Creating the Future of Stroke Recovery

Staying upright is a common challenge for patients with neurological damage from a stroke or older adults with a high falling risk, but pinpointing the specific weaknesses causing falls in a system as complex as the human body can turn diagnosis into high-risk puzzle for clinicians.

“Is the patient falling forward, or backwardto the side, or are they dropping straight down—and why? You need to know to do the rehabilitation,” says Li-Qun Zhang, a professor in the Fischell Department of Bioengineering at the University of Maryland, College Park; he is also a professor of orthopedics and of physical therapy and rehabilitation science at the University of Maryland School of Medicine in Baltimore.

With a new $4.6 million grant from the National Institute on Disability, Independent Living, and Rehabilitation Research, he and colleagues on both campuses will use the power of robotics and machine learning to improve rehabilitation interventions for patients with sensorimotor impairments resulting from a stroke, as well as for older adults who face a high risk of falls. A multi-institutional group led by Zhang has formed a federally recognized Rehabilitation Engineering Research Center (RERC) to conduct advanced engineering research and develop innovative technologies to solve particular rehabilitation problems or remove environmental barriers.

Today, many patients rely on routine clinical evaluations for therapies and recovery of sensorimotor function. But, these evaluations lack the ability to provide patients with accurate assessments of their impairments, which means they can’t receive precisely tailored, impairment-specific treatment.  

Zhang and his team are working to create rehabilitation technologies that more accurately assess complex sensorimotor impairments in both clinical and home settings. They plan to develop and translate impairment-specific treatments and technologies into useful, practical solutions that can improve patients’ quality of life, including apps and portable devices for remote rehabilitation—something that could be convenient at any time, but would be especially helpful during a public health emergency like the coronavirus pandemic, he said.

“The goal is to improve therapeutic outcomes by developing and testing assessment-based rehabilitation, carried out beyond hospitals and clinics to reach the patient at home,” Zhang said. 

The UMD-led team plans to investigate how specific sensorimotor impairments contribute to decreased mobility, slow and asymmetric gait, reduced balance and stability and an increased risk of falls. Resulting technologies could be used in impairment-specific therapeutic training using data from comprehensive, machine-learning powered assessments of patient impairments. In turn, patients would undergo tailored treatment to meet new targeted goals ranging from overcoming muscle weakness, to improving posture and balance control, to bearing weight or regaining the ability to walk with or without assistive devices. 

“This marks an exciting opportunity for engineers and medical experts to work together to create new treatment options that are tailored to address the specific needs of stroke patients and those who face fall risks,” said John P. Fisher, professor and chair of bioengineering. “The work put forth by this research team could one day make a world of difference in the lives of those who face a daunting prognosis involving a loss of mobility or other sensorimotor impairments.”

Zhang is working with the following center collaborators: co-director Peter Lum (Catholic University of America); Gad Alon, Clive Pai, Douglas Savin and Kelly Westlake (University of Maryland, Baltimore);  X. Li and Yang Tao (University of Maryland, College Park);  Jay Barton (Baltimore Veterans Affairs Medical Center); Jackey Gong (University of Alabama); and Sang Wook Lee (Catholic University) and Alex Dromerick, M.D. (National Rehabilitation Hospital).