Objective: To use inertial measurement unit (IMU) data from a mobile device, iPad or iPhone, to quantify PD patients’ gait and turning behavior, on and off anti-PD medication, during the Timed-Up-and-Go (TUG) test.

Background: The performance during the four distinct phases of TUG, Sit To Stand, gait, turning, Turn to Sit is traditionally collapsed into one metric: overall time to completion. Recent studies using inertial sensors have developed pivotal algorithms and metrics to quantify the individual phases of TUG; and using sensors on the torso and limbs, and have developed metrics that are sensitive to detecting PD movement abnormalities. In this study, a combination of new and existing algorithms were developed to analyze IMU data from a consumer electronics mobile device to determine if differences were present in PD patients completing the TUG test on and off anti-PD meds.

Methods: An iPad/iPhone mobile application was developed that utilized the embedded IMU to gather acceleration and rotational data to characterize patient’s center of mass movement in the medial-lateral and anterior-posterior planes and trunk rotation. Thirty-three PD patients were tested on and off (12 hours) anti-PD medication. Cadence (steps/sec), average velocity during turning (deg/sec), turn duration (sec), and total trial time (sec) were primary outcomes. A paired t-test or a Wilcoxon signed rank test was used to assess significant differences between on and off testing conditions. All reported p-values were corrected to account for multiple comparisons (Bonferroni, N=4).

Results: Average turning velocity was significantly slower when off compared to on medication (8.3%; p=0.011). Turn duration showed a trend to increase off meds compared to on, but lost significance when corrected (5.7%, p=0.067). Total trial time (p=0.2), and cadence (p=1.4) were not significantly different between on and off testing conditions.

Conclusions: A quantitative measure of movement, in particular turning, from a mobile device provides a low cost, easy to use tool that detected a significant difference in movement from PD patients on and off medication during TUG whereas total trial time did not. This result supports recent studies and shows the value of analyzing the separate behaviors of TUG individually with quantitative measures that have previously been linked to increased fall rates in PD patients.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/quantifying-turning-behavior-in-parkinsons-disease-patients-using-mobile-technology/