Scientists have created a wheelchair that can be controlled using MIND

A wheelchair that can be controlled with MIND: scientists have created a helmet that turns brain waves into wheel movements

  • Mind-controlled wheelchair helps paralyzed patients navigate cluttered room
  • The participants imagined that they were moving their arms or legs to control the chair.
  • To move to the right, the participants imagined the movement with both hands, and to move to the left, they imagined the movement with both feet.

A mind-controlled wheelchair that translates brain signals into wheel movements is bringing hope to more than 5.4 million Americans with musculoskeletal disorders.

Technology created by researchers from the University Texas in Austin includes a skullcap with 31 electrodes designed to detect signals in the brain’s movement-regulating region, and a wheelchair-mounted laptop so AI can translate the signals into wheel movements.

And all patients have to do is imagine that they are moving their arms and legs.

To move to the right, users imagined they were moving with both hands, and to move to the left, they imagined they were moving with both legs.

A mind-controlled wheelchair has been successful in helping paralyzed patients navigate a cluttered room. Patients wear a cap of 31 electrodes that pick up brain signals.

“The concept of a thought-powered wheelchair has been studied for many years, but most designs have used non-disabled people or stimuli that cause the device to be more or less in control of the person, rather than the other way around,” the researchers shared. Press release.

“In this case, three people with tetraplegia, an inability to move their arms and legs due to spinal injuries, operated a wheelchair in a cluttered natural environment with varying degrees of success.”

The skullcap with electrodes provides a non-invasive method of collecting brain signals and transmitting them to a nearby device—in this case, a laptop on the back of a wheelchair.

In the first part of the experiment, patients were taught how to use a mind-controlled wheelchair.

Brain signals are sent to a laptop attached to the back of a chair, and artificial intelligence translates the signals into wheel movements.

Brain signals are sent to a laptop attached to the back of a chair, and artificial intelligence translates the signals into wheel movements.

The researchers asked them to imagine that they were moving their arms and legs; they were then assigned different directions in the system.

The second success factor of this study is borrowed from robotics.

The wheelchair was designed with sensors that combed the environment and robotic intelligence software that helped the chair fill in gaps in user commands to facilitate precise and safe wheelchair movement.

The team tested everything on three participants who were asked to move left or right 60 times. New scientist reports.

During the first 10 workouts, “Person 1” gave the correct commands on average 37% of the time, and by the last 10 workouts, the accuracy increased to 87%.

And Man 3’s steering accuracy has improved from 67 percent to 91 percent.

To move to the right, participants imagined moving both arms.  To move to the left, they imagined moving both legs.  Otherwise the wheelchair moved forward

To move to the right, participants imagined moving both arms. To move to the left, they imagined moving both legs. Otherwise the wheelchair moved forward

“Person 2” consistently drove the car with an average accuracy of 68 percent throughout all training sessions.

The real test was then carried out – the participants were asked to move a wheelchair to four checkpoints inside a room filled with beds, chairs and medical equipment.

All participants had to walk around obstacles such as a room divider and hospital beds, which were created to mimic the real environment.

The first person completed the course in about four minutes with 80 percent accuracy over 29 attempts.

Person 3 completed it in seven minutes with a 20 percent success rate over 11 attempts.

However, Person 2 reached the third checkpoint in about 5 minutes on 75 percent of his attempts, but was unable to complete the course.

José del R. Millan, research correspondent from the University of Texas at Austin, said in a statement: “It appears that in order for someone to acquire good control over the brain-machine interface that allows them to perform relatively complex everyday activities, such as driving a wheelchair in a natural environment requires some neuroplastic reorganization in our cortex.”

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