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Updated: Mar 18, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Wearable Sensors for Advanced Therapy Referral in Parkinson's Disease
Dustin A Heldman1, Joseph P Giuffrida1, Esther Cubo2
1Great Lakes NeuroTechnologies Inc., Cleveland, OH, USA.
Background:
Advanced therapies, such as deep brain stimulation and levodopa-carbidopa intestinal gel, can significantly improve quality of life in advanced Parkinson's disease (PD). However, determining who should be referred for advanced therapy is a challenging problem.
Objective:
The objective was to determine the impact of remote monitoring using objective, wearable sensors on the advanced therapy referral rate in patients with advanced PD and if sensor data differed in patients who were referred and those who were not.
Methods:
A retrospective, exploratory, secondary analysis was performed on data collected in a study that followed forty individuals with advanced PD for one year with half receiving standard care and half using motion sensor-based remote monitoring once per month in conjunction with standard care. Advanced therapy referral rates were compared between groups. For the group who underwent remote monitoring, objective motor features representing symptoms, dyskinesias, and fluctuations were examined to determine if objective kinematic features differed between patients who were and were not recommended for advanced therapy.
Results:
The advanced therapy referral rate was significantly higher for patients when a clinician had access to remote monitoring reports compared to standard care alone (63.6% versus 11.8%, p < 0.01). Bradykinesia severity, bradykinesia fluctuations, and dyskinesia severity differed significantly (p < 10e-8, p < 10e-5, and p < 0.01, respectively) between patients recommended and not recommended for advanced therapy.
Conclusions:
Remote monitoring technologies can capture motor features that may be clinically useful in identifying patients who may be candidates for advanced therapy. This could lead to development of automated screening algorithms, improve referral efficiency, and expand access to advanced therapies for patients with advanced PD.
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