POWER SPECTRAL ANALYSIS OF EEG AS A POTENTIAL MARKER IN THE DIAGNOSIS OF SPASTIC CEREBRAL PALSY CASES

The detection and diagnosis of various neurological disorders are performed using different medical devices among which electroencephalogram (EEG) is one of the most cost effective technique. Though significant progress had been made in the analysis of EEG for diagnosis of different neurological disorders, yet detection of cerebral palsy (CP) is not quite clear. This study was performed to analyze the EEG power spectrum density (PSD) of spastic CP and normal children to find if any significant EEG patterns could be used for early detection of CP. Twenty children participated in this study out of which ten were spastic CP and other ten were normal healthy children. EEG of all the participants was recorded from C3 C4 and F3 F4 regions following montage 10-20 system. The artifact-free EEG signals of 15 minutes duration was extracted for spectral analysis using Fast Fourier Transformation (FFT) algorithm in MATLAB and power density spectrum (PSD) was plotted. The PSD revealed high intensity power peak at frequency of 50Hz and smaller at 100 Hz, which was consistent for all healthy subjects. In case of spastic CP children, high intensity peak at 100Hz were prominent and smaller peak was observed at 50Hz. The high intensity 100Hz peak observed in the PSD of spastic CP patients demonstrated that this tool can be used for early detection of spastic CP.