Objective Assessment and Scoring of Parkinsonian Tremors using Wrist Sensor Technology

Abstract

Background: Parkinson’s Disease (PD) is the second leading cause of neurodegenerative disease in humans. The gold standard for assessing disease progression is the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Neurologists score motor symptoms from 0-4 and determine medication adjustments based on score variation between the OFF and ON medication states. Numerous studies have noted inter-rater variability due to the subjectivity of the visual-based MDS-UPDRS rating scale complicating treatment plans. Objective: This clinical study evaluated the use of wrist-worn inertial sensors as a more objective and reliable method for measuring the severity of Parkinsonian rest and postural tremors, in comparison to the current gold standard, the MDS-UPDRS. Methods: 30 PD patients and 30 age-matched healthy controls performed the rest and postural tasks. Shimmer3 IMU sensors, sampling at 100Hz, were attached to both wrists to record angular velocity and linear acceleration. Tremor Severity Score (TSS), a novel objective tremor scoring algorithm based on sensor signals, was developed to measure tremor severity. Results: In a subset of controls and PD patients tested only ON medication, the mean scores for rest and postural tremor showed significant differences using both MDS-UPDRS (0.53 vs 0.46) and TSS (0.53 vs 0.39) rating scales, with TSS showing a marginally greater effect size (0.07 vs 0.06). When comparing OFF/ON states in a subset of 7 PD patients, the MDS-UPDRS showed no significant difference between scores, while the TSS showed significantly lower scores in the ON vs OFF state for both postural (0.44 vs 1.1) and rest tremor (0.91 vs 1.97). Conclusion: Results suggest TSS is more sensitive to changes in tasks (rest, postural) and medication effects (OFF vs ON). The ability to more objectively assess tremor severity and progression has implications for early diagnosis, medication dose adjustments, and more accurate assessment of patients in the telehealth setting.