Decoding the Brain: A Look into BCIs and Their Medical Applications
- Amogh Acharya
- Jul 7, 2025
- 2 min read
We are now living in a world where mind control is possible. This once science fiction concept is now becoming reality through the development of Brain-Computer Interfaces (BCIs). BCIs allow direct communication between the brain and external devices without the use of muscles or peripheral nerves. While the application of this emerging technology spans gaming, military, and party tricks, the one I find most impactful is in the field medicine.
The functions BCIs go through detecting and translating brain signals into commands that devices can pick up involve 3 key steps:
First, electrical activity must be captured from the brain. There are 3 ways this can be done. Non-invasive signal acquisition is when brain activity is recorded from outside the skull. The most common form of this is electroencephalography (EEG) where electrodes are placed on the scalp using patches. These electrodes detect voltage fluctuations in the brain's cortex. EEG typically measures alpha, beta, theta, and delta waves in the brain within the frequency of 0.1 to 100 Hz. Filters are used to remove low frequency drift and high frequency noise like muscle activity. Some drawbacks to EEG include low spatial resolution and possible disruptions from other artifacts such as blinking or clenching.
Partially invasive signal acquisition involves placing electrodes directly on the surface of the brain under the skull most commonly done through electrocorticography (ECoG). These electrodes measure local field potentials created by neural activity. ECoG captures signals with much higher resolution than EEG. This means that ECoG can be used for more precise motor movements making it a better option for prosthetics.
Invasive signal acquisition acheives the highest quality signal possible directly from neurons inside the brain. Most commonly implanted is the Utah Array, a tiny grid made up of conductive needles. The electrodes penetrate the cortex around 1-1.5mm deep. A process called spike sorting is used to isolate spikes from specific neurons through advanced algorithms. With the ability to pick up signals so precisely, invasive signal acquisition use cases can even include imagined speech decoding.
Next, once brain signals are collected, they are processed. This includes removing noise and isolating necessary signals or patterns such as spikes from neurons from the motor cortex. Advanced filtering and use of machine learning algorithms are used to identify and classify brain signals in real time.
Lastly, the processed data is translated into commands that control external devices. Command outputs can be connected to computers and robotic devices which could mean moving a cursor along a screen, operating a prosthetic, or mentally typing out letters of the alphabet.
Real World Medical Applications of BCI:
Restoring Movement in Paralysis- use of robotic arms and in patients with paralyzed or missing limbs.
Communication for Patients with Amyotrophic Lateral Sclerosis- allows patients unable to speak due to loss of voluntary muscle control to use brain activity to communicate by forming sentences through imagined speech.
Neurorehabilitation After Stroke- can help stroke survivors regain motor function by reinforcing brain motor signals through activating the corresponding muscles with robotic aid.
Restoring Sensory Input- visual cortex implants that have allowed patients to perceive light patterns called phosphenes and navigate basic environments.
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