Demonstration of a Low Cost EEG Circuit

Summary

In this video, the presenter demonstrates a brain-computer interface (BCI) project based on EEG (electroencephalograph) technology. They explain how the system, using a single-channel EEG circuit with STM32F4 microcontroller, measures brain signals. Homemade, cost-effective electrodes are used to capture alpha waves, triggered by eye closure and relaxation. The system includes a simplified keyboard where users select letters by focusing on flashing checkboxes. While the BCI successfully measures steady-state visually evoked potentials (SSVEPs), more work is needed to improve real-time signal extraction. The presenter plans to share further details and code on their blog.

Takeaways

• 🧠 Overview and demonstration of a Brain-Computer Interface (BCI) project based on electroencephalograph (EEG) technology.
• 🛠️ The EEG circuit used is single-channel, with two measurement electrodes, and samples at 1000 Hz.
• 🔋 The system is isolated from the PC using optocouplers and powered by a 9-volt battery.
• 👂 Homemade electrodes were crafted using ECG pads, making them much cheaper than commercial EEG cups.
• ⚙️ The electrodes reduce electromagnetic noise by twisting the wires, allowing clearer signal detection.
• 📉 Initial tests focus on detecting alpha waves (around 10 Hz), which can be triggered by relaxation and closing eyes.
• 📊 Real-time signal trace and FFT analyses help in identifying EEG spikes, such as the alpha wave response.
• 👀 By using flashing checkboxes at different frequencies, the BCI attempts to trigger steady-state visually evoked potentials (SSVEPs).
• ⌨️ SSVEPs allow the user to interact with a simplified on-screen keyboard by focusing on a specific checkbox, enabling hands-free typing.
• 🔄 Further work is needed on signal processing to improve reliability in real-time feature extraction of EEG signals.

Q & A

What is the main objective of the project discussed in the video?

The main objective of the project is to design and build a Brain-Computer Interface (BCI) that can measure brain signals using an Electroencephalograph (EEG) and communicate those signals to a computer.

What hardware is used in the EEG measurement circuit?

The EEG measurement circuit uses an STM32F4 microcontroller with a single-channel EEG measurement setup, two measurement electrodes, a driven right leg ground for noise reduction, and optocouplers for circuit isolation from the PC.

Why are optocouplers used in this BCI setup?

Optocouplers are used to isolate the circuit from the PC, ensuring electrical safety and reducing the risk of noise interference from the computer.

How are the electrodes created for this project, and why is this method chosen?

The electrodes are created using ECG pads, with a DIY method involving rubber shower hose washers and conductive gel. This method is chosen to keep costs low, as commercial EEG electrodes can be expensive.

What kind of brain activity is the system designed to measure, and how?

The system is designed to measure alpha waves, which are brainwaves at around 10 Hz that occur during wakeful relaxation. These are detected by having the user close their eyes, triggering a measurable spike in the EEG signal.

What is the purpose of the driven right leg circuit in this setup?

The driven right leg circuit is used as a ground reference, helping to reduce interference on the body, particularly 50 Hz noise from mains voltage.

How does the project use Steady-State Visually Evoked Potentials (SSVEP)?

The project uses SSVEP by displaying flashing checkboxes at different frequencies on a simplified keyboard. When the user focuses on a specific flashing checkbox, the BCI detects the frequency response in the brain and selects the corresponding letter or character.

What challenges does the developer face with the current BCI system?

The developer faces challenges with reliable feature extraction in real-time signal processing, as the system currently struggles to consistently recognize SSVEP signals accurately.

What improvements does the developer plan to make in the future?

The developer plans to improve feature extraction and signal processing to achieve more reliable real-time detection of SSVEP signals, which would enhance the functionality of the BCI.

Will the developer share more details about the project, and if so, how?

Yes, the developer plans to share instructions on how to build the circuit, the code, and other resources on their blog in the future.