Brain-Computer Interface and Rehabilitation

The cyborg or cyborg, which we are familiar with from science fiction movies, are beings with both organic and biomechatronic parts. It is a word derived from the abbreviation of the expression “cybernetic organism”. In the cyborg, it is possible to restore or increase the functions by integrating some technologically produced artificial components into the living thing. In this technology, there is a two-way interaction between the living (organic) part and the artificial part, while control orders are sent from the organic part, sensory feedback is provided about the work performed from the artificial part.

Although the concept of cyborg was defined in the 1960s, it can be said that it remained a dream for a long time. In recent years, examples have been seen in terms of both increasing the various skills of healthy people and restoring the functions lost due to various diseases with the use of high-tech devices. Intense efforts for paralyzed patients to regain their lost functions are bearing their first fruits. Brain control of robotic devices that compensate for lost arm or leg movement has become possible. In these applications, the brain-computer interface provides the communication of the brain with the machine.

What is a brain-computer interface?

A brain-computer interface (BCI) is defined as a communication system that does not rely on nerve fibers (peripheral nerves) or muscles, which are the normal output path for commands generated by the brain. With this definition, BCI is distinguished from other methods that increase the patient’s communication skills by using the mimic and eye muscles whose movements are preserved in some paralyzed patients. Although the first studies on brain-computer interfaces focused on the communication function, they are also used to improve movement, sense and other functions today. This technology has a strong potential in the field of physical therapy and rehabilitation in terms of developing assistive devices for motion and sensory perception and providing control of these devices by the patient.

How does the brain-computer interface work?

The main tasks that the brain-computer interface should do are to detect the signals generated in the brain, to process these signals with the help of a computer algorithm, and to perform the action that the person wants to do with a device called an effector tool. That is, recording, decoding the signals and converting them into commands, and performing the appropriate action with the effector device are the main steps. In addition, providing sensory feedback to the person about the movement of the effector device is a feature in most systems.

In which anatomical region is the brain-computer interface used?

Some areas of the central nervous system are more suitable for the use of BCI systems. The shell of the brain near the skull, called the cortex, is specialized for certain functions. For example, in the primary motor cortex in the cerebral cortex, the area that controls the hand is located. Located on the side of the head, this area is a relatively easy area for recording nerve cell signals. The cerebral cortex is the most preferred area for the use of BAA systems, since its functional organization does not vary much from person to person and is easily accessible. However, theoretically, BBA can be used in any part of the central nervous system.

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Recording the activity of nerve cells

All the senses we feel, thoughts and commands that carry out our actions are basically the electrical activity of nerve cells. If this electrical activity is resolved, it is assumed that one can know what one is thinking. The first step for the control of the brain activities of paralyzed patients and robotic devices or functional electrical stimulation is the perception of signals in the brain.

Techniques that record nerve cell signals are of two types, invasive and non-invasive. In non-invasive (non-invasive) techniques, the electrical activities of nerve cells are recorded by EEG recording over the skin or by indirect methods such as functional magnetic resonance imaging, magnetoencephalography, functional near-infrared spectroscopy. In invasive (interventional) techniques, recording electrodes can be placed under the skin, in the skull, between the meninges and even directly into the brain tissue. Invasive techniques carry risks associated with surgery, but allow much more specific recording. Traumatic brain injury and stroke EEG and near-infrared spectroscopy, which are non-invasive methods, are most frequently used in patients with

The resulting signals are converted into commands that enable movement.

Whether invasive or non-invasive methods are used, the obtained signals need to undergo amplification (amplification) and digitization processes. The distinctive features of the signals are decomposed with the help of an algorithm and converted into commands that control the effector device. While recordings obtained by non-invasive techniques such as EEG use the averaged electrical activity of a large population of nerve cells, invasive techniques can process the impulses of individual neurons or small groups of neurons. As the measurement becomes more precise, it is possible to distinguish between different commands generated in the brain and better control of the effector device by the person.

Neural signaling properties can be affected by physical stimuli, such as pain, or by conditions such as fatigue or anger. The algorithm should be able to distinguish the signal changes due to such reasons and analyze the action to be taken. Depending on the success of the person’s device control, the way the signals are processed may need to be adjusted. Although neural decoding algorithms are unique for each BAA, they must also have adaptability. It should be self-calibrating and can be used by different people. In BAA, while the algorithm adapts to the user, the user also adapts to the algorithm, so there is a mutual interaction. Controlling the device with the help of BAA involves a learning process.

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to do fine work

The number and quality of the different signals that can be obtained from the central nervous system determine the freedom of action of the effector device. While 2-4 channels may be sufficient to control a computer mouse or robotic arm, 22 channels are required to control the movement of all joints in the hand individually. Non-invasive methods such as EEG are good for checking systems with a limited number of channels. However, in the average activity of many neurons, it may not be possible to decompose a large number of control signals. Implanted brain-computer interfaces, on the other hand, provide sharper recording and separation of many different commands, and it is possible for controlled devices to perform complex tasks. In EEG or myoelectric control systems, the person has to imagine or try to make representative movements of other limbs instead of the movement they want to do. However, in invasive systems, the movement that the person really wants to do can be distinguished and the effector device can be made; this gives a more natural feeling of control.

Creating sensory feedback

In addition to receiving the signal of the desired movement from the brain, the brain-computer interfaces can also give feedback by directly transferring the sensory signals to the nervous system. As with recording, sensory stimulation techniques can be invasive or non-invasive. Commonly used non-invasive methods stimulate neuronal ensembles with transcranial direct current stimulation or magnetic fields. In invasive stimulation techniques, sensory signals can be given with subdural (between the brain membranes) or intraparenchymal (within the brain tissue) electrodes. For example, a tactile sensation of the hand can be created by stimulating the cortex region of the brain where sensory signals are processed. This type of sensory feedback allows devices to be integrated into the person’s body image.

Types of effector devices

Effector devices that perform the movement in line with the commands of the brain-computer interfaces solved by the algorithm can be in different designs according to the needs of the person and the purpose of the system. The purpose of these devices is generally movement control and neurorehabilitation. Devices that perform movement can be functional electrical stimulation (FES), orthotic and exoskeletons, prosthetic and robotic tools.

Neuromuscular FES

Brain-computer interfaces can be paired with FES to provide voluntary control of movements. FES alone may not generate enough force to overcome gravity, so some FES systems can be designed as hybrids with exoskeletons or splint-like components. FES is clinically used for purposes such as strengthening muscles, reducing spasticity, and helping to heal paralysis. When combined with BAA, FES alerts are user-controlled; this can strengthen learning mechanisms. However, obtaining coordinated movements with FES, which is already a difficult application, is further complicated by BAA integration. In addition, FES as a movement-generating mechanism is not suitable for every patient. For example, peripheral nerve damage and lower motor neuron diseases do not respond to FES. Some patients cannot tolerate the electrical currents that cause muscle contraction. In these patients, the movement of the affected limb can be achieved with exoskeleton or robotic devices. Virtual reality can be preferred as an end effector to reduce pain in amputee patients.

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Control of exoskeleton and robotic devices

Exoskeletons and orthotics are useful for supporting joints in functional positions; they can also provide movement throughout the range of motion. This approach is valid in patients with lower motor neuron disease or severe muscle wasting. Interest in BBA with exoskeleton is increasing in patients with upper motor neuron disease such as stroke. Motor exoskeletons can increase voluntary or FES-evoked muscle strength and enable weak joints to participate in treatment. This type of BCI systems are used for both arms and legs. Examples are Rex Bionics [Boston, MA] for the gait, Cyberdyne’s HAL exoskeleton [Tsukuba, Japan] for the arm, and BOTAS [Tokorozawa, Japan] for the arm. The combination of robotic devices and brain-computer interface is beneficial in terms of increasing patient participation in the intensive rehabilitation process.

Use of brain-computer interfaces in rehabilitation

The potential of brain-computer interfaces in the treatment of neurological diseases increases the collaboration of biomedical engineers and clinicians. Advances in the brain-computer interface focus on restoring or compensating movement in the rehabilitation patient. For compensatory uses, BCI enables the patient to perform tasks such as using a keyboard, surfing the Internet, controlling lights, heat, television at home, managing a motorized wheelchair, controlling a neuroprosthetic arm or leg. When used to restore normal central nervous system functions, it acts by strengthening activity-dependent brain plasticity. BBA synchronizes movement brain activity with real movement and sensations generated by effector devices.

BBAs have been used as an auxiliary communication tool in traumatic brain injuries with aphasia and locked-in syndrome. Regions where brain tissue is intact are used for implanted BAA systems for movement and sensation. In cases where the primary motor cortex is damaged, auxiliary motor areas and parietal sensory areas can be used for BAA. Therapeutic functional gains can be achieved with BAA in corticospinal tract injuries where the connection of the cerebral cortex with the spinal cord is impaired. However, more clinical studies are needed to understand how useful BAA really is.

ethical issues

The use of BCI brings with it some ethical problems. Ethical issues come to the fore, especially since invasive techniques involve certain risks. The patient’s autonomy and informed consent must be ensured before the procedure is performed. In cases where these are not possible for the patient, the official guardian can be the decision maker. Surgical procedures in invasive methods may not be vital and may have experimental characteristics. In addition to its potential benefits, it can have undesirable consequences such as ineffectiveness or loss of function. The cost-effectiveness of these expensive techniques is another controversial issue. Does the cost of these practices to the social security institution and the society compensate with the benefits it provides to the patient? These procedures cannot be performed for everyone, they are currently used in a small number of patients. How to select patients is another problem.

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