Luisa Drescher: Correlation of Subjective and Objective Measures in Naturalistic Multumodal Monitoring of Motor Fluctuations in Parkinson’s Disease

BCCN Berlin / Technische Universität Berlin

Abstract

Rationale: Parkinson’s disease (PD) is a neurodegenerative movement disorder often characterized by fluctuations in symptom severity. These fluctuations are not fully captured by current clinical examination practices, as these assessments are typically infrequent, conducted in clinical settings, or reliant on biased retrospective self-reports. Continuous monitoring of symptom severity in patients’ natural environments is crucial for personalized treatment and effective disease management. This study explored the relationship between wearable sensor-derived objective features and patient-reported symptom ratings during daily life, focusing on motor symptoms, to evaluate the potential of these features for predicting symptom severity in home monitoring.

Methods: Data were collected from five patients with idiopathic PD over a two-week period. Patients wore a wrist-worn sensor and completed ecological momentary assessments (EMA) throughout the day to record the self-rated symptom severity. Objective motor features, namely maximum acceleration (maxAcc), coefficient of variation of acceleration over time (COV), root mean square of acceleration over time (RMS), and spectral power below 4Hz (SPow), were related to the subjective symptom ratings at both the individual and group level using linear mixed models.

Results: This initial data set indicated moderate trends between subjective and objective measures, with feature-specific variations. In three out of four patients, maxAcc, RMS, and SPow showed positive trends, indicating that higher values of these features are associated with improved motor function and reduced symptom severity. In contrast, the relationship between COV and motor function was more variable, with some patients exhibiting positive trends and others negative. One patient with severe dyskinesia showed a unique symptom profile within the study population, leading to negative trends and differing from the other participants, which emphasizes the need to tailor monitoring approaches to individual symptom profiles. Significant positive correlations were observed in a subgroup of patients with similar symptom profiles between the features maxAcc, RMS, and SPow, and movement performance respectively.

Conclusion: These findings highlight the potential of wearable sensors and EMA to enhance home monitoring and support personalized care strategies in PD. Future research should aim to refine objective measures for more accurate tracking of symptom fluctuations and disease progression. Additionally, understanding and accounting for variations across patient subgroups with distinct symptom profiles will be crucial for more targeted monitoring.

 

Additional information:

Master thesis defense

 

Organized by:

Prof. Dr. med. Andrea A. Kühn & Prof. Dr. med. Wolf-Julian Neumann