Individuals with significant physical impairments rely on assistive technology to communicate and control devices within their environment. Any reliable movement or muscle activation that the individual can perform can be used to activate switches, or use specialised keyboards and joysticks to operate assistive technology devices, such as wheelchairs and computers with customised software programmes.
In certain conditions where reliable movements are not available or control of such movements leads to fatigue, brain computer interfaces can offer an alternative solution.
A brain-computer interface (BCI) taps into the brain activations directly without waiting for signals to be transferred from the brain to the respective muscles.
Brain signals, typically recorded using non-invasive electrodes attached to the scalp, are processed to determine the command that the individual wanted to execute. One of the most promising BCIs relies on visual stimuli where the subject is presented with a number of icons which may be displayed on a computer screen, tablet or smartphone, each flickering at a specific flickering rate. The subject needs only to direct their attention to the desired flickering stimulus to execute the corresponding command. Such a system is said to be based on a brain phenomenon called steady state visual evoked potentials (SSVEPs) and compared to other alternative methods for brain-computer interfacing, it requires the least amount of user training while still achieving high performance rates.
Brain-computer interfaces can be an alternative assistive technology for people with amyotrophic lateral sclerosis, muscular dystrophy, brainstem stroke and cerebral palsy, among others. Assistive technologies such as BCIs can provide these individuals with more independence and a better quality of life, giving them the opportunity to regain some autonomy in controlling devices such as the television, motorised windows and doors, or even activating an elevator. Through the BrainApp project, funded by the Malta Council of Science and Technology, our team at the University of Malta in collaboration with Idox Health, are developing an SSVEP-based BCI to allow an individual to control a motorised bed independently. This would allow a person to change the various bed functions and ensure that they are lying in a comfortable position, without requiring a caregiver to do this for them repeatedly.
The team working on BrainApp would like to ensure that this project meets the requirements of potential users and are thus planning a study to identify these requirements and the users’ expectations of brain computer interface systems. For this reason we are inviting patients, or any individuals who feel that they may benefit from a brain computer interface and who wish to form part of this study, to contact us on email@example.com.
Professor Kenneth Camilleri, Dr Tracey Camilleri, Dr Owen Falzon and Inġ. Rosanne Zerafa have been working in the field of BCIs for the past 15 years, contributing to the international research community in improving the reliability of these systems and taking them outside of the controlled lab environment in which they are usually tested.
Did you know?
• The human brain is made up of around 100 billion neurons and they take up 25 per cent of our energy to fuel and maintain.
• The first recording of brain electrical signals was done by Hans Berger in 1924 by inserting silver wires under the scalps of his patients.
• Current research is trying to determine whether an electroencephalography EEG-based brain computer interface can be used to uniquely identify a person, similar to the use of finger prints.
• EEGs can be used as a diagnostic tool to diagnose conditions such as seizures, epilepsy and head injuries.
• Brain signals can also be used for gaming applications, where players can use specific brain patterns to control a game, apart from using joysticks and keyboards.
For more trivia see: www.um.edu.mt/think
• According to the roadmap drawn by the Brain/Neural-Computer Interaction (BNCI) Horizon 2020, by the year 2025 various applications will use brain signals as a source of information. These applications vary from allowing people to monitor their brain state to estimate mental capacity and performance level, to plug and play non-invasive use of BCIs in the home for stroke rehabilitation, to restoration of lost motor functions through control of exoskeletons.
• A brain-computer interface was used so that the subjects could move a cursor on a computer screen using just thought! When using such a system to monitor the brain activity during learning, researchers from Carnegie Mellon University and the University of Pittsburgh found that our brain does not produce new activity patterns but rather tries to repurpose patterns it already knows how to generate. This means that learning something new is suboptimal as the brain patterns do not change in the best possible way to make us proficient at new skills. Thus learning something new requires time and a lot of practice.
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