BCI: Brain Computer Interfaces

Sometimes, the best ideas for a blog come from the things you’re currently working on.

This week has been quite long and exciting for me because the flagship event of IEEE, NETSIP 2026, is being hosted at NFSU. Due to heavy rainfall, the event has been rescheduled to 8th and 9th August. As the IEEE Student Branch Chair and an IEEE Signal Processing Society (SPS) member, I have been involved in organizing different aspects of the event and will also be hosting it. Between planning sessions, coordinating with the team, and managing multiple responsibilities, one topic has been at the center of it all: Brain-Computer Interfaces (BCIs).

The curiosity to know what BCI is, led me to write this blog.

Since I am writing this in between the event preparation and it’s new for me too, I will keep it simple and focus on the fundamentals so that anyone, with any background, can understand what a Brain-Computer Interface is and why people are so excited about it.

A man named Noland Arbaugh sat in front of a laptop and played online chess, without touching his keyboard, his mouse, or anything at all. Arbaugh had been paralyzed below the shoulders after a diving accident years earlier and had received a brain-chip implant from Neuralink, Elon Musk’s brain-computer interface company, that January. Neuralink showed a livestream of him moving a cursor and playing chess online using only the implant. He later said the device had also let him play Civilization VI for eight hours straight, purely by thinking about it, without touching the game’s controls. (Link)

https://youtu.be/k0I9Z-ARbjo?si=uonopZzIdUhJIEEp

That’s a Brain-Computer Interface. And once you see it work in real life like this, the sci-fi feeling wears off fast.

So, what is a BCI, exactly?

Brain-Computer Interface (BCI) is exactly what its name suggests, a communication bridge between the human brain and an external device.

Brain-Computer Interface is a system that reads the electrical signals your brain produces and translates them into commands a device can act on. Your brain is already sending signals constantly, every time you think about moving your hand, your motor cortex fires off electrical activity, whether or not your hand actually moves. A BCI listens in on that activity and turns it into an instruction: move a cursor, select a letter, control a wheelchair.

Normally, you interact with a computer through a middleman, your fingers on a keyboard, your hand on a mouse, your voice into a mic. A BCI removes the middleman. The signal goes straight from brain to machine.

https://youtu.be/bwriLGRuDZI?si=oy7_jTpVqybjO30m

Now, before you imagine a machine reading every thought in your mind, that’s not how current BCIs work. They don’t understand your memories, emotions, or private thoughts. Instead, they detect specific patterns of brain activity associated with particular tasks or intentions.

Why do we need Brain-Computer Interfaces?

For millions of people living with conditions such as spinal cord injuries, paralysis, stroke, amyotrophic lateral sclerosis (ALS), or other neurological disorders, the brain may still be able to generate movement intentions even when the body cannot carry them out. In these situations, the communication pathway between the brain and the muscles is damaged, but the brain itself continues to function.

A Brain-Computer Interface creates an alternative pathway. Instead of sending commands to the muscles, it allows those intentions to be interpreted by a computer and translated into actions such as moving a cursor, selecting words on a virtual keyboard, controlling a robotic arm, or operating a wheelchair. BCIs are not about replacing human abilities, they are about restoring them.

Beginning of BCIs

Although Brain-Computer Interfaces have become widely known because of companies like Neuralink, the idea has been around for much longer.

Over the following decades, advances in neuroscience, biomedical engineering, signal processing, artificial intelligence, and machine learning gradually transformed BCIs from laboratory experiments into real-world systems.

Today, researchers and companies around the world, including Neuralink, Synchron, Blackrock Neurotech, OpenBCI, and Emotiv are working on technologies that aim to improve communication, mobility, and quality of life for people with neurological conditions.

How does the brain even “talk” in the first place?

Your brain runs on electricity. Every thought, every intended movement, every sensation involves neurons firing tiny electrical signals to communicate with each other. When Arbaugh thought about moving a cursor left, the neurons in his motor cortex, the part of the brain responsible for movement, fired in a specific pattern, even though the message could no longer reach his hand. A BCI picks up that pattern before it hits a dead end, and hands it off to a computer instead.

Three basic types of BCIs

Not all BCIs work the same way, and the difference mostly comes down to how close the sensor gets to your brain.

• Non-invasive: Nothing gets implanted. You wear something outside your skull, usually an EEG (electroencephalogram) headset with electrodes on the scalp, picking up brain signals through the skin and bone. Easiest to use, cheapest, but the signal is a bit noisier since it’s traveling through your skull first.
  

• Invasive: Electrodes are surgically implanted directly into brain tissue, right where the signals are cleanest and strongest. Neuralink’s implant is the most talked-about example of this today. More accurate, but it needs surgery and comes with real medical risk.
  

• Partially invasive: A middle ground. Electrodes sit inside the skull but on the surface of the brain, not buried in the tissue itself. Better signal than a headset, less risky than a full implant.
  

  

How does a BCI work?

Although the technology behind BCIs is quite advanced, the overall process can be understood in four simple steps.

1. Your brain generates signals: Every time you think, move, see, hear, or even imagine an action, billions of neurons in your brain communicate using tiny electrical signals. These signals carry information about what your brain is doing.
   

2. The signals are captured. The next step is collecting those signals. This is usually done using sensors called electrodes. Depending on the type of BCI, these electrodes may be placed on the scalp using an EEG cap (non-invasive) or, in some cases, surgically implanted inside the brain (invasive) to capture more detailed signals.
   

3. The computer processes the signals. Raw brain signals contain a lot of background noise, making them difficult to interpret directly. Using signal processing and machine learning algorithms, the computer filters unwanted noise, identifies meaningful patterns, and predicts what the user is trying to do. For example, if the system has learned that a particular brain signal corresponds to moving a cursor to the left, it can recognize that intention when the pattern appears again.
   

4. Finally, the interpreted command is sent to an external device. Depending on the application, this could mean moving a computer cursor, selecting letters on a virtual keyboard, controlling a robotic arm, operating a wheelchair, or even communicating with a smart home device, all without physically touching them.
   

   

Where are BCIs used?

Although BCIs are still an active area of research, they are already making a difference in several fields.

• Healthcare: One of the most impactful uses of BCIs is helping people with paralysis, ALS, spinal cord injuries, or other neurological conditions communicate and interact with the world.
  

• Prosthetics: Researchers are developing robotic arms and prosthetic limbs that respond to signals generated by the user’s brain. Instead of relying on conventional controls, the prosthetic can perform actions based on the person’s intended movement, making it feel more natural to use.
  

• Rehabilitation: Assisting stroke patients during recovery by encouraging brain-controlled movement exercises.
  

• Gaming and Virtual Reality: Exploring hands-free ways to interact with games or virtual worlds using certain brain signals, creating a more immersive experience.
  

• Scientific Research: Brain-Computer Interfaces are valuable tools for neuroscientists studying how different regions of the brain function. They also support research into neurological disorders, cognitive processes, and the development of future assistive technologies.
  

Current Challenges

Despite the remarkable progress made in recent years, Brain-Computer Interfaces are still an evolving technology.

• One of the biggest challenges is the quality of brain signals. Non-invasive methods such as EEG record extremely weak electrical activity, making them susceptible to noise and interference. Even simple actions like blinking, moving facial muscles, or changing head position can affect the recorded signals.
  

• Another challenge is that every person’s brain is unique. A system trained for one individual cannot always be used effectively by another, which means many BCIs require calibration and user-specific training before they can perform reliably.
  

• Another challenge is speed. While humans can move their hands almost instantly, decoding brain activity accurately still takes time, making BCIs slower than natural movement for many tasks.
  

• Invasive BCIs offer higher accuracy but introduce challenges related to surgery, long-term safety, device durability, and cost.

These challenges are active areas of research and overcoming them will play a major role in making BCIs practical for everyday use. AI, robotics, biomedical engineering, computer science, cyber security etc. are future intersections of this topic. 

This blog was meant to introduce the fundamentals without going too deep into the technical details. I will write another blog once I explore more on this. After all, once a device can understand signals from our brain, the next question isn’t just “What things it can do?”, it’s also “How do we make sure it’s secure?”.