Abstract:
The Brain is the main controller of the human
body consisting of neurons which generate electrical signals to
control the body. Different neurological diseases can cause
brain abnormalities such as ALS that affect the electrical
activity of the brain which can be seen in the EEG signal.
Therefore, these abnormalities can be detected by analyzing
the EEG signal. As the Alpha and Beta waves are recorded
during the active state of the brain, the effect of abnormalities
can be seen in the waves. This study proposes a technique to
detect the brain abnormalities and detect ALS syndromes
based on Alpha and Beta waves. In this study, the Alpha and
Beta waves are extracted from the raw EEG signal by discrete
wavelet transformation. Here, the raw EEG signal is divided
into several orthogonal wavelets using Doubechis 4 wavelet
transform; Alpha and Beta wave frequency components are
selected and reconstructed. Then these waves can be compared
between different types of ALS patients and normal people
based on amplitude and event related potential. The result
showed great variation in amplitude as well as event related
potential for different ALS patients and normal people. The
proposed technique could be used in detecting abnormalities
and their severity. It could also help in detecting ALS at a
primary stage.
