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Converting Brain Signals into Action
Today, 8 million Americans are living with paralysis or have lost limbs. Many could benefit from technologies that would help them carry out daily activities, but high-tech prosthetics or other such devices are not always sufficient to meet these needs, particularly for those who are paralyzed. To improve the quality of life for these individuals, NCATS-supported investigators at Pitt are exploring two different computerized chips that convert brain signals into an action simply through the patient's thinking about the action.
"The problem has always been the control of the prosthetic by someone with limited ability to move," said Michael Boninger, M.D. (link is external), professor and chair of the Department of Physical Medicine and Rehabilitation at the Pitt School of Medicine. Boninger and Andrew Schwartz, Ph.D. (link is external), a professor of neurobiology at the medical school, have built a collaborative research program to develop brain-computer interface devices that interpret the brain's still-intact command abilities and convey them to high-tech prosthetics and assistive devices.
A team of NCATS-supported researchers at the University of Pittsburgh developed a micro-electrocorticography grid that may help paralyzed individuals move again. The device, which is implanted in the brain's movement-controlling motor cortex (see image inset), helps this study participant practice simple computer tasks using only her mind. A computer system interprets her brain's electrical impulses captured by the device then converts the signals into movement controls in virtual environments. (University of Pittsburgh School of Medicine Photo)
A team of NCATS-supported researchers at the University of Pittsburgh developed a micro-electrocorticography grid that may help paralyzed individuals move again. The device, which is implanted in the brain's movement-controlling motor cortex (see image inset), helps this study participant practice simple computer tasks using only her mind. A computer system interprets her brain's electrical impulses captured by the device then converts the signals into movement controls in virtual environments. (University of Pittsburgh School of Medicine Photo)