Multi-Dimensional, Short-Timescale Quantification of Parkinson's Disease and Essential Tremor Motor Dysfunction - Sanderson, John B.; Yu, James H.; Liu, David D; Amaya, Daniel; Lauro, Peter M.; D'Abreu, Anelyssa; Akbar, Umer; Lee, Shane; Asaad, Wael F. (Frontiers in Neurology, 2020)
INTRODUCTION: Parkinson’s disease (PD) is a progressive movement disorder characterized by heterogenous motor dysfunction with fluctuations in severity. Objective, short-timescale characterization of these symptoms is necessary as therapies become increasingly adaptive. OBJECTIVES: This study aims to characterize a novel, naturalistic, and goal-directed tablet-based task and complementary analysis protocol designed to characterize the features of PD. METHODS: A total of 26 patients with PD and without deep brain stimulation (DBS), 20 control subjects, and eight patients with PD and with deep brain stimulation (DBS) completed the task. Eight metrics, each designed to capture an aspect of motor dysfunction in PD, were calculated from 1-second, non-overlapping epochs of the raw positional and pressure data. These metrics were used to generate a classifier to produce a unifying, scalar ‘motor error score’ (MES). These data were compared to standard clinical assessments of these same patients. Additionally, these data were compared to analogous data generated from a group of 12 patients with essential tremor (ET) to assess the task’s specificity for PD. Finally, a classifier was generated to differentiate between motor dysfunction in patients with PD with DBS in different stimulation states. RESULTS: The eight metrics calculated from the raw positional and force data captured during task completion were non-redundant. MES generated by the SVM analysis protocol showed a strong correlation with MDS-UPDRS-III scores assigned by movement disorder specialists. Analysis of the relative contributions of each of the eight metrics showed a significant difference between the motor dysfunction of PD and ET. Much of this difference was attributable to the homogenous, tremor-dominant phenotype of ET motor dysfunction. Finally, in individual patients with PD with DBS, task performance and subsequent SVM classification effectively differentiated between the ‘DBSOn’ and ‘DBSOff’ stimulation states. CONCLUSION: The tablet-based task correlated strongly with the MDS-UPDRS-III. Additionally, the task showed specificity for PD when compared to ET, another common movement disorder. Finally, the task was able to distinguish between the ‘DBSOn’ and ‘DBSOff’ states within single patients with PD. This task provides temporally-precise and specific information about motor dysfunction in two movement disorders that could feasibly correlate to neural activity.