09 Oct Computer game to quantify motor learning in cerebral palsy
Human interaction with the physical world is increasingly mediated by automation – planes assist pilots, robots assist surgeons, and cars assist drivers. Automation is introduced in such systems to assist the human and improve performance. However, performance improvement is not guaranteed, since the human may misunderstand the automation’s intentions or behave in a manner not anticipated by the automation. Although some applications may someday yield to full automation (e.g. cars can already drive themselves in traffic) legal and ethical concerns related to safety and accountability will ensure humans play a critical role in many such systems for the foreseeable future. Therefore it is imperative that we develop techniques that guarantee the performance of systems comprised of human and automation elements, which we term human-cyber-physical systems (HCPS).
The purpose of this research is to see whether there is a difference between how unimpaired individuals and individuals with neurologic injury, such as cerebral palsy and stroke learn to control cyber-physical systems. We would like to see whether the techniques developed in this study can separate the motor impairment from the motor learning skill for targeted rehabilitation.
Hemiplegic cerebral palsy, above 13 years old, and manual dexterity approximately equivalent to modest skill at video games in one or both arms sufficient to utilize the haptic devices to control the virtual robots
Additional Study Details
Full Study Title
Provably Safe HCPS
Samuel A Burden
Accepts Healthy Volunteers?
University of Washington Department of Electrical and Computer Engineering
185 E Stevens Way NE 455
Seattle, Washington 98195