Prediction of Disorder of Brain using EEG Signal Processing in MATLAB GUI Platform

Mukherjee, Ratri; Dhar, Shemul Sutra; Tara, Kusum

doi:10.1109/ceee.2017.8412847

Cited by 2 publications

(4 citation statements)

References 12 publications

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“…After obtaining the PSD value in the Delta, Theta, Alpha, and Beta frequency sub-bands on all normal EEG signals and autistic EEG signals, it can be said that the PSD value obtained on the autistic EEG signal is higher than the normal EEG signal as a whole in the frequency range 0 Hz to 30 Hz, this is following what was obtained in previous studies [6], that the PSD value in subjects affected by brain disorders has a higher PSD value compared to normal subjects. What distinguishes this study from the previous study [6] is that in the previous study, the PSD value obtained was the PSD value in people with brain disorders in general. Whereas this study only focuses on autistic people.…”

Section: Discussionsupporting

confidence: 84%

“…This study analyzes the PSD value in each frequency sub-band (Delta, Theta, Alpha, and Beta). Unlike the previous study [6], the PSD value is analyzed only in general. It can be seen from the study results that the Delta frequency sub-band has the highest PSD value of the other frequency sub-bands both in normal EEG signals and in autistic EEG signals.…”

Section: Discussionmentioning

confidence: 99%

“…And the results of the PSD parameters of the two signals will be analyzed for differences. The PSD parameter of the EEG signal needs to be analyzed because, in previous studies, it was explained that subjects with brain disorders had higher PSD values than normal subjects [6]. So that there is a difference between the PSD value of a normal EEG signal and an EEG signal that has abnormalities in brain activity, one of which is in people with autism.…”

Section: Introductionmentioning

confidence: 99%

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The effect of power spectral density on the electroencephalography of autistic children based on the welch periodogram method

et al. 2023

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Autism spectrum disorder (ASD) is a serious mental disorder affecting social behavior. Some children also face intellectual delay. In people with ASD, the signals detected have abnormalities compared to normal people. This can be a reference in diagnosing the disorder with electroencephalography (EEG). This study will analyze the effect of Power spectral density (PSD) on the EEG of autistic children and also compare it with the PSD value on the EEG of normal children using the Welch Periodogram method approach. In the preprocessing stage, the Independent Component Analysis (ICA) method will be applied to remove artifacts, and a Finite Impulse Response (FIR) filter to reduce noise in the EEG signal. The study results indicate differences in the PSD values obtained in the autistic and normal EEG signals. The PSD value obtained in the autistic EEG signal is higher than the normal EEG signal in all frequency sub-bands. From the study results, the highest PSD value obtained by the autistic EEG signal is in the delta sub-band, which is 54.06 dB/Hz, while the normal EEG signal is only 33.14 dB/Hz at the same frequency sub-band. And in the Alpha and Beta sub-bands, the normal EEG signal increases the PSD value, while in the autistic EEG signal, the PSD value decreases in the Alpha and Beta sub-bands. In addition, FIR and ICA methods can also reduce noise and artifacts contained in autistic and normal EEG signals.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The effect of power spectral density on the electroencephalography of autistic children based on the welch periodogram method

et al. 2023

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“…These postsynaptic potentials summate in the cortex and reach surface of the scalp where they are recorded as EEG [2]. The EEG signals can be recorded by placing electrodes on a patient's head region at the scalp [3]. Hence, they can be used non-invasively to detect brain function as well as disorders such as head injury, brain tumor, memory problems, stroke, encephalitis,…”

Section: Introductionmentioning

confidence: 99%

Secure EEG Signal Transmission for Remote Health Monitoring Using Optical Chaos

et al. 2019

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For the very first time, we present the use of optical chaos for the secure transmission of electroencephalogram (EEG) signals through optical fiber medium in remote health monitoring systems. In our proposed scheme, a semiconductor laser source is used to generate optical chaos, which hides EEG signal before its transmission over the optical fiber medium. The EEG signals are acquired by using a 14channel Emotiv headset device, which are then processed and rescaled to be compatible with the experimental environment (Optisystem). The mixing of EEG signals and chaos is performed using additive chaos masking scheme, which exhibits certain useful properties such as simplicity and easy recovery of the message. Chaotic data (a combination of EEG signals and chaos) is sent over the optical fiber medium to investigate propagation issues associated with secure EEG signal transmission. The scheme is implemented for long haul communication in which the linear impairments of optical fiber are controlled for successful transmission of the secure signal. The parameters at transmitting and receiving sides are selected to achieve synchronization, such that the transmitted signal could be subtracted from identical chaos to restore the original EEG signal at the receiving side. The scheme is tested for different lengths of the optical fiber cable in which the quality of the received signal is determined by obtaining Q-factors. This scheme could also be used with medical signals such as electrocardiography and electromyography.INDEX TERMS EEG signal, Emotiv, semiconductor laser, optical chaos, additive chaos masking, synchronization, remote health monitoring, long haul.

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Prediction of Disorder of Brain using EEG Signal Processing in MATLAB GUI Platform

Cited by 2 publications

References 12 publications

The effect of power spectral density on the electroencephalography of autistic children based on the welch periodogram method

The effect of power spectral density on the electroencephalography of autistic children based on the welch periodogram method

Secure EEG Signal Transmission for Remote Health Monitoring Using Optical Chaos

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