Integrating Wearable Sensor Signal Processing with Unsupervised Learning Methods for Tremor Classification in Parkinson’s Disease

Integrating Wearable Sensor Signal Processing with Unsupervised Learning Methods for Tremor Classification in Parkinson’s Disease

Tremor is one of the most common symptoms of Parkinson’s disease (PD), assessed using clinician-assigned clinical scales, which can be subjective and prone to variability. This study evaluates the potential of unsupervised learning for the classification and assessment of tremor severity from wearab...

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Bibliographic Details
Main Authors: Serena Dattola, Augusto Ielo, Angelo Quartarone, Maria Cristina De Cola
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Bioengineering
Subjects:
unsupervised learning
tremor detection
Parkinson’s disease
wearable sensors
Online Access:https://www.mdpi.com/2306-5354/12/1/37
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