Early detection of parkinson disease using wavelet transform along with fourier transform

Abstract

Parkinson disease (PD) is one of the neurodegenerative diseases caused by numerous factors. The patient is affected by PD grows gradually to the limit that he/she may not be able to perform their daily routine. PD is having two types of major symptoms Motor and Non-motor. Motor symptoms are the major contributor towards the detection of the PD. From the cluster of motor symptoms, Tremor attack is the cause that can depicts the PD by observing the Electroencephalography (EEG). EEG is a rich set of brain signals showing wide variety chronic tasks performed by the brain. The detection of early onset of the PD helps us to investigate that if the patient is having the severe chances of the PD or not. In our propose method we are using the Wavelet Transform along with the Fourier Transform to visualize the EEG signals. Both normal and abnormal EEG’s are tested and the result shows that our propose method is good to classify the early tremor attacks.