The quantitative progression of motor symptoms of Parkinson's disease (PD) over time using wearable sensor data.
By Neha MathurOct 11 2023Reviewed by Lily Ramsey, LLM In a recent longitudinal study published in npj Parkinson's Disease, researchers tracked the quantitative progression of motor symptoms of Parkinson's disease over time using wearable sensor data and machine learning algorithms.
Wearables are invaluable tools for monitoring motor symptom progression in PD. They are portable, affordable, and can assess features of walking and balance spatiotemporally. In addition, they used walking and postural sway data collected by six wearable inertial measurement units to identify the preliminary signal of motor symptom progression in 74 PD patients over 18 months. In the study duration, all participants completed a total of seven visits.
They hypothesized that these models could detect a statistically significant progression of motor symptoms in PD patients earlier than the MDS-UPDRS-III scale. A multivariate LR model used the two kinematic features, showing the most statistically significant temporal progression. From 29 progressing features, forward feature selection identified six for use in the early stopping model . The team also investigated the RF Regressor with 29 progressing features as input .
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