Moving a wheelchair just with your thoughts!
"Thoughts are free, but who can guess them?" is the theme of one of the most cited German poems and volk songs. Interestingly, recent research seems to give an answer. They can be guessed by so-called brain-computer interfaces (BCIs), at least some of the thoughts but with promising success. Researchers are developing new technologies that are able to read your mind and allow you to control external devices just with your thoughts, also with applications in clinical rehabilitation. The use of these systems as a rehabilitation method for patients is under particular research. Together with our international partner, our research group is working to further improve these BCIs. In particular, we examine how to teach participants to do mental imagery, and whether improved instructions also improve the usability and accuracy of such systems. In addition, we are studying advanced mathematical analysis to improve the BCI system for recognizing different brain states.
The public's interest has been aroused especially in recent years. In 2016, interest in BCIs was sparked after Elon Musk co-founded Neuralink. Neuralink is a neurotechnology company claiming not only to restore but to even enhance human functioning with implantable BCI systems. Just last year, ImmersiveTech broadcasted a video showing a paralyzed patient moving around barriers with an electric wheelchair. These science-fiction-like advances are observed with great interest by the general public, but a large part of the online community is also skeptic. Questions such as "Can they read my thoughts through BCI?", "Will this technology allow us to actively access all our memories?" seem to arise more frequently.
Although 'mind reading' in its simplest form is possible under very specific conditions, non-invasive methods such as electroencephalography, have not yet achieved good levels of accuracy when a BCI system must differentiate in real-time between different brain activities triggered by different mental activities. At present, the accuracy of non-invasive BCI systems for differentiating between different mental images, for example the imagination of a hand movement as opposed to an imagination of a foot movement, is around 74 percent. This is good, but not sufficient for certain applications. In other words, it is possible to control a wheelchair more or less well with such mental ideas. For example, if you want to turn right, do so with current accuracy 74 percent of the time.
Many researchers, including us, advocate an interdisciplinary and joint effort to bring BCIs from the laboratory into practice. Current challenges can thus be tackled in a more promising way. The resulting advances could not only help support paralyzed patients, but also help improve the diagnosis and treatment of many other neurological disorders. Whether a large-scale clinical application is feasible in the following decade remains unclear; nevertheless, apparently small improvements in instruction methods have already shown to enhance the performance of such systems.
The public's interest has been aroused especially in recent years. In 2016, interest in BCIs was sparked after Elon Musk co-founded Neuralink. Neuralink is a neurotechnology company claiming not only to restore but to even enhance human functioning with implantable BCI systems. Just last year, ImmersiveTech broadcasted a video showing a paralyzed patient moving around barriers with an electric wheelchair. These science-fiction-like advances are observed with great interest by the general public, but a large part of the online community is also skeptic. Questions such as "Can they read my thoughts through BCI?", "Will this technology allow us to actively access all our memories?" seem to arise more frequently.
Although 'mind reading' in its simplest form is possible under very specific conditions, non-invasive methods such as electroencephalography, have not yet achieved good levels of accuracy when a BCI system must differentiate in real-time between different brain activities triggered by different mental activities. At present, the accuracy of non-invasive BCI systems for differentiating between different mental images, for example the imagination of a hand movement as opposed to an imagination of a foot movement, is around 74 percent. This is good, but not sufficient for certain applications. In other words, it is possible to control a wheelchair more or less well with such mental ideas. For example, if you want to turn right, do so with current accuracy 74 percent of the time.
Many researchers, including us, advocate an interdisciplinary and joint effort to bring BCIs from the laboratory into practice. Current challenges can thus be tackled in a more promising way. The resulting advances could not only help support paralyzed patients, but also help improve the diagnosis and treatment of many other neurological disorders. Whether a large-scale clinical application is feasible in the following decade remains unclear; nevertheless, apparently small improvements in instruction methods have already shown to enhance the performance of such systems.
Usage for neurorehabilitation and training of athletes' performance.
Brain-computer interfaces (BCIs) can be used for modulating the brain activity in a way that it is beneficial for motoric and cognitive abbilities. In the clinical domain the BCIs can be used for motoric rehabilitation of patients who suffered from a stroke. Patients train the brain activity that was affected by a stroke and by this they try to restore the communication and functionality of the affected limb. BCIs can also be used in cognitive rehabilitation for instance in children with Attention Deficit Hyperactivity Disorder (ADHD). Children try to learn how to modulate and normalize the brain rhythms connected to the affected cognitive domain - i.e. attention. Beside the clinical domain, BCIs can also be used in the sport domain. Nowadays, more and more attention is devoted not only to the physiological and biomechanical abilities of the athletes but also to their competence in focusing on the task or controlling the pressure and anxiety. Promoting these abilities via the BCIs is beneficial for sport performance.
What is the purpose of our research group?
Although BCI systems can assist others in several different ways, they are rarely used outside the laboratory setting due to low reliability and the inability of some users to control them. Our research groups try to tackle these issues by investigating two areas of improvement. The first area we investigate is related to how users are instructed on operating BCI systems (NIMI-Study). The second area is related to how the measured brain activity is converted to machine-readable output (TIC-Study). The scope of our research group is to improve the usability of brain-computer interfaces and further expand our knowledge and understanding of the underlying issues.
Already Participated
About Us
Our group focuses on improving brain-computer interfaces to contribute to their futur application in different health care settings. In this, we especially focus on improving two aspects of these systems: instructions and mathematical analyses.
