Using Brain-Computer Interfaces to detect emotions

em·pa·thy — noun

the ability to understand and share the feelings of another.

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Humans are built for communication. And much of the way that we communicate isn’t verbal. In fact, 55% of it is body language, 38% of it is how we say it (pitch, pace, volume), and only 7% is what we say.

So then, to understand how someone feels and avoid miscommunication, it’s obvious that we need to pay attention to more than just their words.

And how can we do that? With brain-computer interfaces (BCI’s), of course.

Wait… but first, what are BCI’s?

If we break down the name, brain-computer interfaces are basically in there. The goal is to connect the brain signals to a computer in order to complete some sort of operation.

While they are described as “mind-reading” machines, they can’t exactly “read your thoughts”. The brain doesn’t send messages through words, but rather through electric signals. It’s similar to the idea of code. Code communicates with a computer, and electric signals are used to communicate in your brain.

The electric signals can be measured by using an electroencephalogram (EEG) and can then be converted to data.

The EEG’s take input from your brain waves, which are patterns based on the billions of signals that your brain nerve cells send out. During this process, small electrodes and wires are attached to your head, during which the electrode picks up your brain waves and amplifies them, recording them in a graph-like manner.

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This is a sample graph recording a focal spike of a seizure

5 different types of brainwaves that are measured in hertz. These are Gamma, Beta, Alpha, Theta, and Delta.

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Detecting emotions

It’s so important to increase the ability of humans to communicate. By using BCI’s to track and record emotional responses, many fields could be revolutionized, and it would make the lives of government workers, such as policemen and doctors much easier.

It could also be used to diagnose (and treat) those with mood disorders by tracking their progress and becoming adaptive. Meaning that a headset could pick up what makes a person feel better when they are sad, and they would be encouraged to repeat that activity next time they are sad.

In a study from 2016, subjects were asked to arrive with their hair washed, but without any added substances (ex. gel). The electrodes were placed in the 10/20 formation, meaning that the distance between one electrode to another is 10%-20% all around the head.

The electrodes were secured using EEG gel, and was placed on the subjects’ heads using an EEG cap.

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This is a view of potential electrode placement looking down at the top of the head.

In this study, the electrodes FP1, FP2, F3, F4, C3, C4-A2, P3, P4, O1, O2, F7, F8, T7, T8, P7, P8, Fz-AV, Pz-AV, and Cz-AV were used.

According to the study, it was found that:

  • Anger was linked to theta waves
  • Sadness was linked to both delta and theta waves
  • Thrilled was linked to alpha waves
  • Shock was linked to every wave, but most noticeably theta and delta waves

While we’re getting closer to tracking and understanding emotions, there’s still quite a bit fo research to get done. The benefits of which, however, are undeniable.

Key takeaways:

  • Understanding emotion is extremely important and is a big factor in our communication
  • Brain-computer interfaces use your brain signals to communicate with computers
  • Electroencephalogram (EEG) can record the data from your brain waves on graphs
  • There are 5 types of brain waves, Alpha, Beta, Delta, Gamma, and Theta, and they each correspond to a level of alertness
  • A study was done in 2016 on detecting emotions and used an EEG cap. The results were such that anger, sadness, thrilled, and shocked were linked to theta, delta and theta, alpha, and every wave (respectively)
  • The implications and possibilities of a better understanding of emotions are endless and can include diagnosing and treating mental health disorders.

This is just the first step of diving into a world that may not be noticeable by our eyes but can be from the eyes of an EEG.

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Written by

I’m 16 year old high school student who’s learning more and more about emerging technology. I write about tech, philosophy, social sciences and personal growth.

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