Is the MyCap Finger Tapping Smartphone Application Effective in Differentiating Healthy Controls from Parkinson’s disease Patients? Preliminary Pilot Study Data (2807)

Objective: To evaluate if MyCap finger tapping task can distinguishing between healthy controls and Parkinson’s disease patients.

Background: Preliminary app studies demonstrated accurate capture of PD symptoms and potential for distinguishing between controls and PD patients. The MyCap app leverages ResearchKit, RedCap, and ResearchStack to capture subject data via iOS mobile devices. This distinct app collects data and readily synchronizes to RedCap research databases.

Design/Methods: Preliminary data from 30 subjects (18 PD, 12 HC) is presented. “Speed” is the average number of taps completed during each trial; “rhythm” is the inter-tap time interval in seconds. T-test was used to assess significant differences (p<0.5) in left-hand and right-hand speed and rhythm between PD and HC subjects.

All consented subjects completed the task two times about an hour apart on three days per week for five weeks. PD patients were asked to complete the task first in the off state followed by the on state one hour later. HC mimicked this pattern.

Results: The tapping task discriminated between PD and HC based on both speed (p<0.05) and rhythm (p<0.05) regardless of the hand and medication state. Exploratory analysis did not show significant difference between on-state and off-state speed and rhythm measurements among PD subjects.

Conclusions: Preliminary results demonstrate promise in detecting differences between PD and HC using MyCap tapping task. PD subjects tapped slower and less rhythmically than HC subjects, regardless of medication state or hand used. However, no distinction was made between medication states among PD subjects. Thus, MyCap finger tapping task can help to distinguish between PD and HC. Further analyses of a larger cohort of this ongoing trial may assist in demonstrating medication effect. Additionally, using other MyCap tasks may aid in capturing additional data points to quantify PD motor symptoms and medication effect.

Disclosure: Dr. Tripathi has nothing to disclose. Samantha Barkan has nothing to disclose. Yu Hou has nothing to disclose. An immediate family member of Fei Wang, PhD has received personal compensation for serving as an employee of IBM. Fei Wang, PhD has received personal compensation in the range of $50,000-$99,999 for serving as a Consultant for IBM. Fei Wang, PhD has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Boerhinger Ingelheim. The institution of Fei Wang, PhD has received research support from NSF. The institution of Fei Wang, PhD has received research support from MJFF. The institution of Fei Wang, PhD has received research support from NIH. Dr. Sarva has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Accorda Therapeutics. Dr. Sarva has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Amneal Therapeutics. Dr. Sarva has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Merz Pharmaceutics. Dr. Sarva has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Neurocrine. Dr. Sarva has received personal compensation in the range of $0-$499 for serving as a Consultant for Cala Trio. Dr. Sarva has received research support from Insightec. Dr. Sarva has received research support from NIH.