Building a Brain-Controlled Mobility Device after spending the last few weeks planning, researching, and collecting hardware, I’ve officially started work on my brain-controlled mobility device project.
The goal is to build a prototype that can be controlled using EEG (brain signals) and EMG (muscle signals). My long-term vision is to explore assistive technology that could help people with limited mobility interact with devices more naturally.
Hardware so far

Raspberry Pi 5

ESP32

Arduino

BioAmp EXG hardware

EMG sensor

DC motors and motor driver

Battery pack and chassis

What I’ve done
✅ Learned the basics of collecting EEG and EMG signals
✅ Tested the BioAmp hardware and verified I can read signal values
✅ Started designing the software architecture for how everything communicates:

EEG/EMG acquisition

AI signal processing

Motion prediction

Wireless communication

Motor control

Biggest challenge
One of the biggest hurdles has been figuring out how to reliably combine EEG and EMG data into something an AI model can actually understand. There’s a lot more preprocessing involved than I expected, but it’s been fun learning about biosignal processing.
Next steps

Collect a dataset of EEG and EMG signals

Train an AI model to recognize different commands

Connect the Raspberry Pi with the ESP32

Test the first driving prototype