Category: Technology
Objective: To investigate how continuous objective information on motor symptoms and treatment response combined with subjective patient reported insights can be used to optimize Parkinson’s disease treatment.
Background: Wearables combined with artificial intelligence allow for the continuous monitoring of motor symptoms and treatment response in patients with Parkinson’s disease (PwP), enabling physicians to optimize treatment. We now have the opportunity to integrate such technology into the clinical workflow to increase efficiency and outcomes.
Method: We report interim results from an observational trial conducted in two outpatient clinics in Singapore. Enrolled PwP receive a wrist-worn sensor during the initial clinical visit. During each of the following two clinical visits (after 2 and 4 months), physicians assess PwP and decide on treatment adjustments. Information on motor symptoms (MDS-UPDRS) and quality of life (PDQ-39) is gathered in addition to the algorithm-derived information.
Results: At the time of analysis, 12 patients (7 male, 5 female) with an average age of 65 (± 7) years and a disease duration of 11 (± 7) years completed the study. In 42% of patients, treatment was adjusted and 86% of the adjustments were influenced by algorithmic insights. We present the case of a patient with troublesome OFF episodes whose treatment timing was altered. In another patient, algorithmic insights enabled the visualization of the reduction in dyskinesia time and severity due to treatment adjustment. The third case presents a patient whose treatment remained unaltered during the course of the study. However, this patient tried to improve symptoms by taking additional medication.
Conclusion: Continuous objective symptom and treatment insights enable better access to care and can help improve treatment decision-making. Combined with subjective patient input, this can further improve communication between healthcare professionals and patients.
To cite this abstract in AMA style:
M. Sander, S. Goh, S. Knapp, F. Pfister, S. Karie, K. Rou, S. Li, N. Jie, V. Zhi, L. Louis, C. Teng, L. Seng, A. Lok, T. Yaw, X. Zheyu, S. Min, M. Anish, P. Manharlal, L. Weishan, A. Ng. Wearable sensors and AI in Parkinson’s disease – How continuous symptom and treatment response monitoring can enable better clinical decision making – Interim results from an observational study [abstract]. Mov Disord. 2024; 39 (suppl 1). https://www.mdsabstracts.org/abstract/wearable-sensors-and-ai-in-parkinsons-disease-how-continuous-symptom-and-treatment-response-monitoring-can-enable-better-clinical-decision-making-interim-results-from-an-observational-stu/. Accessed June 14, 2025.« Back to 2024 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/wearable-sensors-and-ai-in-parkinsons-disease-how-continuous-symptom-and-treatment-response-monitoring-can-enable-better-clinical-decision-making-interim-results-from-an-observational-stu/