Brain Computer Interface (BCI)

Brain Computer Interface Abstract Brain-computer interface (BCI) is a computer-based system that acquires brain signals, analyzes them, and translates them into commands that are relayed to an output device to carry out a desired action. In principle, any type of brain signal could be used to control a BCI system. Artifutech team is engaged in this challenging new work in the hope of restoring independence to severely disabled individuals and by interest in further extending human control of external systems. BCI allows improving the quality of life of disabled patients and along with being an integral innovation in various fields of life. Our Goal The idea of communicating directly through a control channel between a human brain and computer has been a topic of research for many years. In today’s era technology has advanced so much that it can process trillions of bytes of data within a fraction of a second, but still the input that is provided by we humans are at a much slower rate, so why not to discard the intermediaries used in between while transferring the command from mind to external device? Thus via BCI, it is possible to give commands to an external device directly via our brain. Here at Artifutech, our team is doing research on various aspects of BCI with an aim to integrate this technology in the lives of a common man. BCI Definition, Signal Types, and Operation BCI A brain-computer interface (BCI), sometimes called a neural-control interface (NCI), mind-machine interface (MMI), direct neural interface (DNI), or brain-machine interface (BMI), is a direct communication pathway between an enhanced or wired brain and an external device without using conventional neuromuscular pathways. That is, messages and control commands are delivered not by muscular contractions but rather by brain signals themselves. This BCI feature helps people suffering from most severe motor disabilities, including people with amyotrophic lateral sclerosis (ALS), spinal cord injury, stroke, and other serious neuromuscular diseases or injuries By reading signals from an array of neurons and using computer chips and programs to translate the signals into action, BCI can enable a person suffering from paralysis to write a book or control a motorized wheelchair or prosthetic limb through their thoughts or it can directly control a exoskeleton or can be a source of entertainment of a common man Types of Brain Signals Depending on the biophysical nature of the signal source, these signals can be broadly grouped into three categories: electrophysiological, magnetic, and metabolic.
 Electrophysiological Signals
 These signals result from brain activity and can be broadly classified according to the degree of invasiveness of the recording device
Figure1 : BCI systems based on electrophysiological signals measured by non-invasive (EEG), cortical surface (ECoG), and intracortical recording devices Electroencephalography (EEG) It is an electrophysiological monitoring method to record electrical activity of the brain. It is typically non-invasive, with the electrodes placed along the scalp, although invasive electrodes are sometimes used, as in electrocorticography. Being non-invasive they provide the simplest and safest BCI recording methods. Figure 1a- EEG-based BCI systems: shows two non-invasive BCI systems based on different EEG signal features. Electrocorticographic (ECoG) signals are recorded from electrodes surgically placed on the surface of the cortex. These electrodes measure the same signals as in EEG, but their closer proximity to the brain. Figure 1b- ECoG-based BCI systems: shows an example of human ECoG signals and topographies during two-dimensional movement control. Figure 1c- Intracortical-based BCI systems: shows a microelectrode array for intracortical recording, its placement location in human motor cortex, and results from intracortical BCI studies. BCI Operation & working

Figure2: controlling a robotic arm with BCI

Please refer to the below url for the Live working demo:


Figure 2: Illustrated the controlling of a robotic arm by the use of BCI. Here we have trained the algorithm to detect the brain waves and execute an associated output/command or action with respect to that particular thought or wave. Once the user thinks he/she is closing the fist, the brain wave associated with it is transferred to the robotic hand via a specified protocol and thus the robotic hand executes accordingly as shown in the figure2 above.


It consists of four essential elements

• Signal acquisition;

• Feature extraction;

• Feature translation; and

• Device output.


Figure 3: Illustrates the essential elements and operation of a BCI system, as well as its few applications. These four elements are managed through a specified protocol, that we follow. Signal Acquisition It refers to the measurement of the neurophysiologic state of the brain. For electrophysiological BCI systems in BCI operation, the recording interface i.e., electrodes, tracks neural information which reflects a person's intent embedded in the ongoing brain activity. The most common electrophysiological signals employed for BCI systems include: EEG recorded by electrodes on the scalp; ECoG recorded by electrodes placed beneath the skull and over the cortical surface; and local field potentials (LFPs) and neuronal action potentials (spikes) recorded by microelectrodes within brain tissue. Feature Extraction The signal-processing stage of BCI operation occurs in two steps. The first step, feature extraction, extracts signal features that encode the intent of user. In order to have effective BCI operation, the electrophysiological features extracted should have strong correlations with the user's intent. The signal features extracted can be in the time-domain or the frequency-domain or both . The most common signal features used in current BCI systems include: amplitudes or latencies of event-evoked potentials (e.g., P300), frequency power spectra (e.g., sensorimotor rhythms), or firing rates of individual cortical neurons. Our algorithm filters the digitized data and extracts the features that will be used to control the BCI. Feature Translation This constitutes the second step of signal processing which is accomplished by the translation algorithm, which converts the extracted signal features into device commands(with the use of our algo). Brain electrophysiological features or parameters are translated into commands that will produce output such as letter selection, cursor movement, control of a robot arm, or operation of another assistive device Device Output The signal features thus extracted and translated from the above two steps of signal processing provide the output to operate an external device. BCI Applications Clinical BCI applications People who are severely disabled by disorders such as ALS, cerebral palsy, brainstem stroke, spinal cord injuries, muscular dystrophies, or chronic peripheral neuropathies might benefit greatly from BCIs. By observing the extent of motor disability, people with physical disability fall into three reasonably distinct groups: • people who have no detectable remaining useful neuromuscular control and are thus totally locked-in; • people who retain only a very limited capacity for neuromuscular control such as weak eye-movements or a slight muscle twitch; and • people who still retain substantial neuromuscular control and can readily use conventional muscle-based assistive communication technology. For the people belonging in the first group, who are totally locked-in (e.g., by late-stage ALS or severe cerebral palsy). Resolution of this issue requires extensive and prolonged evaluation of each individual in order to resolve basic issues of alertness, attention, visual or auditory capacities, and higher cortical function At present, people belonging to the second group constitute the primary prospective user population for current BCI systems. This group, includes people with late-stage ALS patients who rely on artificial ventilation as their disease progresses, people with brainstem strokes, and people with severe cerebral palsy. Typically, they retain only very limited, easily fatigued, and/or unreliable eye movements or other minimal muscle function and thus cannot be adequately served by conventional muscle-based assistive communication technology. For people in this group, BCI systems may be able to provide basic communication more convenient and reliable control system than that provided by conventional technology The third group which comprises the largest group of potential BCI users consists of people who possess substantial neuromuscular control. People with high-cervical spinal cord injuries, could be served better by BCI over conventional assistive devices that provides their remaining voluntary muscle control (e.g., systems that depend on gaze direction or EMG from facial muscles). In the future, as the capacities, reliability, and convenience of BCI systems continue to improve, more people in this group could find them of value, and the number of people using BCIs could substantially increase. Potential BCI Users The potential uses of BCIs can be classified as: • direct control of assistive technologies; and • neurorehabilitation. Since the BCI serves as a replacement of normal neuromuscular pathways, the most obvious BCI applications are those that activate and control assistive technologies that are already in place to enable communication and control of the environment. These applications of BCIs to assistive technology encompass the areas of communication, movement control, environmental control, and locomotion. We have just begun exploring the possible uses of BCIs in neurorehabilitation. BCI Exoskeletons One of the most important applications of BCI is in the field of controlling Exoskeletons directly by the use of BCI. Crutch-less assistive LL exoskeleton is based on brain neural-computer interface (BNCI) control for balanced walking patterns & thus BCI can be a very useful application in exoskeletons actions/commands control. It can be used as an augmented system of locomotor therapy (LT) by reviewing its initial validation in a paraplegic patient having SCI. BCI can be combined with Virtual Reality (VR) based technology that could support patient/user training for reaching a high confidence level for controlling the exoskeleton virtually before the real transition. We are currently ongoing a research on exploring & developing a working prototype of BCI Exoskeletons. Movement control Restoration of motor control abilities for the paralyzed patients is another key application of BCI .We have systems that is able to support multidimensional control of the movement of an orthotic device such as a robotic arm. Functional electrical stimulation (FES) can also be used for restoration of motor function in paralyzed patients with intact lower motor neuron and peripheral nerve function and we are looking forward to it. Environmental Control BCI-based environmental control could greatly improve the quality of life of severely disabled people. People with severe motor disabilities are often home-bound. Effective means for controlling their environments (e.g., controlling room temperature, light, power beds, TV, etc.) would increase their well-being and sense of independence . Studies suggested that the self-control of the domestic environment realized with BCI technology increased the patient's sense of independence. Also, caregivers could be relieved to some extent from the need to be continually present. Neurorehabilitation BCI systems also have potential to serve as therapeutic tools to help people whose neuromuscular function has been impaired by trauma or disease to relearn useful motor function. Neurorehabilitation using BCI systems promotes functional recovery and may improve quality-of-life .This specific application of BCI systems seeks to augment current rehabilitation therapies by reinforcing and thereby increasing effective use of impaired brain areas and connections. Some of the other fields for BCI applications are: • Entertainment & Gaming; • Smart Home Control; • Military; and • Factories Future Scope BCI research and development is a multidisciplinary effort involving specialists form various domains. BCI technology is still in its infancy. Further research on different components of BCI development is still ongoing and challenging. These include explorations of: • useful brain signals; • signal recording techniques; • feature extraction and translation methods; • methods for engaging short- and long-term adaptations between user and system so as to optimize performance; • appropriate BCI applications; and • clinical validation, dissemination, and support. We are looking forward to translate this BCI technology into home systems for severely disabled individuals and a system of entertainment & control in the life of a common individual. The BCI home systems are currently limited to applications for simple communication (e.g., word processing, speech synthesizing, email, etc) and simple environmental control (e.g., TV, room temperature, etc.) Other applications, such as restoration of motor function, have been confined mainly to laboratory settings or limited lab-based demonstrations, and are not yet being used in everyday life. Thus our effort is to make this available & integrate this mind boggling technology in the lives of a common man.



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