Machine Learning-Based Smartphone App to Evaluate Parkinson’s Symptoms
New smartphone app HopkinsPD, utilizes the smartphone’s microphone, touchscreen, and accelerometer to examine patients for symptoms while they perform daily tasks
Parkinson’s affects central nervous system of an individual, which affects movement including tremors. For diagnosis of this disease, evaluation of symptoms is vital. Scientists from Johns Hopkins University, the University of Rochester Medical Center and England’s Aston University developed new machine learning app, which is designed to monitersymptoms of Parkinson’s as they develop from initial stage. Using the app, patients can test themselves when and wherever they want, receiving a Parkinson’s disease severity score when they’re done. The final score reported by app can be shared with doctor for further treatment.
“If you think about it, it sounds crazy, but until these types of studies, we had very limited data on how these people function on Saturdays and Sundays because patients don’t come to the clinic on Saturdays or Sundays,” said Rochester neurologist E. Ray Dorsey, who led the research along with Johns Hopkins assistant professor of computer science, Suchi Saria. “We also had very limited data about how people with Parkinson’s do at two o’clock in the morning or 11 o’clock at night because unless they’re hospitalized, they’re generally not being seen in clinics at those times.” HopkinsPD is available on Android and on Parkinson’s Voice Initiative website. An iOS version, mPower, is available through the App Store. A paper on the research was published in the journal JAMA Neurology in April 2018.
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