BMI as an effective means for rehabilitation of movement disorders
Neuroscience has shown that certain parts of the brain become active when people try to make some kind of motion.
For example, it is known that the part of the brain that controls hand movements, called the hand motor area, becomes active when a person tries to move his/her hand.
Conversely, if you measure the activity in that area, you can see that this person is trying to move the hand. Then, for instance, by connecting a brain activity measuring device and a robotic arm, a person can control the robotic arm as if moving the hand on his/her own.
While the study of applications of this technology is advancing in various fields, we are conducting research to apply it to rehabilitation of patients with movement disorders.
For example, cerebrovascular disease, or stroke, affects about 290 thousand people a year, with many of these patients suffering various sequelae, including movement disorders. As a result, it is the number one cause of being bedridden (about 40%), and annual related medical expenses have reached 1.8085 trillion yen, and it tends to increase year by year.
Brain disorders can cause movement disorders because commands from the brain may not be sent out of the motor area, or to the hand muscles.
This is because part of the neurons is damaged by the stroke and dies, and the pathway of the brain to transmit commands is interrupted. This may sound unrecoverable, but it is not.
As an analogy, if you take the Chuo Line from Tokyo Station to Shinjuku Station, but an accident occurs at Ochanomizu Station on the way and the train becomes stuck, you can transfer to the subway or other transport to reach your destination.
Or, if you know in advance that the Chuo Line has stopped, you can take the Yamanote Line to Shinjuku Station instead. It may take longer than the shortest route, but you can reach your destination.
The circuit of the brain works similarly to this route map of Tokyo. Even if the usual pathway is blocked, the command can be transmitted through a different pathway.
However, unlike trains that you can judge by looking at the route map, you cannot see the circuits of the brain.
Therefore, a therapist deals with a patient one on one and tries to find a trigger to move the hand. Once the therapist discovers it, an attempt can be made to rehabilitate the patient by repeating the process. This is how new pathways are created.
We thus believe that BMI can play a major role in such a process.
BMI is one of the potentially effective countermeasures against the year 2025 problem
When BMI is used for rehabilitation, a device that measures brain activity is attached on the head. It is like wearing a cap that fits your head. The cap is connected to an electroencephalograph and a computer, and the computer is connected to a robotic device that can be worn on the hand like a glove.
Patients wearing such devices, for example, are shown an image of a ball rolling toward their hands, and are asked to imagine making the same movement. A healthy person has brain activity required to grab the ball, but a stroke patient with a movement disorder may have weak signal level, or may not have such signals at all.
When the BMI system detects brain activity, it puts a pneumatic robotic glove in motion to grab the ball. In other words, when the patient’s brain is activated properly, the paralyzed hand does move with his/her intent.
In addition, the glove is designed to move with a weak level of brain activity at the beginning, but requires progressively stronger signals in later stages. In a word, the patient’s body moves in conjunction with brain activity, instead of use of a robot to move the body blindly.
By repeating this training, the patient may eventually be able to move his/her hands or have a wider range of motion without the device. In other words, a new pathway will have been created and rebuilt to substitute a problematic or inactive one.
When the device was actually used in hospitals and other settings, doctors and therapists were surprised to find that it was able to help move the hands of patients whose rehabilitation had not been successful to that point.
Also, compared with conventional rehabilitation, it has an effect of motivating patients. I think that is because robotic devices linked to the brain help us visualize and feel the movement of our hands.
Currently, we are developing a set of an easy-to-operate electroencephalograph and virtual images from a smartphone application that allows patients to engage in rehabilitation training similar to playing a game.
In fact, rehabilitation at the hospital is limited to 3 hours a day, and hospitalization is limited to 180 days. With such a device, however, patients can continue training on their own in the hospital room or at home after discharge.
In addition, the system allows rehabilitation to proceed, and the progress and results are recorded on a computer, allowing one therapist to deal with several patients.
For this reason, we believe that BMI, which is expected to reduce the burden on medical professionals and promote the reintegration of patients into society through effective rehabilitation, will be one of the effective measures in response to the 2025 problem, in which Japan’s rapidly aging population is expected to lead to doctor and caregiver shortages.
Visualization of brain activity is an effective way to change brain activity
There is another important point about BMI. It is visualization of brain activity.
As mentioned earlier, although neuroscience has shown that certain parts of the brain are active when people try to make some kind of motion, we typically cannot see our own brain activity.
However, if we show brain activity, for example, in a bar graph, and see it with our own eyes, we will be able to intentionally control brain activity. This is called neurofeedback and is attracting attention as a technology that actively changes brain activity patterns.
For example, people with ophidiophobia are usually treated by observing snakes step by step and familiarizing them with the creatures. However, it exposes the fear of snakes little by little, which can be stressful for such people.
Therefore, we visualize the activity of the part of the brain that generates the fear of snakes in the form of a bar graph. Patients are trained to raise and lower the activity by themselves by looking at the bar graph.
In other words, patients can learn to control the fear of snakes without actually seeing them.
In short, by visualizing brain activity, we can intentionally perform actions and controls that affect brain activity, that is, we can feed back to the brain, and thereby enhance our activity and change ourselves.
This technology is still under study, but if it is brought into practical use in the future, it is expected to be applied not only to phobias, but also to various mental disorders such as depression.
The use of BMI in rehabilitation for people with movement disorders is, in fact, visualizing the brain activity of moving hands with the movement of gloves.
In conventional rehabilitation, a therapist treats patients by trial and error while touching or talking to a patient’s hand in order to find a trigger to make a new pathway to move the hand in the brain.
However, by visualizing the activity of the brain, we believe that patients themselves can actively participate in creating new pathways in the brain to move their hands.
In other words, by looking at their hand moving, they can create brain activity in their brain that moves the hand.
In addition, therapists can provide better support to patients if brain activity can be visualized and checked.
Currently, we are conducting joint research with hospitals specializing in rehabilitation and accumulating various clinical data.
Stroke is associated with various sequelae, and there are many cases where several factors are complexly intertwined. We therefore need to accumulate a lot of data in order to provide the optimum rehabilitation according to the diversity.
In the near future, I think such rehabilitation will be put into practice. We believe that BMI is a very useful tool for this purpose.
* The information contained herein is current as of November 2020.
* The contents of articles on Meiji.net are based on the personal ideas and opinions of the author and do not indicate the official opinion of Meiji University.
* I work to achieve SDGs related to the educational and research themes that I am currently engaged in.
Information noted in the articles and videos, such as positions and affiliations, are current at the time of production.