Unveiling the Unpredictable in Parkinson’s Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life

Abstract

Background: Dyskinesias and freezing of gait are episodic disorders in Parkinson’s disease, characterized by a fluctuating and unpredictable nature. This cross-sectional study aims to objectively monitor Parkinsonian patients experiencing dyskinesias and/or freezing of gait during activities of daily living and assess possible changes in spatiotemporal gait parameters. Methods: Seventy-one patients with Parkinson’s disease (40 with dyskinesias and 33 with freezing of gait) were continuously monitored at home for a minimum of 5 days using a single wearable sensor. Dedicated machine-learning algorithms were used to categorize patients based on the occurrence of dyskinesias and freezing of gait. Additionally, specific spatiotemporal gait parameters were compared among patients with and without dyskinesias and/or freezing of gait. Results: The wearable sensor algorithms accurately classified patients with and without dyskinesias as well as those with and without freezing of gait based on the recorded dyskinesias and freezing of gait episodes. Standard spatiotemporal gait parameters did not differ significantly between patients with and without dyskinesias or freezing of gait. Both the time spent with dyskinesias and the number of freezing of gait episodes positively correlated with the disease severity and medication dosage. Conclusions: A single inertial wearable sensor shows promise in monitoring complex, episodic movement patterns, such as dyskinesias and freezing of gait, during daily activities. This approach may help implement targeted therapeutic and preventive strategies for Parkinson’s disease.

Motor improvement of remote programming in patients with Parkinson's disease after deep brain stimulation: a 1-year follow-up

“…For physicians, auxiliary technologies such as closed-loop stimulation ( 23 ) and visualization stimulation ( 24 ) are being developed to optimize the workflow. For PwPD, various wearable devices are available to monitor clinical features such as tremors, dyskinesia, and freezing of gait ( 25 – 27 ). Continuous feedback from these devices could help physicians adjust stimulation more suitably to individual daily variations in symptoms and activities.…”

Editorial: High-tech personalized healthcare in movement disorders

“…Technological advances offer new methods for early diagnosis, remote monitoring, tailored treatments, and enhanced rehabilitative strategies, all aimed at addressing individual needs through personalized approaches and increasing patients' quality of life. The opportunity to use these instruments directly at patients' homes allows for further improving therapeutic strategies by gathering ecological data recorded in free-living situations ( 3 ). In this context, new health technologies and computational techniques are promising tools possibly helpful for the overall clinical management of patients with movement disorders.…”