Charles Babbage, considered as the “father of the computer”, was an English mechanical engineer and polymath. He originated the concept of a digital programmable computer. Computers follow generalized sets of operations, called programs. Technological advancements over time ensured that the computing power of the computer also grows. According to an article in Forbes, The Rise In Computing Power: Why Ubiquitous Artificial Intelligence Is Now A Reality clearly explains how computing power and technology have changed over a duration of time. Along with the advancement in technology, our understanding of the human brain also reached new heights.
Have you ever imagined a world where we can make the computer to do work just by our thoughts? Today our technological advancements have made us reach a stage where we can make it a reality. A brain-computer interface is a collaboration between our brain and the computer, where we can make the computer to work with the help of signals from our brain. Such technological advancements can be of great use to our society. Several people in this world are suffering from difficulties such as paralysis. Such Medical conditions can break the communication between the brain and muscles. Even if that’s the case, the brain still generates signals for the intended activity. BCI can be of great benefits to those kinds of people. In short, our mind can be used to control robots and other technologies to overcome human limitations.
How does a BCI(Brain-computer interface) work?
BCI records and interprets brain signals. The human brain is made of approximately 100 billion nerve cells, called neurons [source: howstuffworks]. Each neuron is linked to others by way of connectors called axons and dendrites. For each action we do, our neurons are made to work. These neurons communicate with each other through minimal electrical signals. These electrochemical signals are generated by differences in electric potential carried by ions on the membrane of each neuron and can travel over long distances within the body[source: howstuffworks]. People can walk or run because the brain sends signals via the central nervous system to the muscles of the body. We can record and interpret these electrochemical signals by making use of some advanced sensors. BCI can be of 2 types based on the ways by which we can detect these signals.
- Non-Invasive Brain-Computer Interface
Works on the principle of electroencephalography(EEG), MEG (magnetoencephalography), or MRT (magnetic resonance tomography). EEG based brain-computer interface is the most preferred type of BCI. Signals from the brain are captured via electrodes placed on the scalp surface. Electroencephalographic (EEG) activity from the brain will be picked up by electrodes, and the information can be used to do the necessary. These electrodes measure differences in the voltage between neurons. NeuroSky is a manufacturer of brain-computer interface technologies for product applications. They make use of the concept of EEG since its Cheaper to work. The massive research focus is always given to non-invasive BCI due to this underlying reason. Multiple people from diverse backgrounds can work on non-invasive BCI. Signal quality is comparatively less fot non-invasive BCI when compared with the invasive BCI.
- Invasive Brain-Computer Interface
Electrodes are placed under the scalp directly on or in the brain tissue. Requires surgical method to place the implant into the skull of the person. Such implants won’t cause any damage to the brain, and the signal quality is comparatively better than the one captured from the scalp. Invasive BCI requires a medical practitioner to work on and is more costly than non-invasive BCI. Invasive BCI can be helpful especially for blind people. When a healthy person sees some colours, the optic nerve will send some signal to the brain. For a blind person, they can make use of a camera that will send the signal to the implant precisely similar to the signal optic nerve will make if a healthy person sees the same thing, thus allowing a blind person to have a visual experience[source: howstuffworks].
Once the signals for an action is obtained, it can be converted to a command to operate a device or software. A processor or a computer can be further programmed to perform tasks based on the command. This type of technology is already used by people who have paralysis or other difficulties.
Convolutional Neural Network(CNN) is a machine learning technique modelled after the brain structure. CNN is a type of AI neural network based on the visual cortex [source: Towards Data Science]. The visual cortex is part of the cerebral cortex that receives and processes sensory nerve impulses from the eye. CNN has four key layers and they are Convolution, Subsampling, Activation and Fully Connected.
[Image courtesy: http://www.ais.uni-bonn.de/deep_learning/ ]
Convolutional Neural Net is a deep learning technique for visual recognition tasks and with a set of a prepared dataset, CNN can outsmart humans in visual recognition tasks. CNN has the capacity to learn the appropriate features from the input data automatically by optimizing the weight parameters of each filter through the forward and backward propagation in order to minimize the classification mistake [source: howstuffworks].
Future Scope of BCI
So far, BCI has been mainly used in the field of medicine. BCI is a good option that can be used for human-machine collaboration. Suppose you have the ability to type the keyboard just by thinking about the words. Imagine how good it is if your brain is connected to the internet 24/7. BCI can find it’s application in information, entertainment, healthcare, the realization of individual cognitive and artistic potential, and so on. At present, there are lots of limitations that prevent us from using BCI on a large scale. With Continuous research and studies going on all over the world, we can expect a smart world where we all will be connected through our brains.
To know more about the future scope of BCI, refer The Future of Brain-Computer Interfaces: Blockchaining Your Way into a Cloudmind.
Sandra Moraes is the Content Management Specialist at Datahut. Professionally she is a Data Scientist and researched Data Analytics. She authored on Data Science and Customer relationship.
LinkedIn: Sandra Moraes