Implementation of Schizophrenia Diagnosis with EEG Signal using Stationary Wavelet Transform and Linear Wavelet Transform Algorithm

The aim of the study is to compare accuracy in Stationary wavelet transform and linear Wavelet Transform to diagnose schizophrenia using EEG signals. Material and methods: The research study consists of two groups. Sample group 1 and sample group 2 consist of 253 samples each. The T-test power of this study is kept at 80 %Result: From the study, it is observed that stationary wavelet transform (SWT) has better accuracy when compared to linear wavelet transform (LWT). Schizophrenia diagnosis using stationary wavelet transform (SWT) has a higher accuracy of 95 % than the linear wavelet transform (86 %). The independent sample test reveals t the difference between the groups is considerable. 0.001 (p i 0.05). Conclusion: The study shows that the SWT algorithm has better accuracy than that of the LWT algorithm.