"Dataset for Automated Parkinson\u2019s Disease Detection Using High-Precision Spiral Drawing Features and ML Algorithms"

"Parkinson\u2019s disease (PD) is a progressive neurodegenerative disorder that significantly impairs motor functions, including handwriting and spiral drawing. Traditional diagnostic methods rely on subjective clinical assessments, which are often time-consuming, costly, and require specialized expertise. This study proposes a machine learning-based approach to analyze spirograph drawings for early and objective PD detection. Using a dataset of 130 PD patients and 60 healthy controls, kinematic and dynamic features such as pressure, speed, acceleration, and directional variability were extracted from digital spiral drawings collected via an iPad and Apple Pencil. Four machine learning models (Support Vector Machine, Random Forest, XGBoost, and AdaBoost) were evaluated for classification performance. "