How Paralyzed Patients Could Communicate (to a limited degree)

I recently read a paper, Brain–Computer Interface–Based Communication in the Completely Locked-In State, about how people who are unable to move any muscles (including their mouths) could potentially communicate using “Yes” or “No” via a Brain-Computer Interface or BCI.

Though this seems underwhelming, it’s a huge leap towards understanding how thinking works. There are already devices that can process thoughts, using deliberate (on purpose) actions. An example of this is Stephen Hawking’s computer, which uses his cheek as a control device. He even writes long lectures with it.

Our problem, is that a person can lose all motor control (control of movement) and is completely unable to do meaningful actions. This is called a CLIS – Completely Locked-In State.

In the past, people have tried looking at electrical signals in the brain to determine a “Yes” or “No” (because your brain runs off electrical signals, kind of like a computer), but with little success. This is called the electroencephalogram (EEG) method. An EEG consists of putting a bunch of electrodes on your head to analyse how brain signals are behaving. It can measure brain activity, which is useful for finding out how much certain tasks can make the brain work. This, however, is not that useful for determining a specific yes or no response.

A typical EEG setup.

There are lots of ways that we use to look into the brain. One such method that you may have heard about is MRI – Magnetic Resonance Imaging. This uses a magnet to take snapshots of the brain and captures a slice of its structure. If you want more on brain imaging, let me know. MRIs are unsuitable for BCIs since they require a giant magnet to be carried around whenever the patient needs to interact with the world.

The study in the paper uses a different method to measure brain activity and get computer interaction- fNIRS – or Functional Near-Infrared Spectroscopy. This may sound complicated, but it’s not that hard to understand.

Essentially, you take a camera that captures light that’s almost infrared. (Light exists in a bunch of frequencies, just like how a radio receives a bunch of frequencies; fNIRS is like a camera that captures near-infrared instead of visible light – kind of like your radio listening to 102.5 FM and your friend’s radio listening to 87.4 FM.)

Human skin is almost transparent at the NIR frequency, so it’s kind of like looking through a window into the brain. Blood absorbs this light (not transparent), so it lets people closely see what is happening with blood flow inside the brain.

Using this, researchers were able to discover that the CLIS patients were giving off different patterns for “yes” and “no”, with over a 70% correctness rate. This was measured using statements such as “Berlin is the capital of Germany”.  These statements were often paired with other questions like “Paris is the capital of Germany”, “Berlin is the capital of France”, and “Paris is the capital of France” in order to validate results.

When testing with an EEG-BCI, results were inconsistent during the 15 seconds in which the patients were answering and correct responses were rarer.

The procedure involved putting both EEG electrodes and fNIRS sensors on the patients at the same time to study the differences between methods.

Results using an fNIRS-BCI. Look  at the different patterns for “Yes” and “No”. They’re quite distinct (different from each other), and shows that fNIRS has promise.

There are also some limitations though. First, there isn’t a 100% accuracy, yet. Secondly, “Yes” and “No” can only be used to answer so many questions – open ended questions with speaking is still something to work towards.

In conclusion, I think that this study not only gives us a possible way for people to communicate in the future (ex. automated chefs knowing what you want to eat without you even needing to actively think about it), but also a deeper view into how we think. fNIRS BCIs have great potential for the future, and the technology is off to a great start.

Be sure to check out the paper if you want to do some in depth reading (also linked above).
Otherwise, thanks for reading!

Stay tuned and stay sciency,


P.S. Remember how I said last post that this would be about rocket engines? Well, I guess it isn’t now. This was kind of science news, so it’s different from my general science stuff. I’ll definitely do rocket engines sometime in the future.

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