A Detection Method for Parkinson’s Hand Tremor Based on Machine Learning

Parkinson’s disease (PD) is a common neurode-generative disease, which threatens people’s health seriously. Advanced artificial intelligence methods such as machine learning provide a new way for the diagnosis of PD, so it has become a hot topic of concern. This paper proposes a method to expand the hand tremor data set by Generative Adversarial Networks (GAN), extracts the characteristics of tremor data by Discrete Wavelet Transform-Singular Value Decomposition (DWT-SVD), and finally utilizes multiple classification by Support Vector Machine (SVM) to realize the detection of Parkinson’s disease.