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A team of researchers — including Shirley Ryan AbilityLab research scientist Mary Ellen Stoykov, PhD, OTR/L — has developed a wearable wrist device powered by a machine-learning algorithm that can continually track changes in arm movement impairment caused by stroke.
Monitoring changes throughout the entire rehabilitation process will allow clinicians to make real-time adjustments to therapy programs for tailored interventions and personalized care.
“This new device will enable continuous monitoring of patients during upper-limb rehabilitation after stroke,” said Dr. Stoykov. “This marks an important step toward more personalized treatment for stroke survivors and, hopefully, will lead to improved outcomes for patients. Because the measurement is more precise, clinical trials will require fewer participants and can be completed in less time.”
Dr. Stoykov is one of the authors of a new paper about the wrist device, published in Science Translational Medicine. The research was led by researchers from the University of Massachusetts Amherst (UMass) and conducted alongside colleagues from Washington University in St. Louis and Harvard Medical School/Mass General Brigham.
“We are the first group to actually show that, using wearable data, we can extract information about patients’ motor severity, which clinicians can actually use to determine whether their intervention is effective or not,” said Sunghoon Ivan Lee, PhD, associate professor in the Manning College of Information and Computer Sciences at UMass Amherst and corresponding author on the paper describing this new technology.
Dr. Lee also was one of the first funding recipients of Shirley Ryan AbilityLab’s Center for Smart Use of Technologies to Assess Real-World Outcomes (C-STAR) Pilot Project Program in 2020 — an opportunity he learned about through Dr. Stoykov.
Tracking Stroke Recovery Beyond the Clinical Environment
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Annually, more than 795,000 Americans experience stroke, with upper-limb mobility issues affecting up to 77% of patients immediately following the stroke. About 40% of patients continue to have chronic issues, posing a major limitation to independent living.
While occupational therapy and physical therapy improve arm movement in patients after stroke, there are some limitations. Currently, progress is measured by a clinician’s observational assessment, which takes about 30 minutes. Because this is a time-consuming process, assessment typically occurs only pre- and post-rehabilitation.
With a wearable monitor, such as the wrist device developed in this latest research, recovery data collection can be ongoing and occur outside of therapy sessions.
This would allow therapists to make timely adjustments to a patient’s treatment strategies for more personalized rehabilitation. Additionally, clinicians could better track a patient’s movement in a real-life environment — providing a truer picture of movement at all times of day, instead of one snapshot of time in a clinical setting. Finally, patients would be able to track their own recovery progress, with an aim toward increasing their engagement in and motivation for therapy.
Read more about this research.
