Welcome to the weekly FANTM Microupdate (the full size update is on a month-to-month basis and can be found here). This week we’re exploring one facet of utility power you might not usually worry about: the frequency. The electricity you get from your wall is AC, meaning it has a non-zero frequency and an amplitude, in fact it is a sine wave. The tricky part is that it looks a little different depending on where you are in the world. In the U.S. our mains power runs at 60 Hz, Europe it’s nominally 50 Hz, and if you’re actually a train in Switzerland, you would find it’s 16.667 Hz. In many electronics applications this wouldn’t be something worth worrying too much about, however when measuring biopotentials (like EMG), we’re trying to amplify incredibly weak signals.
One of the weak signals we end up accidentally measuring is the electricity in the walls around us, going through the air and amplified through you: the human antenna! The easiest way to see this effect is by putting on your FANTM DEVLPR, using Arduino’s serial plotter, and reading the raw data being collected. If you’re using a device plugged into an outlet in the U.S. you’ll see the orange line in the graph pictured below, and if you move your hand closer to the outlet you’ll actually see that main 60 Hz signal get stronger and stronger. We can see a small amount of noise becoming a big problem, blocking us from seeing the muscle activity we’re interested in. So how do we make our signal look like that green line?
There are two places to look for a solution: hardware and software. The hardware solution is a band-stop filter, sometimes referred to as a Notch filter. It stops amplification of a certain frequency in a signal. The downside is that it’s implemented on the actual device, so it might work great in the U.S., when you need to block 60 Hz, but it wouldn’t do anything for you in Europe where you want to stop 50 Hz. That’s why FANTM prefers to solve our problems with software; by implementing IIR software filters we’re able to mimic hardware filters and dynamically change the filter based on your location. FANTM has been focused on fine-tuning these filters over the course of this last week, greatly improving the DEVLPR's signal-to-noise ratio and opening up new, exciting possibilities like gesture recognition and higher fidelity control mappings. If you want a longer demo in how the filtering works, checkout one of the videos we've made, linked below.
That's all for this week and the first FANTM Microupdate. Feel free to post any questions below and we'll do our best to answer them, or leave feedback so we can make the next one even better. Thanks for reading, and we hope you learned something! 💪🤖