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Early Detection of Parkinson Disease Using Wavelet Transform Along with Fourier Transform

  • Syed Qasim Afser Rizvi
  • Guojun WangEmail author
  • Xiaofei Xing
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1122)

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.

Keywords

Parkinson disease (PD) Tremor Patient EEG DWT FFT 

Notes

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 61632009, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006, and in part by the High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01.

This work is supported in part by Guangdong Natural Science Foundation of China under Grant No. 2016A030313540, Guangzhou Science and Technology Program under Grant No. 201707010284.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Computer ScienceGuangzhou UniversityGuangzhouChina

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