New device would help rehabilitate stroke survivors by turning thoughts into actions, retraining motor pathways. The research aims to help stroke victims recover the ability of using their limbs with an exoskeleton and an electroencephalograph (EEG) brain-computer interface. When set into motion, the intelligent exoskeleton will use thoughts to trigger repetitive motions and retrain the brain’s motor networks.
Scientists at Rice University, the University of Houston (UH) and TIRR Memorial Hermann have received a $1.17 million grant from the National Institutes of Health (NIH) and the President’s National Robotics Initiative (NRI). The combined device will be validated by UTHealth physicians with as many as 40 volunteer patients in the final two years of the four-year R01 award, the oldest research grant offered by the National Institutes of Health (NIH).
The multidisciplinary team hopes to develop and validate a noninvasive brain-machine interface (BMI) to a robotic orthotic device that is expected to innovate upper-limb rehabilitation. The new neurotechnology will interpret brainwaves that let a stroke patient willingly operate an exoskeleton that wraps around the arm from the fingertips to the elbow.
“With a lot of robotics, if you want to engage the patient, the robot has to know what the patient is doing,” said principal investigator Marcia O’Malley, an associate professor at Rice and director of Rice’s Mechatronics and Haptic Interfaces Lab (MAHI Lab).
O’Malley said. “If the patient tries to move, the robot has to anticipate that and help. But without sophisticated sensing, the patient has to physically move – or initiate some movement.”
The team led by José Luis Contreras-Vidal, director of UH’s Laboratory for Noninvasive Brain-Machine Interface Systems and a professor of electrical and computer engineering, was the first to successfully reconstruct 3-D hand and walking movements from brain signals recorded in a noninvasive way using an EEG brain cap. The technology allows users to control, with their thoughts, robotic legs and below-elbow amputees to control neuroprosthetic limbs. The new project will be one of the first to design a BMI system for stroke survivors.
Initially, EEG devices will translate brain waves from healthy subjects into control outputs to operate the MAHI-EXO II robot, and then from stroke survivors who have some ability to initiate movements, to prompt the robot into action. That will allow the team to refine the EEG-robot interface before moving to a clinical population of stroke patients with no residual upper-limb function.
An earlier version of the MAHI-EXO II developed by O’Malley, already in validation trials to rehabilitate spinal-cord-injury patients at the UTHealth Motor Recovery Lab at TIRR Memorial Hermann, incorporates sophisticated feedback that allows the patient to work as hard as possible while gently assisting – and sometimes resisting – movement to build strength and accuracy.
“The capability to harness a user’s intent through the EEG neural interface to control robots makes it possible to fully engage the patient during rehabilitation,” Contreras-Vidal said. “Putting the patient directly in the ‘loop’ is expected to accelerate motor learning and improve motor performance. The EEG technology will also provide valuable real-time assessments of plasticity in brain networks due to the robot intervention – critical information for reverse engineering of the brain.”