News Glove with Sensors Measures Spasticity More Accurately than Physicians Glove with Sensors Measures Spasticity More Accurately than Physicians by Janet Stewart, MSc | April 24, 2017 Share this article: Share article via email Copy article link A Ā multidisciplinary team at the University of California at San Diego has come up with a computerized glove used as a sensor to measure spasticity, or stiffness, in the limbs of patients with multiple sclerosis, cerebral palsy, and stroke. The system is more accurate than physiciansā assessments of spasticity through touching, but still needs work, the team said. Experts in signal processing, robotics, printable electronics, neurosciences and medicine teamed up to develop the device, which will allow doctors to adjust medication to meet patients’ spasticity needs. Inaccurate measurements of spasticity can lead to patients receiving too little or too much medication for spasticity. This can mean ineffective treatment on the one hand. Or, on the other hand, it can mean money wasted on high doses of medication that are not needed, or even overdoses. Physicians assess spasticity on the basis of how much resistance they feel when moving a patientās limbs. They rate the resistance on the Modified Ashworth Scale (MAS), a simple measure of spasticity. Results for the same patient can vary greatly from one physician to the next. The goal of using a glove with sensors is to have an objective, accurate, and consistent measure of spasticity. A doctor wears the glove, which is a regular sports glove with over 300 pressure sensors taped to the palm. The sensors are connected to a computer that calculates the amount of power needed to move a limb. The more power needed, the greater the spasticity. In an initial study, two physicians assessed spasticity in five cerebral palsy patients by feeling resistance in the flexing and extending of patientsā arms and legs. The physicians provided their own spasticity ratings using MAS, without knowing the readings from the glove. Only 27 percent of their spasticity ratings agreed with each other. The glove was also tested with a robotic system called a mock patient. That system consists of an artificial arm that can be moved up and down and set to different levels of arm motion resistance. The arm has sensors that measure the amount of power needed to move it accurately. The power measured to move the mock patient arm was compared with the power the glove measured. Researchers found that the mock patient results agreed with the glove results in 64% of cases. āThis number needs to be higher if we want to deploy our system for use in the hospital, but it shows better consistency than existing spasticity assessments,ā Harinath Garudadri, a research scientist at the universityās Qualcomm Institute and the projectās lead investigator, said in a UC San Diego news release by Liezel Labios. āMany clinical exams and procedures are very subjective and rely on measurements that are done with a physicianās hands,ā said Andrew Skalsky, director of the division of Rehabilitation Medicine at Rady Childrenās Hospital. āWe often make major medical decisions and diagnoses based on touch and feel. With this technology, we can start to develop objective measurements for subjective processes.ā The team is in the process of trying to optimize theĀ computerized glove’s measurements. It believes the technology can also be applied to other procedures thatĀ rely on a doctor’s touch and feel to assessĀ a patient’s condition. These include physical therapy, monitoring of spine health, and assessing the severity of hip dislocation in infants. For more information about the technology, check out the UC San Diego video below. Print This Page About the Author Janet Stewart, MSc Janet Stewart is a life sciences writer and editor, holds an MSc. in Virology and Immunology and has worked on research on multiple sclerosis during the course of her graduate studies. Tags diagnosis, spasticity, stroke
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