifiers -> multiplexers -> analog to digital converters of the Arduino. That way, the neural network can decide for itself which voltage differences it wants to look at.

New PCB layout

While soldering the PCB, I found some flaws and made these changes to the previous PCB:

  • Added silkscreen labels to the connectors and components. I was sure I wouldn't mix up anything since there aren't many connectors, they're nicely symmetrical, and I'm the designer after all. But nope. I still mixed them up.
  • Removed unnecessary vias. (I was actually not sure whether the pin holes will really conduct between the front and the back side of the board, so I added vias as a safety measure.)
  • The label now shows the new name "psylink" instead of "myocular"
  • A friend also gave me the tip to increase the thickness of power supply wires

psylink6 PCB

Gyroscope + Accelerometer

I fixed up the PsyLink UI. It was so broken after the rewrite to Bluetooth Low Energy, I'm once again stunned that I got ANY useful results before. But now it receives the transmissions from the Arduino properly.

PsyLink UI screenshot

I also added 6 more signal channels: The x/y/z-axes from the Gyroscope and from the Accelerometer that are built in to the Arduino Nano 33 BLE Sense.

All put together finally allowed me to singlehandedly drive through the finish line of my favorite racing game F-Zero! \o/

  • For training the AI, I recorded 60k samples over 2 minutes (500Hz)
  • Trained for 5 epochs, which took 1 minute without GPU acceleration
  • 4 training labels ("left", "right", "accelerate", "nothing")
  • Final training and validation loss: 0.04, accuracy: 98%
  • 6 layer neural network with 2 convolutional layers
  • Music by Mitch Murder

Dedicated Website

The PsyLink project now has it's own website:, and this is the place where I will continue the development log, as soon as I finish the basic structure of the website.

Website is Ready

The website is more fleshed out now, with a nice black/green design, neurons in the background, and a logo that is based on the logo of the fictional TriOptimum Corporation from the System Shock game series.

Videos are now hosted on a PeerTube Channel, allowing me to upload higher quality videos in the future while keeping the git repository of the website small.

I also catalogued individual components (circuit schematics, circuit boards, textiles, software) that resulted from this project so far, and documented how they all fit together in the prototype overview. Each component has an individual ID now, that I can easily write, print or sew on the hardware so I don't mix everything up. For example, prototype 4 has the ID "p4" and can be reached directly via, while the signal processing board of p4 has the ID "b1" and can be reached via

Here's a screenshot, for a future time when the design has changed:

screenshot of the new website

Back to the Roots

While uploading the old videos to the new PeerTube channel, I viewed the first video once again, which shows a pretty good signal from just two pieces of aluminum foil taped to the skin. And I wondered, why do I even bother with such a complicated set-up like in Prototype 4? It was really annoying to assemble, and the device is clunky and fragile.

Let's go back to the roots and build something more simple. Plenty of reasons:

  • Having 8 small, distributed signal processing PCBs sounds nice at first, but it creates more points of failure. With Prototype 4, I had multiple instances where a connecting wire broke off, so this time I'd rather have everything on one PCB.
  • What happened to the idea of processing the signal as little as possible and leaving the job to the neural network? Circuit 6 (whole device) amplifies certain information but hides other, like the DC voltage offset between electrodes.
  • The electrode map of Prototype 4 provides me with signals (like "arm turns left/right") which are redundant since I added support for the inertial measurement unit (IMU).
    • The signal from the IMU is actually way more reliable than what I'm getting from the electrodes, so why not ditch them completely? Well, there are some parts of the arm that move separately from the Arduino, mainly the fingers. So let's focus on these.
  • My main issue with the early prototypes was the poor signal-to-noise ratio, but that was mainly due to the power line. This should be gone with a battery-powered device.

Circuit 7

The Circuit 7 (whole device) shows a simplification of the signal processing module to a simple non-inverting amplifier per electrode with a gain of 221x. There's also a 560KΩ bias resistor towards Vref so the voltage we measure isn't too far off the center. In Circuit 6 (whole device) I had used 1MΩ, but here it produced mysterious oscillations, and going down to 560KΩ mysteriously fixed it.

This circuit also features a rechargeable 1.2V AAA battery with a TPS61220 step-up converter boosting the voltage to 5V, because I don't hate nature, and I burned through enough CR2032 coin cells. Coin cells also aren't exactly optimized for currents of 20mA, and thus get drained too quickly.

circuit 7

I measured a signal while pressing down a finger onto the table with two electrodes along the Flexor Digitorum Superficialis. Blue is electrode 1, red is electrode 2, and green is an amplified difference:


Circuit 8

But let's cut even more out of this circuit. Here's one that is designed to be a shield to the Arduino Nano 33 BLE Sense, containing just the power supply, and an array of pass-through pins:

circuit 8

The signal that I'm getting is weaker, but certainly usable: (again, I measured a signal while pressing down a finger onto the table with two electrodes along the Flexor Digitorum Superficialis. Blue is electrode 1, red is electrode 2, and green is an amplified difference)



I also built a PCB that implements this power supply/pass-through shield, and I figured, even if the device ends up not very useful, I'll still be able to use this for experiments later on, thanks to the pass-through pins.


I just hope that the PCB/circuit will work at all. I still haven't figured out how to simulate it, and I don't really know the best practices for PCB design. The PCB footprint for the AAA battery clips (Keystone 82) is my first custom-made PCB footprint too. Hope it all works out.

Next Prototype

It will be a relatively small forearm band with 8 electrodes (+ 1 ground electrode), which I plan to place around the Flexor Digitorum Superficialis for detecting what individual fingers are doing. The information from the gyroscope + accelerometer should cover the rest.

Believe The Datasheet

Today the order of Power Module 2 arrived!

And with relief I saw that the battery clips fit nicely onto the board, as does the Arduino (with pin strips), and all the other components. Just that simple thing already felt like an accomplishment at my level of expertise with PCB design ;)

After some dreadful time trying to solder on the tiny 1x2mm-sized chip at U1 (I need a microscope for this shit), I had the SMD parts assembled and the circuit was ready for a test drive:

photo of assembled p5

But something was weird. The output voltage was a meager 1.5V, not the expected 5V, even though everything was connected properly. After hours of debugging I flipped over the table and just soldered a fresh board, this time without the Vref-generating OpAmp (U2+R3+R4+C3). But no luck, still just 1.5V. This was lower than the minimal output voltage of the voltage booster, so the chip didn't even finish it's start-up phase. How could that be, if there's not even any load on the output voltage?

I desperately tried several different things. One was doubling the inductance at L1 from 4.7µH to 9.4µH by using two SMD inductances in series:


Unfortunately I think I broke the coils while constructing this, since they didn't let any current go through. But I found a regular, big inductance coil with 10µH, manually held its pins down onto the SMD pads, and indeed, the voltage jumped up to 5V!

So I soldered it... onto... the SMD pads.


(Probably you can reconstruct my entire room from all the reflections in this image, along with a biometric picture of my face and at least 3 of my fingerprints...)

But once I connected the OpAmp, the voltage went back down to 2.5V, and with the Arduino connected, it went down further to 2.4V. Adding a second coil in series for a total of 20µH didn't compensate for this, but made it even worse, bringing it all the way down to 1.5V.

Well, clearly whatever is wrong with this construction has something to do with the inductance, and it's not purely the amount of inductance... Which brings us to the title of this post:

The mistake (probably)

Of course the data sheet of the voltage booster CLEARLY STATED that the inductance coil needs to be AS CLOSE AS PHYSICALLY POSSIBLE to the chip. The capacitors C1 and C2 too, by the way. And I even read that. But I thought, what could possibly go wrong if I move it ~1cm away to make some space for the battery? Nothing, right? Well, awesome, I guess it's time for another revision :)

At least the 2.4V were enough to power the Arduino, although it was visibly struggling. I could establish a Bluetooth connection and collect some signals, but the Bluetooth packets were coming in extremely slowly (though still faster than mobile internet in 80% of Germany.)




Somehow the oversized inductance coil adds a nice vibe to it.

Front, with battery:


Back, with attached Arduino:


This picture shows a pin strip socket that will be gone in the final version, where the Arduino will be soldered onto the board, reducing the height from 3cm to 2cm.

Side, with Arduino and battery:


(Yes, the pin strip socket is too long by one pin ;))

Power Module 3

Since Power Module 2 has the wrong PCB layout for the step-up converter, I built Power Module 3 to fix this issue.

It was still a worthwhile learning experience to build Power Module 2, resulting in the following changes:

  • Instead of stacking the Arduino and the Battery on top of each other (one on the front side of the board, one on the back), they're now side by side, to make the board flatter and fit better on the forearm.
  • Added more capacitors all over the place
  • Added various jumpers:
    • A solder jumper to enable/disable the reference voltage generator, in case I come up with a setup where I won't actually need it
    • A solder jumper to sacrifice one electrode and use its analog input pin to measure the battery charge instead.
    • Three configuration pins, connectable via jumpers, to change software settings on the fly and toggle between up to 4 different modes. Or you can use them to plug in an extra module.
  • Hopefully fixed the layout for the step-up converter

Here's the circuit:

circuit 9

And the new PCB:

PCB bp3 front side

PCB bp3 back side

If you're wondering why the sparky, fancy looking power line goes all the way from the power switch on the right through digital pin D10 and into L1 on the left side... Indeed that looks pretty awkward, but L1 is the noisiest component, and I wanted to keep it as far as possible from the analog pins at the bottom, without sacrificing the effectiveness of the boost converter layout. Given the size & time constraints, I didn't find a better solution.

What time constraints, you ask? Well, actually I made a different PCB layout first. Polished every detail, and when it was perfect (according to my crude appraisal), I ordered it. Was already excited about the delivery, started putting the board on the website, and so on. But at some point I noticed that something was wrong... The Arduino pins were inverted. Theoretically, everything would still work, but the Arduino would have to be plugged in from the back side, which is something I wanted to avoid to keep the board laying nice and flat on the forearm...

Thankfully the manufacturing process hasn't started yet, and I could update the board for free. So I started redesigning half of the board and finished just in time for the production to start :D

Let's hope it works this time.

Running on AAA battery

Wow, it feels like ages since I started working on making PsyLink run on a rechargeable AAA battery. It sounds so simple and straight-forward, but it wasn't :). This ate 2.5 weeks of my time, but finally I succeeded!

photo, tilted perspective

Coming from software engineering, the iteration time of hardware prototypes is horribly slow. There was a lot of waiting for package deliveries, a lot of time assembling, and a lot of wrestling with leaky abstractions. For example, it wasn't enough to just connect the 1.2V->5V boost converter like on the circuit diagram, but I had to take special care of the distances between the parts, and the widths of the copper tracks connecting them.

Another problem you never face in software engineering is that the package with electronics parts was stolen, and when the new PCB of Power Module 3 arrived, I had to work with the few remaining (suboptimal) parts that I had.

What almost drove me insane was that I had only one fresh TPS61220 chip left. That's the 5V boost converter at position U1 (in the bottom of the red circle on the photo below), which is so small that I don't really have the tools to solder it on properly. I kept accidentally connecting the pins of the chip with solder. I gave up and started asking around friends for whether they could solder it on for me, when I remembered this soldering tip someone gave me: If you don't have soldering flux (which I didn't have), just use ✨margarine✨ instead ;D. It sounds very wrong, but it actually made a huge difference, and only thanks to the power of margarine I was able to keep the solder exactly where I needed it to be. "If it's stupid and it works, it's not stupid."

Then - for whatever reason - the voltage was going up to 1.5V instead of 5V, just like with the previous PCB layout. I thought I fixed that problem by optimizing the layout around the TPS61220 chip, but apparently that wasn't enough. I figured the 4.7µH inductance at L1 wasn't big enough, so I squeezed in a second coil:

photo, coil acrobatics

(It looks like two tardigrades playing ball :) I wish I made a better picture before I disassembled it again)

This alone didn't help, but when I manually held an additional 10µH inductance in parallel to L1 for 1 second while the device was running, it surprisingly kickstarted and reached 5V!... until I drained some current, which made the voltage collapse back to 1.5V immediately. Curious behavior. :D

Then I tried soldering on the big 10µH coil directly onto the SMD pads, and the voltage reached 5V and stayed at 5V =)

photo, front

No idea why the big 10µH coil worked while the two smaller coils totaling 9.4µH didn't work... I doubt that the 0.6µH difference in total inductance turned the tide, probably there's some factor I'm not aware of. I actually had ordered a 10µH SMD inductance coil in anticipation of this, but well, it got stolen... My only consolation is the face of the package thieves when they open the package, they realize that it's just a couple of tiny SMD parts, and they wonder WTF this shit is even good for.

P.S.: I found out that the reason why the coils didn't work was that they were not rated for the >200mA that's passing through them. Once I got a 4.7µH coil rated for 280mA, everything was fine.

More pictures:

photo, side photo, back

The lack of parts forced me to adjust the resistance/inductance/capacitance values of Circuit 9 (power):

circuit 9.1

Thankfully I had planned for way too many capacitors on the PCB, just for some extra VROOOM, so the fact that I only had 10µF capacitors instead of the planned 100µF didn't matter too much.

I also changed the 1MΩ resistors in the reference voltage generator to 110kΩ because I read that smaller resistances in a voltage divider make the output voltage more stable, at the cost of more power use, but I think we can sacrifice some power for signal accuracy. No idea whether it's actually going to help though. I chose 110kΩ instead of the more common 100kΩ and 220kΩ because the boost converter already requires a 110kΩ resistor, and that way this prototype requires fewer different parts. But the exact values don't matter, as long as both resistances are identical.

Tomorrow I'll start working on the electrodes and wristband. :)

Cyber Wristband of Telepathy +2 [UNIQUE ITEM]

Power Module 3 finally found a home: Sleeve 4. Looks a bit like a Pip-Boy from the Fallout Series :)

photo, closed

Under the hood there's 9 electrodes (1x ground, 8x signal):

photo, open

New Frontpage + Logo

The front page now looks a little more "modern", and I changed the logo from

old logo


old logo

Once again, this was inspired by the System Shock 2 Trioptimum logo.

Neurofeedback: Training in both directions

For now, the training of neural networks mostly happens on the AI side. The human makes arm gestures and presses keys on the keyboard. This provides the input (electrode and IMU signals) as well as the output/labels (keyboard actions) to the artificial neural network, which then learns the correlation between the two through supervised gradient descent.

Now I'm looking into how to train both the neural network of the AI as well as the nervous system of the user through neurofeedback, that is, by making the user more aware of their neural signals, which in turn allows them to fine-tune these.

My hope is that this will make up for the low quality of information that's available to the AI, due to noise, attenuation, and the low number/quality of electrodes. The user neither knows what signals the electrodes can access, nor how to willingly produce movements that create these signals. Some gestures work well, while others can't be detected at all, so the best bet is to use forceful gestures with maximal muscle activation. But if there was some sort of feedback to the user, like a visualization of the data that the neural network is extracting, the user could focus on the movements that work, and gradually lower the intensity, perhaps to the point where no actual movement is required anymore.

Of course there is already some feedback about the signals: The PsyLink UI shows the amplitude of each electrode in a rolling graph, and the GNURadio application shows detailed plots of the raw signals, both of which already help determining which movements will work for gestures and which will not. But the AI can of course combine, cross-correlate, filter, convolve and deconvolve the signals, which enables it to extract information that a human won't see in the raw signal data.

Ultimately, the goal is that the user learns to, on demand, fire off just enough neurons that PsyLink can pick up the signal and trigger the intended key press without any visible movement of the arm.


As described above, simply presenting the user with the raw electrode data is insufficient. A machine-learning approach will likely be optimal here, to overcome the preconceptions of a top-down designer. Since we already have an artificial neural network, why not use that one to generate the visualizations too?

In my current version of this idea:

  1. The user needs to invent some arbitrary gesture that should correspond to the action "Press key 'A'".
  2. The user is repeatedly asked to perform the gesture by the UI
    • At random intervals
    • For random durations
    • With 2-3 seconds of heads-up warning to account for reaction time
    • In between the gestures, the user should perform random other activities, but never do the gesture without being asked by the UI
  3. The AI is trained on the fly with
    • Electrode signals as input
    • A binary label of "Key 'A' pressed" vs. "Key 'A' not pressed" as output
    • Each data point is added randomly (80:20) to the training or validation dataset
    • After X seconds of collecting data, the AI is trained for Y epochs
  4. Every Z milliseconds, the AI is asked to predict the output from the current input, and the neural activations of the last non-output layer of the NN are presented to the user visually, along with the predicted output.
    • The visualization could be a heatmap or a scatterplot, for example
    • The visualization should cover a large dynamic range (both small changes and large changes to the values should be easily visible)
  5. Using the feedback, the user can tweak their gesture as desired, to e.g.
    • Minimize the movement required to trigger the key
    • Maximize the reliability with which the key press is predicted
  6. Over time, old data is dropped from the NN training to refine the visualization and to keep the training time short.

Once the user is ready, they can add a second action like "Press key 'B'" and so on.

Batch Update

I haven't been posting recently because I've been focusing on other areas of my life, but there has still been progress with PsyLink:

Prototype 6 improvements

I redesigned Power Module 3 to be more easily hand-solderable by enlarging the solder pads and adding thermal clearances to some of the filled copper areas. (The copper tracks to several pads were so wide that the heat of the solder iron was dissipating too fast into the copper, and the pads were not heating up properly). The result is Power Module 3.1.

Prototype 7

PerlinWarp reached out to me, and after some fruitful conversations, I build a Prototype 7 for him for research purposes. It's a hybrid of Prototype 4 and Prototype 6 which combines the advanced Power Module 3 with a cluster of Electrode Module 1 attached to Sleeve 3.


The assembly of the Prototype 7 took a full 20 hours of mindless labor, so I had a LOT of time to think about improvements to the design that would make it easier to assemble:

  • Instead of having small boards for differential amplifiers that have to be tediously connected with three fragile wires, bulk four of them up in a single board.
  • Instead of having a piece of custom-tailored fabric with precisely placed electrodes, use electrodes made of metal screw-like parts that fit right on to the PCB. The PCBs are held together with a rubber band that presses the electrodes tightly to the skin.
  • Made Power Module 3 more easily hand-solderable (described above)

Prototype 8 (WIP)

The 8th prototype implements those changes, resulting in a device purely made of PCBs connected by rubber bands and wires. These PCBs rest on the skin on legs of metal, which double as the electrodes.

As of now, only the differential amplifiers are finished. The circuit for these is Circuit 10 (electrodes):


The front-side of the Electrode Module 3:


The four wide holes in the board are connection points for rubber bands, and the eight round metal-plated holes are mounting points the electrodes. These consist of a screw on one side, a nut on the other, holding both metal pieces tightly in place.

The electrodes can be spacer screws like these or dome nuts like these. While the spacer screws seem to pick up a better signal, the dome nuts are considerably more comfortable thanks to the rounded cap, so I think I'll stick with these for now.

Dome nuts are also called "hutmutter" in German, which translates to "hut's mother" (my nickname is hut), so just because of that fact, I had to try them out.

Additionally, one can use the pins EX1 through EX8 to connect arbitrary external electrodes.

A first prototype using Electrode Module 3 and Power Module 3.1 (with an improvised rubber band mounting mechanism) can be seen here:

outside view

inside view

I played around with using off-the-shelf wet EMS (electric muscle stimulation) electrodes for the ground electrode, since good connectivity for the ground electrode is important for a good signal.

outside view with wet electrode

I did not find an improvement in the signal though, perhaps wet electrodes are not worth it.

Finally, the global microchip shortage has affected this project as well, and I could not find any sources for the power converter chips (TPS61220 DCKR) that boost the battery voltage of 1.2V to the required 5.0V. I still have some legit chips left, but in the long term, I need more of these, so I acquired some chips from Shenzhen via AliExpress. They have been advertised as "Original new, 100% quality", so what could POSSIBLY go wrong? But I tried them out, and they actually do their job quite nicely.

Future plans

The power module is currently only clumsily attached to the rubber band. The finished Prototype 8 will need a power module that's more compatible with the Electrode Module 3, by making it as long as the Electrode Module 3, and either by adding rubber band mounting holes, or by adding pin headers so that it can be stacked on top of the amplifier board, which would reduce the number of dangling wires as well.

I will also try out cheaper differential amplifiers to reduce the total cost of the device from ~70€ to ~30€ (excluding the ~39€ for the Arduino Nano 33 BLE Sense).

Power Module 4

Prototype 8 needs a matching power module. I can't continue to awkwardly stuff the rubber band between the velcro and the PCB of Power Module 3 like this:

showing a p8 with a very awkward rubber band construction

We need a PCB with proper rubber band holes and screw mounting points, so it can be worn along the radius bone with about 2x Electrode Module 3 beside it.

Unfortunately the large dimensions of the Arduino and the battery make it a little difficult. There's several options to do this, but none of them are perfect:

  1. Place Arduino and battery beside each other like in Power Module 3 and either...
    1. make the board ~15mm longer to fit the holes.
    2. make the board ~12mm wider to fit the holes.
      • Downside: It would be too wide to comfortably fit on the radius bone
    • Downside of both options: it might feel unbalanced when worn on the side of the arm, because the heavy battery moves the center of mass off to the side
  2. Place Arduino and battery on top of each other, with pin sockets for the arduino that are taller than the battery, then make the board the size of Electrode Module 3 to fit the holes
    • Downside: It might be hard to acquire pin sockets that tall
    • Downside: Little space left for the holes and the remaining components, but might work
  3. Place Arduino and battery in a line next to each other and make the board 20mm longer and 8mm wider than Electrode Module 3 to fit the holes.
    • Downside: The rubber bands are relatively close to the center, reducing the force with which the far ends of the board are pressed onto the skin
    • Downside: The large dimensions might make it too bulky
  4. Remove the Arduino and solder the NINA-B306 bluetooth module of the Arduino onto the board directly, along with all the peripherals I need
    • Downside: Unnecessary complexity
    • Downside: More difficult soldering
  5. Instead of adding any holes, just stack the board on top of a Electrode Module 3 and use its screws and rubber band holes for physical support. (Thanks to PerlinWarp for that idea!)
    • Downside: Would require a redesign of Electrode Module 3
    • Downside: The height of the prototype might make it feel unbalanced
    • Downside: The board would have be either wider or longer than the Electrode Module 3 due to the dimensions of the Arduino and battery. As a result, it would stick out to the sides, unless I enlarge the electrode board as well.

In the end I chose option 3 for simplicity reasons, and because the downsides seemed the most acceptable. This also gives me a lot of space on the PCB which is currently not needed, but may be used for analog multiplexing later on, to allow supporting more than 8 electrodes.

I am quite tempted by option 2 though, it would make for a really compact board. Maybe I give it a try later (if I ever find a source for 1x15 pin sockets that are 14mm+ tall and 2.54mm spaced apart.)

Here is the resulting board. As you see, I also added a screw mounting hole in the center, which should point right at the bone, which perhaps makes for a great ground electrode. Any of the screws can be used as ground electrodes though, simply by closing their respective solder jumper. I will try out various combinations to see which one is best.

PCB bp4 front side

PCB bp4 back side

The matching circuit:

circuit 11

I ordered the production of this board already, and I'm excited to see if it will work out like I imagine. :)

Fun story on the side: I ordered the boards on Aisler, and they let you change the PCB design for free until it hits production. This time, I had a couple of hours left, which I used to make a couple of adjustments here and there, until I was happy and went to sleep. After 3 hours I woke up, with racing thoughts, and I couldn't really fall asleep again (which happens very rarely). After laying awake for 2 hours, it occurred to me that I should run the automatic PCB layout check of KiCad once again to test my board for obvious mistakes. Of course I had run the check before submitting my order, and several times after doing my various modifications. But as it turned out, I had indeed forgotten to run it on the final version, and there were multiple errors too! Several unconnected nodes and some copper tracks that were too close to each other. Luckily I caught this just a couple minutes before my time for free modification ran out, and fixed it just in time. Thanks insomnia.

INA155 Instrumentation Amplifier

I tried replacing the INA128 chips on the Electrode Module 3 with INA155 chips with a Gain of 50, and it works just fine :) The signal even looks a little bit cleaner than with the INA128, though I don't have good metrics to decide which one is better overall. They both have the same PCB footprint so I didn't even have to change the board design :)

This is good news. If I buy the INA155 chips in bulk (250+), they would cost ~1.75€ each (and I currently pay ~5.65€ per INA128), which would bring the material cost of the whole product down from ~60€ to ~30€ plus Arduino (~38€) plus shipment. Even if the INA155 is slightly worse, that's totally worth it.

At this price, it would even be affordable to use more than 8 signals (with additional analog multiplexing, since the Arduino only has 8 analog inputs) and wear more than two Electrode Module 3 at the same time.

Another big plus is that INA155 chips can easily work with a supply voltage of 3.3V!! And I wouldn't need to boost the battery voltage all the way up to 5V anymore, which is probably not very power efficient.


I did some more tests and concluded that with the electrodes that I'm currently using, the maximum gain of INA155 is not high enough, and I have to either find better electrodes, add extra amplifiers, or switch back to INA128 for the time being. For now, the relatively expensive INA128s will have to do.

But hey, the current electrodes are literally just... plain metal spacer screws, so there is DEFINITELY room for improvement.

Here are some pictures of electrode placement and resulting signals, where you can see that the INA128 (blue line) shows considerably more features:

resulting signal

electrode placement

Prototype 8

The order of the PCB of Power Module 4 has arrived, and so all the parts for Prototype 8 are finally here :) After some assembly (and crimping of some rainbow-colored connectors that look a little neater than those stray black wires from previous photos), this is the final picture:

photo of the p8

And another picture:

photo #2 of the p8

The Signal

A sample of the signal is this, using an INA128 with a gain of x228 and electrodes near the flexor digitorum superficialis:


The baseline is the midly noisy line around a value of 0.3 and shows the state of rest.

The spikes and "spindles" (periods of higher amplitude) occured when I performed various movements, like extending the arm, snapping the fingers, or twisting the wrist.

Bugs in the BP4

The Power Module 4 is not perfect though:

  • The solder jumper J8, that activates the central Screw 5, overlaps with the battery clip, resulting in a short circuit with the battery's ground, unless I put some isolation tape over the jumper... Need to move the jumper further away.
  • The power switch (SW1) is too close to the Screw 2, so the switch I wanted to use didn't actually fit, and I had to fall back to one that points off to the side, and looks a little awkward.
  • I also wish that the analog pins were closer to the power pins, so that I can bundle up the wires, resulting in what would appear like one single connector, rather than two, per Electrode Module 3. Although this may lead to EM interference between the wires, reducing the quality of the signal, so maybe it's actually better this way.

Prototype 8 Demo Video

The demo video of Prototype 8 is out now:

HackChat & Hackaday Article

Someone at Hackaday kindly invited me ("hut") to host a Hack Chat about Electromyography and PsyLink on Wednesday, January 19, 8 PM GMT. There, I will answer all sorts of questions from the hackaday community.

Drop by too, and watch me struggle for an hour to pretend that I know what I'm talking about :)

Someone else at Hackaday also kindly wrote a whole article about PsyLink, which sparked nice discussions in the comments, got the P8 Demo Video over 5k views, and inspired several tinkerers to reach out to me about getting their own PsyLink :)

Prototype 9 + Matrix Chatroom

News #1: PsyLink now has a Matrix chatroom:

News #2: PsyLink Prototype 9 is now out, which is pretty much the same as Prototype 8, just with a few bugfixes and enhancements. Notably:

  • The Power switch now actually fits on the power module
  • The Battery clip doesn't intersect with a solder jumper anymore, which used to cause a short-circuit unless you'd cover it up with tape
  • The built-in electrodes on the electrode modules now can be activated/deactivated via solder jumpers, which allows you to use external electrodes while wearing the PsyLink regularily, without the built-in electrodes interfering with the signal.

Obligatory Picture:

photo of P9

It's less colorful and has more boards than the photo of the P8, but that's just the type of wires, and an additional electrode module. You could make the P8 look the same way.

Mass production

More and more people are asking me to send them a PsyLink prototype! I've written some Tutorials to help the users to get started, and I'm working diligently to assemble them all. Can't wait to see the ways in which they will be used. :)

photo of 15 PsyLink modules

Request your own pre-assembled PsyLink now too!

Unlike software, unfortunately, you can't just download a PsyLink and use it right away. It takes me about 1-1.5 hours per module to assemble these. I wish I could automate and outsource more of the assembly process, but I don't see a low hanging fruit worth exploring so far. Still, I'm happy about the progress, since I'm now ~5x faster than when I sent out the first Prototype 7.

Currently, the assembly process consists of:

  1. File off the rough break-off points on the PCB to avoid scratching the skin
  2. Solder on the SMD components
  3. Do optical quality tests, as well as tests with a multimeter on critical parts
  4. Since my pin sockets have 16 pins and the Arduino has 15 pins, I cut off one of the pins of the socket
  5. Cut the downward-facing pins of all through-hole components down to ~1.4mm so that they don't stick out of the PCB and possibly scratch the skin
  6. Solder on the Through-hole components (except battery clips)
  7. Plug in the battery clips, bend its pins inward so that they don't scratch the skin, (the end may break off but that's ok), and solder them on
  8. Clean off solder flux stains with Isopropyl Alcohol on the sides that face the skin
  9. Cover the bottom of the power module with insulating tape to avoid skin contact
  10. Screw on the electrodes / legs
  11. Wire up everything as described in the wiki
  12. Push the elastic band through the respective holes to connect the boards together
  13. Do a test run of the entire system

Outsourcing pick&place and soldering of the components would be helpful, but the through-hole components (pin headers/sockets, switch, battery clip) need special treatment: I have to trim the pins so that they don't stick out of the PCB and scratch the skin. I doubt that any pick&place contractor will do this for me. This close-up shot of a Electrode Module 3.2 shows it well, that there are no sharp points under the pin headers, just round solder blobs:

Close-up of a B3.2 board

But I could at least outsource the soldering of SMD components. Let's see if I can find something cheap.

If you have tips to accelerate the assembly process, please reach out to us.

Next Steps & Resources

The PsyLink Wiki now contains two new pages:

  1. Next Steps documents potential directions that he project could take in the future
  2. Resources points to external pages that are connected to PsyLink, similar projects, related news, papers, and educational material.

If you have suggestions for potential next steps or know about interesting links, please let me know, or add them to the wiki. :)

Microchip 6N11-100

In my quest for premature optimization, I tried out yet another instrumentation amplifier chip: The Microchip MCP6N11-100. At 1.55€, this chip is about 4 times cheaper than the INA128 instrumentational amplifier (which is currently the cost bottleneck), and would make a 16-electrode-PsyLink about half as expensive. It also works with as little as 1.8V (while INA128 requires 4.5V), eliminating the need for power conversion if a 3.7V lithium battery is used.

Unfortunately the pin configuration is different from the INA128 that the Electrode Module 3.1 normally uses, so I had to jury-rig the board a little:

photo of a MCP6N11-100 on a PsyLink Electrode Module B3.1

But it worked, and the signal (the first one) is similar enough to those of INA128s (the last 4):

Screenshot 1 of signals with the MCP6N11-100 chip Screenshot 2 of signals with the MCP6N11-100 chip

These were recorded with a Prototype 9.1 with two Electrode Module 3.1, one with 1x MCP6N11-100 at a gain of x501, and one with 4x INA128 with gains of x501 as well. I'm wearing it much like on the P8 demo video, except that there's two electrode modules side by side, not just one.

In the top center of the first picture (light blue signal), you can see that there is some clipping in the negative peaks of the wavelet, which is not great, but other than that, it does seem to show very similar signals. (They shouldn't be identical, of course, because each signal measures electrodes at different locations on the arm)

There's also a similar chip, the MCP6N16, which has a smaller footprint size and better performance, but has slightly higher cost and worse availability. It's more difficult to solder, too. But it's good to know that there's the option to switch to that one if we ever need to.

I'm quite happy with this result, and perhaps the next iteration of the electrode module will be designed for this chip rather than the INA128. :)

3M Red Dot electrodes

Alex Lao suggested to try some 3M Red Dot electrodes, and so I got me some of the model 2248-50 (he actually suggested model 2660 but I mixed it up.) They are used for ECG patient monitoring, which is close enough, right?

photo of the electrodes

I connected two of them to EX1 and EX2 on an Electrode Module 3.1 and placed them on the flexor digitorum superficialis muscle (where I place the built-in PsyLink electrodes on most of the other pictures/videos too), and placed a third electrode on the radius bone near the wrist, and connected it to a Vref pin of a Power Module 4.2, which therefore acted as a ground electrode. The electrode module is the one from the previous blog post about the MCP6N11-100 instrumentational amplifier (for no good reason - I should have used INA128 for better comparability).

This is what they look like on my skin:

Photo of the electrodes on my skin

I recorded the following signals when pressing different fingers onto the table:

Screenshot of signals

The amplitudes of the wavelets were a little disappointing, but perhaps boosting the gain from 501x to 1001x-2001x would help.

The nice surprise was the specificity of the signals. I only saw signals when I actually used that muscle. Unrelated movements like twisting the wrist sometimes produce strong signals with the built-in PsyLink electrodes, but produced no signal with these. There could be many reasons for that:

  • The "unwanted" signals may be too weak to be visible against the noise
  • There are less mechanical artifacts from electrodes moving around
  • The ground electrode is closer to the wrist here, whereas in the default configuration, it's closer to the middle of the bone.

It's good to see that it works, and there's clearly a potential, but I'm not blown away either. Next steps could be:

  • increasing the gain
  • trying electrodes with better adhesion like the 3M 2660

Note that before attaching the electrodes, I did not shave off hair and did not clean off skin oils with alcohol, but at least I was fresh out the shower. Ok, time to end this post, this is getting weird :).

2022 Retrospective

I've gotten out of the flow of writing blog entries, but that doesn't mean we have been idle. There has been progress in the PsyLink sphere along various fronts and I could make several blog posts out of it, but I want to try something new, and summarize everything in a 2022 retrospective post:


Early in 2022, Hackaday released an article on PsyLink (see HackChat & Hackaday Article) which pointed many eyes towards this project, and inspired several follow-up blog posts on other platforms:

Around 30 people have reached out to me following those blog posts, with their own stories, suggestions, and requests for collaborations, for which I am extremely grateful.

I could make arrangements for 8 people in 2022 to get their own PsyLink device for their personal research. (See also: Mass production) This is quite a small number, especially when compared to the spread of software-only projects, which anyone can obtain through a click of a download-button.

But let's look at the bright side: Instead of serving a large number of casual users, I served a smaller number of serious, enthusiastic users of which most have contributed back to the project. Thanks to all the new users for collaborating with me, it was a pleasure so far!

Yet, I'm looking into how to improve that number in the future, perhaps by outsourcing production or through cheaper components, faster assembly, and better advertising.

In total, there are now 9 PsyLinks in the wild: 4 in Europe, 4 in the USA, and 1 in Canada. That's 1x Prototype 4, 3x Prototype 9.1, 5x Prototype 9.2.

Prototype 9.2

The design of the PsyLink Prototype 9.2 was finalized in early 2022, and has remained the standard prototype since then.

The modular setup of electrode modules allows custom-tailoring to specific purposes. The photo above shows a dense electrode layout (only 2 electrode modules with 8 electrodes each), but it's also feasible (although cumbersome) to go for an 8-electrode-module setup for maximum flexibility:


AntonX' Electrode Module for MCP6N11

The Microchip 6N11-100 seems quite promising for use in an electrode module, and AntonX designed a PCB that supports this chip natively:

front side of the PCB

See also:

Thanks a lot to AntonX for designing this!

Hopefully I get to test out this board soon and evaluate how it compares to Electrode Module 3.2.

Before ordering it, I wanted to do some polishing: The connector for the signals (S1 through S4) should be at the top rather than bottom, like in Electrode Module 3.2, and the label with the link ("") should be on the front side rather than the back side, but that's relatively minor problems and maybe I should just go ahead and order it as it is.

3D-Printed Case

It's not a long-term solution to wear raw circuit boards on the skin. (Or is it?) John Shahbazian saw an opportunity, and designed a 3D-printed case for PsyLink's Power Module:


Thanks John for designing the case, this is a good start! I tried out printing it with the help of a friend successfully and it fits well, though we couldn't quite get the hinge to work.

What I would personally change:

  • The hole on the side should rather be two holes, lined up with the holes on the power module PCB itself, so that the rubber band that holds the modules together can easily go through.
  • Currently there's only one hole at the bottom, for one of the electrode screws. Since the user can choose which ground electrode they can use (and also for symmetry reasons), there should be 5 holes for all the electrode screws on the power module.

You can get the source files here:

John also built a convenient MacOS user interface for plotting PsyLink's EMG signals:


You can find his project on GitHub. Note that the software is not officially supported.

PsyLink is mainly an EMG sensor, but can be turned into a wide variety of appliances. The power module, e.g. Power Module 4.2, can be used as a battery powered breakout board for the Arduino Nano 33 BLE Sense for any purpose besides neural interfacing.

For example, due to a domestic flooding situation, I wrote some quick-and-dirty code for water detection, plugged a PC speaker and 2 wires onto the PsyLink, and now it makes a siren sound whenever water touches the wires:


And of course PsyLink can also be used to power LEDs for a mobile, battery-powered mood light, see this mastodon post:


This is taking advantage of PsyLink's boost converter without using the Arduino at all:



PCBWay has offered sponsorship for free PCB prototyping to the project, for which I'm very grateful. We haven't actually made any use of this sponsorship so far, but may do so in the future.


By the end of 2022, the project has cost me (Roman, the main author) about 2500€. (excluding lost income)

The total income from donations and PsyLink-related consulting work was about 1850€, which is more than I ever dreamed of earning from an open source project! Yet, it's not quite enough to cover the costs, and certianly not enough to pay my bills. (Not that making money was ever a priority of this project.)

As a result, I am currently looking for paid work as a freelance software developer, so that this project can stay independent and free. If you know of any company in the field of neural interfaces, medical devices or biotechnology that's looking for a freelancer to get some IT work done, let us get in touch!

What's Next

Hopefully the funding situation improves soon and I can dedicate more time to PsyLink and take on the next steps which are outlined in the wiki. :)

But of course there are now other PsyLink users out there and I am very excited what other contributions will come from the community.

Rochester Institute of Technology's Neurotech Exploration Team (NXT) is currently getting set up with their PsyLink and is looking into getting it to run on Microsoft Windows, and to control a 3D-printed robotic arm with PsyLink.

Good luck to everyone in the open source neural interface community, a big thank you to every PsyLink contributor, and a successful 2023 to you all! :)

Sample Signals

On popular request, I have uploaded some data sets of recorded signals, along with videos of their recordings.

They can be found in the new git repository "psylink-datasets". Here's a quick overview:

Spelling Out "hello"

Here, I recorded 4 different gestures to produce 4 different keys, "h", "e", "l" and "o", obiously to be able to spell out the word "hello".

Unlabeled Samples

Here I perform various arm movements and simply display/record their signals.

Enhanced Signal by >1000%

Through a very simple change in the circuit, we've been able to greatly enhance the EMG signal captured by PsyLink!

On the suggestion of Farzam, I took a closer look at the high-pass filter at the very beginning of the signal processing pipeline in Circuit 10.2 (electrodes) and it turns out that any signal under 1,600Hz is being weakened. This is a big problem, since the EMG signals that we are interested in are approx. 5-500Hz. By changing the capacitance from 100pF to 100nF, the cut-off frequency of the high-pass filter is shifted to 1.6Hz, leaving the EMG signal intact, while still removing low frequency noise and DC voltage.

The signal-to-noise ratio is through the roof. See for yourself:



Red = before, Blue = after.

Some more details, if you're interested: These are two signals at out1 (blue) and out3 (red) on Circuit 10.2 (electrodes) where C1 and C2 have been changed from 100pF to 100nF while C5 and C6 have been left unchanged. The electrode pair of out1 is in a row and side-by-side to the electrode pair of out3 on the same muscle (flexor digitorum superficialis muscle, as usual), about 2cm apart, so they record almost the same information.

It's even more impressive if you consider that the red signal is 16x magnified in software. The red signal spans ~300mV whereas the blue one spans ~5V, making use of all the 12 bits of the Arduino's analog-to-digital converter (though the bluetooth connection currently transfers only 8 bits. To be fixed in the future.)

What I am especially excited about:

photograph of two electrode modules side by side. the left one uses the more uncomfortable electrode, the right one the more smooth, rounded, comfortable electrode

We can switch from the spacer screw electrodes (on the left) to the dome nut electrodes (on the right)! These are infinitely more comfortable, and mean that you can easily wear the PsyLink for hours.

The spacer screws bite into the skin and produce a better signal, but cause pain after a while. With this kind of ground-breaking improvement in signal quality, this trade-off is not worth it anymore and the dome nuts make more sense now.

In the coming days I will update the schematics to reflect these changes.

I highly recommend PsyLink users to swap their 100pF capacitors (C1-C8) for 100nF capacitors on their electrode modules. If you do not want to do this yourself, you will be pleased to hear that we are offering every existing PsyLink customer an upgrade free of charge. We will cover the material and delivery cost for you. Simply contact us if you're interested in the upgrade.

Prototype 10

I'm excited to announce that we reached the double digits with Prototype 10! 🥳

As the most advanced prototype so far, it's more comfortable, more sensitive, and cheaper than any of the prototypes before (if we don't count the super-cheap early prototypes that don't use any amplifiers.)

The three big changes are:

  1. Enhanced Signal by >1000% by optimizing the passive high-pass filter before the amplifiers, as described in the previous blog post. See Circuit 10.4 (electrodes). (thanks Farzam!)
  2. Switched to cheaper Arduino Nano 33 BLE (without the extra sensors of the "Sense" model, which were actually not needed anyway)
  3. More comfortable rounded "dome nut" electrodes, as you can see on this photograph:

Photograph of the Prototype 10

Along with this release, I have cleaned up the schematics folder in the git repository. and upgraded from KiCad 5 to 6. It should now be much easier for you to open/edit the PCBs/circuits. (Thanks AntonX!)

By the way, PCBWay kindly helped out by sponsoring their services, and I gave it a try and ordered pre-assembled PCBs. I never did that before, and of course, I made a bunch of mistakes with the order, but fortunately they quickly reached out to me, free of charge, and we fixed my mistakes before they went into production. I was very happy with the results and got exactly what I wanted on the first try. This kind of hand-holding sure takes off some pressure from experimenting with new technologies :) PCBWay also offers metalworking services, maybe it's finally time to dive into that and order some custom electrodes!

I hope you're also enjoying the continuous improvements I'm making to the website design, such as the rounded corners on the blog posts (only when more than one post is visible), the separator gaps between them.

Thanks to everyone who contributed ideas, code, financial support, and anything else to this project. For this release, it's especially Farzam Khodajoo and AntonX. We wouldn't have made it this far without you. Stay tuned for more updates! :)

Data Sheets

After learning about the 4-document-model (permalink), an insightful guide to writing better documentation for software projects, I realized that PsyLink really suffers from having its documentation so spread-out among the dozens of pages with no clear reference page that contains it all.

As a first step to mitigate this, I wrote extensive data sheets for the power module and the electrode module, bundled right along with their source in the schematics folder. You can find them here:

Hopefully this will help you to get the most out of the boards and reduce the mistakes you do while replicating or using them!