The Effect Of Power Spectral Density On The Electroencephalography Of Autistic Children Based On The Welch Periodogram Method

Autism spectrum disorder is a serious mental disorder affecting social behavior. Some children also faceintellectual delay. In people with autism spectrum disorder, the signals detected have abnormalities compared to normalpeople. This can be a reference in diagnosing the disorder with electroencephalography. This study will analyze the effect ofpower spectral density on the electroencephalography of autistic children and also compare it with the power spectral densityvalue on the electroencephalography of normal children using the Welch periodogram method approach. In the preprocessingstage, the independent component analysis method will be applied to remove artifacts, and a finite impulse response filter toreduce noise in the electroencephalography signal. The study results indicate differences in the power spectral density valuesobtained in the autistic and normal electroencephalography signals. The power spectral density value obtained in the autisticelectroencephalography signal is higher than the normal electroencephalography signal in all frequency sub-bands. From thestudy results, the highest power spectral density value obtained by the autistic electroencephalography signal is in the deltasub-band, which is 54.06 dB/Hz, while the normal electroencephalography signal is only 33.14 dB/Hz at the same frequencysub-band. And in the Alpha and Beta sub-bands, the normal electroencephalography signal increases the power spectraldensity value, while in the autistic electroencephalography signal, the power spectral density value decreases in the Alphaand Beta sub-bands. In addition, finite impulse response and independent component analysis methods can also reduce noiseand artifacts contained in autistic and normal electroencephalography signals