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
