Smart glove could help measure muscle stiffness

Mike Crossley was born with cerebral palsy, a neurological disorder that has among its symptoms muscle stiffness. Doctors assess the degree of his muscle stiffness using touch and feel during physical exams, grading it on a subjective rating scale they use to decide on medications and therapies.(photo grabbed from Reuters video)
Mike Crossley was born with cerebral palsy, a neurological disorder that has among its symptoms muscle stiffness. Doctors assess the degree of his muscle stiffness using touch and feel during physical exams, grading it on a subjective rating scale they use to decide on medications and therapies.(from Reuters video)

CALIFORNIA, United States (AFP) — Mike Crossley was born with cerebral palsy, a neurological disorder that has among its symptoms muscle stiffness. Doctors assess the degree of his muscle stiffness using touch and feel during physical exams, grading it on a subjective rating scale they use to decide on medications and therapies.

The problem, according to Dr Andrew Skalsky, director of the division of Rehabilitation Medicine at Rady Children’s Hospital, is that the scale often produces inconsistent results.

Skalsky teamed up with scientists at the University of Southern California’s Qualcomm Institute to come up with a solution — a sensor-filled glove for doctors to wear that measures the amount of force and speed needed to move a patient’s limb.

“This technology will, in addition to what they do, it will provide objective metrics that they can refine their diagnosis and refine their interventions. So that’s really what we’re hoping for that the clinicians would use it and demonstrate that there are improved outcomes in taking care of patients,” said Harinath Garudadri (pronounced: HARR-ee-nat Gara-DAT-ree), a research scientist the institute.

Garudadri and Skalsky worked with electrical engineers and neuroscientists to develop the glove. It has 300 pressure sensors to measure the amount of force required to move a patient’s limb and a motion sensor on the back to measure how fast the limb is being moved.

All that information is fed in to a computer to be processed and mapped in real time using algorithms developed by Garudadri’s group.

Researchers used a “mock patient arm” to simulate the flexing motion of an actual patient’s arm and validate their results. They set the arm’s resistance, knew the amount of power required to move the arm and then tested whether the glove produced a matching result.

Garudadri said results from the mock patient arm were impressive.

“The first thing that we did was develop a glove with multiple sensors and a motion sensor and we found that between two doctors and five patients that they tested they were agreeing only 26 percent of the time. So we developed the mock patient that you saw. That has its own sensors and it is also measuring how much work is being done in moving the mock patient arm. And by comparing the numbers that come from the glove and the mock patient, we are eighty two percent. So things have really improved,” he said.

Patients who have suffered from stroke, brain injury and other muscle control disorders could all benefit from doctors’ ability to better evaluate and treat their conditions.

Researchers say the high-tech glove, which is still in development, could also potentially be used in other cases that rely on a doctor’s touch and feel to assess a patient’s condition.