Brain-computer interface is popularly known as BCI. These computer-based interfaces acquire brain signals and analyze them. It translates the signals into commands and sends them to the relevant output devices for further action. They do not use the normal pathway of neuromuscular output pathways. Its main objective is to support and help disabled persons with neuromuscular disorders.
It helps them by demonstrating electroencephalography-based spelling and neuron-based device control. Now a day, scholars use electroencephalographic, intracortical, electrocorticographic, and other brain signals to create complex controls. BCIs are very helpful in rehabilitating patients after strokes and other disorders. This novel Brain-Computer Interface technology is the prime focus of the research and development industry.
Brain–computer interface (BCI) is otherwise called a brain-machine interface (BMI), termed a SmartBrain. It is a direct communication pathway between neural electrical activity and external devices.
The Brain-Computer Interface focuses on three vital areas, namely:
First, it needs signal acquisition hardware that is easy to handle, portable, safe and convenient, and functions in all critical environments.
BCIs need to be validated for human use by people with more disabilities with clinical trials and tests. And the effective viable models should be implemented, distributed, and used.
Further, it should be enhanced to employ moment-to-moment performance reliability as natural muscle-based functions.
What is a Brain-Computer Interface?
The brain-computer interface is a computer-based system that acquires brain signals. It analyzes them. Further, it translates the signals into commands and relays the commands to the output device connected to carry out the instructions in the command. The BCI does not use the peripheral nerves and muscles. Therefore, the BCI is not a mind-reading device. Instead, it enables users to act using brain signals than the muscles. Therefore the BCI and the user need to coordinate and work together for desired results. Consequently, proper training is required for the user to generate brain signals that encode intention. And the BCI needs to align to decode the signals as commands and relay them to the output devices to obey the user’s command.
Origin and development of Brain-Computer Interface:
Most of the early BCI research used scalp-recorded EEG signals, which have the advantages of being easy, safe, and inexpensive to acquire.
The brain-computer interfaces project was an early attempt to evaluate the feasibility of using neuronal singles into a person-to-computer dialogue system that enabled computers to be a prosthetic extension of the brain. For example, a study starting with monkeys shows that signals from single cortical neurons can control the movement of a meter needle.
The electrical brain signals can be put to work as a carrier of information and feed to the computer systems to control the prostheses devices. That was the concept of the early state of research in 1973.
Though, in principle, any type of brain signal could be used to control a BCI system, the most common brain signal stated are the electrical signals produced by the neuronal postsynaptic membranes.
Neuroprosthetics versus Brain-Computer Interface:
Neural prosthetics is related to neuroscience, with biomedical engineering concerned with developing prostheses or prosthetic implant (prostheses is an artificial device that replaces a missing body part, which may be lost through trauma or disease). Therefore prostheses are combinations of devices that can substitute a motor sensory or cognitive modality that has been damaged. It uses artificial devices to replace the function of the impaired nervous system and brain-related problems. But sometimes, both terms are interchangeable. Further, use similar experimental procedures and surgical techniques.
Human Brain–Computer Interface Research:
Invasive Brain–Computer Interface Research:
IN BCI research, the non-invasive EEG-based research approach is widely used to minimize the risk involved. Sensorimotor rhythms are used to control the devices such as robotic and prosthetic devices, wheelchairs, etc.
Invasive Brain–Computer Interface Research requires surgery to implant electrodes under the scalp for communicating brain signals. It includes side effects from surgery, and sometimes the body resists the implanted electrodes, leading to medical complications. The invasive research targets repairing damaged sight and providing functionality to people with paralysis. They implant it directly into the grey matter or the central nervous system by doing neurosurgery. The purpose of planting them in grey matter is to get the highest quality signals from the implanted BCI devices. But the scar tissue build-up can cause the signal to become weaker over a period of time.
Vision scientists do direct brain implants to treat non-congenital blindness. For example, Dr. William Dobelle is a biomedical researcher who treated blind patients and restored limited sight to them. His first prototype, a single-array BCI containing 68 electrodes, was implanted into a visual cortex and produced a sensation of seeing the light (poshenes). The system of devices includes a camera mounted on spectacles to send signals to the implant. After his attempt in 2002, Dobell employed his second-generation implant commercially. It enabled better mapping of phosphenes into a coherent vision.
BCI helps to restore movement in paralyzed patients to assist them with robot arms focusing on motor neuro-prosthetics.
There are a number of challenges to recording brain activity with invasive BCIs. The advanced CMOS technology enables integrated invasive designs of BCI with smaller sizes, minimum power requirements with higher signal acquisition capability. The challenges of electronic limitations of BCIs are the potential voltage level in intercellular recordings.
Partially Invasive BCI Devices:
The partially invasive device is implanted inside the skull but rests outside the brain. They can produce better resolution signals than non-invasive BCI. In fully invasive BCIs, the formation of scar tissue around the device can affect the quality of the signal, and in non-invasive BCI, the bone tissue of the skull can deflect and deforms the signals considerably.
In recent years the partially invasive BCI entered into the area of interventional neurology. An Australian neurologist Thomas Oxley conceived the idea of Stentrode, a new BCI. Stentrode is a monolithic stent electrode array. It is designed to deliver via intravenous catheter under image guidance to Superior Sagittal Sinus, which lies adjacent to the motor cortex. The Stentrode communicates the neural activity to a battery-less telemetry unit implanted in the chest.
The implanted unit in the chest communicates wirelessly to an external telemetry unit capable of power and data transfer. This type of insertion eliminates the risk of clotting and venous thrombosis. And the human trials are underway. In 2020 two participants with amyotrophic lateral sclerosis could control operating systems. With the Stentrode brain-computer interface, they were able to text, email, and utilize banking services. This is the first BCI implanted through blood vessels, eliminating the need for open skull surgery.
Electrocorticography (ECoG)
ECoG measures the brain’s electrical activity from beneath the skull, similar to non-invasive electroencephalography. In ECOG, the electrodes are packed, embedded in a thin plastic pad, and placed above the cortex and under the dura mater. It was clinically tested on humans in 2004. The subsequent research indicates that control is rapid with minimum training. The signals are not taken from the parenchyma, but it is either subdural or epidural.
The ECoG is a very promising intermediate BCI modality because it has higher spatial resolution with a good signal-to-noise ratio. In addition, it requires minimum or less training than the scalp-recorded EEG, with lesser clinical risk and difficulty, and has long-term stability. But the light reactive imaging BCI devices are still in the realm of hypothesis.
Non-Invasive BCI:
The EEG-based interfaces are easy to wear, and they do not require surgery; therefore, non-invasive EEG-based interfaces are used for much broader applications. However, the negative side is they have inferior spatial resolution and cannot use higher-frequency signals. In addition, since the skull dampens signals and disperses and blurs the electromagnetic waves created by neurons, they have poor resolution.
EOG (ElectroOculography):
By 1989 the researchers found a robot could be controlled by eye movement using EOG signals. The mobile robot was driven from start to end point with five EOG commands, forward move, backward move, stop, left, and right. And it was successful.
In 2016, a paper was published about a new communication device and non-EEG-based human-computer interface requiring non-visual fixation. The interface is based on covert interest. The user-chosen letter is identified without using eye movement; instead, they are identified with the help of unintentional pupil size oscillations and background circle brightness oscillation patterns. Accuracy is further improved by the brightness transition of the letter’s circle.
Electroencephalography (EEG) Based Brain-Computer Interfaces:
In the early days, the extensive training required was the important hurdle in implementing an Electroencephalography (EEG) Based Brain-Computer Interface. However, a Neuroimaging approach for training protocol refined the recent advancement in EEG-based brain-computer interface.
Limitations and Issues with Brain-Computer Interface:
User-Centric, Legal, and Social Issues:
- The Long term effects on the user remain unknown.
- Getting consent from people who have communication difficulties is tough.
- The consequences of BCI technology on the quality of life of the patient and their family are unknown.
- Health-related side effects such as sleep pattern
- Therapeutic application and chances of their misuse
- Patient safety at risk
- Non convertibility of some of the changes made to the brain
- Issues related to accountability and responsibility (the influence of BCI overrides the free will and control of sensory-motor actions. Sometimes the cognitive intentions may wrongly translate due to the malfunction of BCI.
- Due to deep brain stimulation, personality changes may happen.
- Concerns over the state of “Cyborg.”
- It may further lead to the question of the personality of the human.
- Unable to distinguish between human and BCI-controlled actions
- Restrictions on Technology in advanced interrogation techniques by governments
- Social stratification and selective enhancement issues
- Research ethics and animal experimentation and application on human subjects
- Privacy and Mind Reading
- Mind control is possible.
- Movement control is possible.
- Emotion control is possible.
- A tracking and tagging system is possible.
Future of BCI:
12 European nation partners have designed a road map and funded the framework program named Horizon 2020.
Disorder of consciousness (DOC)
The disorders of consciousness are a medical condition that inhibits consciousness. In other words, it is a kind of disorder or absence of self-awareness and arousal. This state is defined to include persons in a coma. Some persons with DOC may, in fact, be able to process and make important life decisions. It has given them new prospects in life by allowing DOC patients to provide their views on their decision, such as whether to do therapy, where to reside and their views on end-of-life decisions.
Motor recovery:
Research in recent years has highly demonstrated the utility of EEG-based brain-machine interface systems in aiding motor recovery and neurorehabilitation in persons who have had a stroke. So far, BCIs for motor recovery have relied on the EEG to measure the person’s motor imagery. However, researchers have also used fMRI to learn different brain changes when people undergo BCI-based stroke rehabilitation training.
Functional Brain Mapping:
People undergo brain mapping during neurosurgery. Brain mapping is often required for people with tumors or epilepsy who do not respond to medication. In this procedure, electrodes are placed on the brain to identify the structure’s location and functional areas precisely. Patients may be awake during the neurosurgery procedures. And they are asked to perform specific tasks. It is crucial that the surgeons remove the desired tissue while sparing other critical movement or language regions. Removing additional brain tissue can cause permanent damage. While removing only a little tissue can leave the underlying condition untreated and further require additional neurosurgery. Researchers are exploring new ways to use BCI technology to improve neurosurgical mapping.
Flexible Devices:
Flexible neural interface devices have been extensively tested in recent years to minimize brain tissue trauma related to the mechanical mismatch between tissue and electrode.
Neural Dust:
It is a term used to refer to a tiny-sized device operated by wirelessly powered nerve sensors.
Components of BCI:
The Brain-Computer Interface detects and quantifies the features of brain signals that show the user intention and translates these features in real-time into device commands. The BCI system consists of the following four sequential components:
Signal Acquisition:
Signal acquisition is measuring brain signals using sensor modality. The signals are amplified to a level suitable for electronic processing, and then the signals are digitized and transmitted to the computer system.
Feature Extraction:
It is the process of analyzing digital signals to distinguish the signal characteristics from extraneous content to translate into output commands.
Feature Translation:
The resulting signal is sent to the translation algorithm, which converts the signals into appropriate commands for the output device. The translation algorithm is dynamic to adapt spontaneous changes in the signal features into a possible range of feature values to cover the full range of device control.
Output Device:
The final commands from the translation algorithm operate the external device. The executed device operation provides feedback to the user and thus closes the control loop.
All the above four components are controlled by an operating protocol that defines the onset and timing of operation. The operating protocol allows the BCI system is flexible to serve the specific need of the user.
Conclusion:
Various groundbreaking advances in neuro-sensors and computational tools offer great promise for more sophisticated, user-friendly BCI systems with nil maintenance.
Researchers throughout the world develop various kinds of BCI systems that are in the realm of science fiction. Only the Time-variant psycho-neurophysiological fluctuations impact on brain signals impose another challenge for BCI researchers to transform the Technology from laboratory experiments.
Those systems use different brain signals, different recording methods, and signal processing algorithms. As a result, they can operate different devices. Unfortunately, few people with severe disabilities already use BCI for essential communication and control in their daily lives.
BCI is a major communication and control technology for disabled people. Brain-computer interfaces present direct communication between the brain, the computer system, and the external device. As a result, they provide an extended degree of freedom in rehabilitation.
