Electroencephalography: Mapping Brainwaves for Interface Innovation
Consider a future in which a single idea generates a quick response from an artificial intelligence linked to the huge internet information network. This is the ultimate achievement of human-computer collaboration and reflects significant advancement.
This article show the meaning of brainwave activity, discussing how it might be used to better understand mental states and enhance direct contact between the human mind and technology.
What is EEG ?
Electroencephalography detects electrical brain activity using electrodes put on the scalp. EEG gives crucial insights into brain function by collecting diverse brainwave patterns associated with different mental states, such as severe sleep and conscious thought. This non-invasive approach has applications in many sectors, including neurology, where it can provide paralyzed persons with transforming skills to direct on-screen activities only via the strength of the mind. Such an invention also stepped forward to capitalize on a new development in the field of artificial intelligence.
Brain Waves
Brainwaves are electrical signals that indicate brain activity. These electrical impulses have various rates and are measured in cycles per second, or Hz. While observing a person’s brainwave activity, you may determine their mental state and measure the electrical activity in specific brain locations associated with a certain brain function.
What are the most commonly measured brainwaves?
- Delta Brainwaves (0.1–4 Hz) — Deep Sleep:
Delta waves are the slowest type with the highest amplitude (wavelength). These brainwaves typically appear for people during deep sleep when they are not dreaming. - Theta Brainwaves (4–7 Hz) — Deep Meditation and First Stages of Sleep:
These waves are related to subconscious activity. These types of brainwaves appear in deep relaxation and meditation. They are likely to arise while drifting off to sleep or in a light sleep phase before waking up. - Alpha Brainwaves (7–12 Hz) — Relaxation:
These Alpha waves do not appear when we are asleep. They are usually found in the brain’s occipital lobe (backside of the brain) when patients are awake with their eyes closed. These alpha brainwaves would be less intense if our eyes were opened. - Beta Brainwaves (12–40 Hz) Conscious Reasoning:
These brainwaves are the second-fastest form of brain frequency and are mostly linked with the active brain.
You will likely exhibit beta brainwaves when attempting to solve complex math problems or a puzzle. Logical thinkers tend to display a higher level of beta-brainwave activity, depending on their cognitive abilities. Interestingly, beta brainwaves show an increase as we grow older. - Gamma Waves (40–70 Hz):
Measuring these waves is challenging with current EEG technology. The fastest waves, Gamma, are associated with high-level cognitive activities like perception, problem-solving, and memory recall.
Understanding Human Behavior via Neural Connections
The brain can be described as an architecture of interconnected neurons that determines human behavior. Electroencephalography is a technique that reads electrical potential from the brain and measures it using a special device called an electroencephalogram (EEG). EEG signals are classified based on signal frequencies for different states or stimuli, such as eye ball movement, eye opening, eye closing, finger clenching, etc. These signals are associated with specific frequency ranges from 0 Hz to 100 Hz.
Some signals have more than 100 Hz in frequency. This signal-based analysis with respect to different states helps medical researchers better understand the functional and behavioral characteristics of complex brain structures.
From Brain Waves to Readable Data
A technician attaches small metal discs known as electrodes to the scalp to cover all parts of the brain, acting as receivers and picking up the electrical currents the neurons produce. The electrical signals picked up by the electrodes are fragile. So, they are amplified to a level that we can measure and analyze. The heightened signals are then recorded over a period, providing a visual depiction of the brain’s electrical activity. This graphical representation is the EEG, a snapshot of the brain’s electrical symphony.
Placement of electrodes on the scalp:
Presentation of thoughts and acts into readable brain waves from electrodes:
Questing through gaming using thought alone
EEG has revolutionized healthcare, it has found its way into everyday mobility solutions through brainwave commands. Not only has it significantly improved the quality of life for individuals living with paralysis or locked-in syndrome, but it has also stepped foot into the world of gaming.
The video game and variety streaming video broadcaster Perri Karyal has developed a method for using her brain waves to play games. Karyal, who hosts a regular show on twitch.tv, has been using a custom controller that reads EEG signals to play the popular video game “Elden Ring.”
- Data Collection:
Gathering EEG data from the user: While EEG signals are highly variable, common patterns within them can be recognized and decoded from repeated mental actions. She designed the system to recognize repeatable patterns in EEG measurements (electrical oscillations) in order to simulate the act of pressing a button on a game pad or keyboard. - Data Labeling:
Label the preprocessed EEG data with the associated gaming tasks, producing a labeled dataset for supervised learning. This allows the manipulation of the Elden Ring character’s actions, such as swinging weapons, casting spells, and avoiding competitor attacks, by inducing the same brain activity patterns. Karyal taught the program to identify brain-wave patterns she made while envisioning different physical moves in order to translate EEG signals into inputs that the game could recognize. This method is known as motor imagery, and it collects average patterns of brain waves from a person’s brain as they imagine themselves moving their body in a certain repetitive pattern. Karyal said, “I imagined pushing something forward in my thoughts. The program was obtained to detect the pattern of activity that my brain occurred to routinely create while performing that task.” - Model Training:
Train the selected machine learning model on the labeled dataset to learn patterns associated with different gaming actions:
“I have spent more hours training the EEG than I have in the game, and I have over 250 hours in the game.” — Perri Karyal, Twitch gaming streamer
Conclusion
One of the most significant advances in computing is the possibility of direct contact between the human brain and artificial intelligence based only on the electrical impulses that generate our ideas.
Consider a world in which the distinction between human minds and machines is blurred. A world in which two people make eye contact across a room and communicate virtually mentally.
But the issue remains: What deviations exist between our apparently comparable concepts and the electrical activity in our unique brains? Is your “hello” the same as mine, and how does this relate to our computing objectives?
References
- Clarkebioscience.com. (n.d.). Brain waves explained. Retrieved from https://clarkebioscience.com/brainwaves-explained-alpha-beta-delta-theta-what-these-brainwaves-mean-for-your-brain-health/
- IEEE Spectrum. (n.d.). This gamer turned EEG tech into a game controller. Retrieved from https://medium.com/r?url=https%3A%2F%2Fspectrum.ieee.org%2Felden-ring-hands-free-controller
- ScienceDirect. (2012). Analysis of electroencephalography (EEG) signals and its categorization–a study. Retrieved from https://www.sciencedirect.com/science/article/pii/S1877705812022114
- Tshibangu, A. (2023, June 19). Navigating the brain’s electrical landscape: An introduction to electroencephalography. Retrieved from https://medium.com/@alphatshibangu/navigating-the-brains-electrical-landscape-an-introduction-to-electroencephalography-3f61192ab632
