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To analyze the evolution of machine learning and digital technology in monitoring motor symptoms of Parkinson's disease.

March 18, 2022npj Digital MedicineOpen Access

Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson’s disease motor symptoms

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To analyze the evolution of machine learning and digital technology in monitoring motor symptoms of Parkinson's disease.
Reviewed approximately 12,000 papers from the PubMed database.
Analyzed technological progress from in-lab to in-home monitoring systems.
Examined the development of machine learning algorithms for classifying PD symptoms.
Significant advancements in monitoring technologies over five decades.
Progress from in-lab devices to wearable technologies and mobile applications.
Development of both neural network and non-neural network algorithms to classify tremor, gait, bradykinesia, and dyskinesia.

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Randomized trial demonstrates advancements in monitoring motor symptoms in Parkinson's disease, suggesting improved management.

Chandrabhatla et al. (2022) studied this question.

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