Technology created by researchers at the University of Texas in Austin has allowed those with tetraplegia, the inability to move their arms and legs due to spinal injuries, to control a wheelchair which translates brain signals into wheel movements. In a press release, the researchers said this new technology is “a sign of future commercial viability for mind-powered wheelchairs that can assist people with limited motor function.”
The invention involves a skullcap with 31 electrodes which is designed to detect brain signals and a laptop fixed to a wheelchair with an AI that can translate the signal to the wheelchair.
In order to use the device, users simply have to imagine they are moving with their hands and feet.
To move right, those using the wheelchair have to imagine moving both arms and to move left, they have to imagine moving both legs.
The press release by the university stated this new study is “significant” due to the noninvasive equipment involved for the wheelchair operator.
They said: “The researchers did not implant any kind of device into the participants, nor did they use any kind of stimulation on them.”
The wheelchair was also designed with sensors to help users navigate safely, which used robotic intelligence software to scan the environment.
Wheelchair users involved in the study were trained in order to use the mind-controlled wheelchair.
The New Scientist has reported that the researcher tested the wheelchair with three participants, who were all able to move around a cluttered room with a “reasonably high level of accuracy”.
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That participating in the study were first asked to move either left or right 60 times during a series of ten training sessions.
‘Person One’ was able to deliver the correct command on average 37 percent of the time, and this increased to 87 percent by their final training session.
The steering accuracy of ‘Person Three’ improved from 67 percent to 91 percent while ‘Person Two’ was able to consistently steer with an average accuracy of 68 percent throughout their training sessions.
Researcher José Millán from the University of Texas said: “There will be people who will learn it very fast and very well, then there will be others who will need more time to learn, such as Person Two, but I think anyone can learn to do it.”
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Participants were then asked to navigate the wheelchair through four checkpoints in a hospital room, which contained cluttered objects such as beds, chairs and medical equipment.
‘Person One’ was able to finish the course in around four minutes with 80 percent accuracy with over 29 attempts.
‘Person Three’ was able to complete the trial in seven minutes with 20 percent success with 11 attempts.
However, ‘Person Two’ was unable to complete the course but managed to reach the third checkpoint at around five minutes during 75 percent of their attempts.
The technology is a breakthrough, however, it might still not be ready for other everyday scenarios.
Mr Millán said: “I wouldn’t say the approach is useful on busy streets or less controlled environments, but the ability to move independently at all can be a huge benefit to these people.”