Prof David Reinkensmeyer is collaborating with neurology professor Steve Cramer and electrical engineering professor Mark Bachman as well as former UCI doctoral student Eric Wolbrecht, who is now an assistant professor at the University of Idaho.
He said that although researchers know that exercise after stroke helps restore brain pathways, a concept known as use-dependent brain plasticity, what they don’t know is whether the exercise is more beneficial if it is aided by robots that guide the patients’ hands and help them complete specific tasks.
Current therapies were designed to be administered by physical or occupational therapists, limiting their affordability and availability. So, Reinkensmeyer said that there has been a concentrated effort to develop technology that can automate these processes.
’People prefer exercising with a robot that helps them complete computer games, so there’s a motivational benefit to robotics. But it’s not clear yet whether having a robot assist a person is more effective than just having them exercise without it,’ he added.
Researchers will work with local hospitals, starting with UC Irvine Medical Center, to begin studying patients in the first days after a stroke.
Reinkensmeyer’s research effort is two-pronged. The team will build a wearable sensor that will measure patients’ hand movements in the days and weeks after stroke but before therapy begins.
They will also fabricate a compact, portable device to assist the patients at home as they exercise the affected hand. The ’smart’ apparatus will build a computer model in real time of how much support each patient needs to complete the required tasks.
Patients will be randomly divided into two groups. In one group, the hand robot will assist in the limb exercises. The second group will also use the robot, but it will be programmed to provide a higher level of assistance. The device will encourage stroke sufferers to practice moving their fingers in different configurations and in different gripping techniques.
Outcomes will be measured by therapists using standard assessment measurements in conjunction with quantitative measurements from the robot.
Because the severity of stroke is an important factor in recovery, all patients will undergo brain scans prior to taking part in the study to determine the degree of damage to the brain. By correlating the data from the brain scans, the sensor and the information acquired by the robot, they then hope to be able to predict how much limb dexterity patients can expect to regain after a stroke.
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