App Measures Parkinson’s Symptoms A smartphone app to objectively measure Parkinson’s disease severity? Yes, say researchers from Johns Hopkins University and the University of Rochester, based on a study indicating that the app can be used to help manage Parkinson’s disease (PD) symptoms—including voice—more effectively. With the HopkinsPD app, “Patients can use their mobile ... News in Brief
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News in Brief  |   June 01, 2018
App Measures Parkinson’s Symptoms
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Special Populations / Older Adults & Aging / News in Brief
News in Brief   |   June 01, 2018
App Measures Parkinson’s Symptoms
The ASHA Leader, June 2018, Vol. 23, 15. doi:10.1044/leader.NIB5.23062018.15
The ASHA Leader, June 2018, Vol. 23, 15. doi:10.1044/leader.NIB5.23062018.15
A smartphone app to objectively measure Parkinson’s disease severity?
Yes, say researchers from Johns Hopkins University and the University of Rochester, based on a study indicating that the app can be used to help manage Parkinson’s disease (PD) symptoms—including voice—more effectively.
With the HopkinsPD app, “Patients can use their mobile phones to complete a few simple tasks, which the proposed method turns into an objective score,” explains Suchi Saria of Johns Hopkins’ Department of Computer Science. “This score, when plotted over time, provides a lens into the patient’s Parkinson symptom profile and how it’s varying over time” and in response to medication.
In the study published online in JAMA Neurology, researchers assessed people with PD who completed five tasks—voice, finger tapping, gait, balance and reaction time—remotely on the app. A novel machine-learning approach objectively weighed features derived from each smartphone activity—stride length from the gait activity, for example—and generated a mobile Parkinson disease score (mPDS) on a scale from 0 to 100.
The researchers derived the mPDS from 6,148 smartphone activity assessments collected from 129 participants. The total score weights the factors: gait (33 percent), balance (23 percent), finger-tapping (23 percent), voice (17 percent), and reaction time (3 percent).
The mobile score captured intra-day symptom fluctuations, correlated strongly with current standard rating scales, and detected responses to medication.
Because there has been no way to measure the fluctuations in disease severity from hour to hour, many patients keep a motor diary and record when they experience good symptom control or complications like dyskinesia. These diaries are used to adjust medication doses.
Objective measurements of daily fluctuations and long-term symptom trends would allow medication adjustment based on the patient’s profile, researchers say.
The mPDS—which could be extended to wearable sensors or other devices, in addition to a smartphone—needs to be validated further in a larger sample, the researchers note.
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June 2018
Volume 23, Issue 6