TY - JFULL AU - Subha D. Puthankattil and Paul K. Joseph PY - 2014/8/ TI - Analysis of EEG Signals Using Wavelet Entropy and Approximate Entropy: A Case Study on Depression Patients T2 - International Journal of Bioengineering and Life Sciences SP - 429 EP - 434 VL - 8 SN - 1307-6892 UR - https://publications.waset.org/pdf/9999038 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 91, 2014 N2 - Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy. ER -