Objective: The objective of our pilot study was to assess the feasibility of using a portable accelerometer system to accurately identify motor findings in patients with Parkinson’s Disease (PD). A second objective was to identify novel motor tasks tailored to the sensor system that could aid in remote detection of rigidity and prediction of freezing of gait (FOG).

Background: PD is largely considered a clinical diagnosis, but even in experienced movement disorder neurologist hands, accuracy is not 100%.  Objective measurement using accelerometry has been increasingly recognized as a complementary diagnostic and research tool.

Method: Six PD patients and five age-matched controls participated.  Participants wearing the accelerometers were guided through the Movement Disorders Society Unified PD Rating Scale (MDS-UPDRS) examination while a board-certified movement disorder neurologist completed an independent assessment.

Two supplemental tasks were created to complement the standard assessment, Wrist rotation (WR) and Metronome-guided foot tapping (MGFT).  These tasks were created to assist in an effort to develop tasks that could be performed in a standardized fashion and employed in remote visits (i.e. telehealth). Unpaired t-tests, ANOVA and linear regression analyses were calculated for data analysis.

Results: Our preliminary analysis yielded the following:

– Mean stride length strongly correlated with total MDS-UPDRS part 3 motor scores and exhibited a strong negative correlation with FOG item on the UPDRS (R² = 0.6739, m= -0.17, p= 0.0067).

– Wrist Rotational area was reduced in PD patients compared to controls (576 vs 1729 mm² p= 0.026).

– PD patients had greater variability in rotation when performing wrist pronation-supination (Standard deviation of PD vs control: 8.28 vs 2.54 degrees, p = 0.038).

– With metronome guided foot tapping, PD patients trended towards a larger variation or standard deviation of beat timing than control participants (p=0.09).

Conclusion: Using portable sensors, we were able to identify differences in motor function between PD patients and controls. These data serve as a proof of concept that wearable technologies may assist in the diagnosis and monitoring of PD progression, even remotely.  Larger numbers of participants will need to be assessed to further define the medical potential of accelerometer sensor systems.

References: 1. Rajput, A. H., & Rajput, A. (2014). Accuracy of Parkinson disease diagnosis unchanged in 2 decades. Neurology, 83(5), 386-387. doi:10.1212/WNL.0000000000000653
2. Rastegari, E., Ali H., & Marmelat, V. (2022). Detection of Parkinson’s Disease Using Wrist Accelerometer Data and Passive Monitoring. Sensors. 22(23):9122. https://doi.org/10.3390/s22239122

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MDS Abstracts - https://www.mdsabstracts.org/abstract/validating-wearable-sensors-as-an-assessment-tool-for-parkinsons-disease/