Electroencephalography Signal Power Spectral Density from Measurements in Room with and Without Faraday Cage: A Comparative Study

Suwandi, Galih Restu Fardian; Khotimah, Siti Nurul; Suprijadi,

doi:10.1088/1742-6596/2243/1/012002

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…To convert a time domain into a frequency domain, signal processing is required to convert the signal. A method that can be used to obtain frequencies is based on spectrum estimation calculations using power spectrum density (PSD) [57][58][59]. PSD is a measure of how strong brain activity is at various frequencies.…”

Section: Eeg Recording and Analysismentioning

confidence: 99%

Investigating the Relationship between Noise Exposure and Human Cognitive Performance: Attention, Stress, and Mental Workload Based on EEG Signals Using Power Spectrum Density

Astuti,

Suhardi,

Laksono

et al. 2024

Applied Sciences

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A pervasive environmental stressor is one that damages mental and physical health as well as cognitive abilities by producing noise at a specific frequency and level. Current noise pollution levels pose a significant threat to public health, potentially leading to impaired cognitive function, increased stress, and other negative health consequences. This study aims to investigate the relationship between noise exposure and human cognitive abilities using a comprehensive analysis of power spectrum density (PSD) derived from EEG signals. Twenty-four participants completed the experiment to identify the effect of exposure to different noise levels (55 dB, 65 dB, 70 dB, 75 dB, 80 dB, and 85 dB) and two types of continuous and intermittent noise. The Stroop Color–Word Test and the Emotive Epoch EEG are cognitive task instruments used during experiments. Behavioral performance (accuracy and response time) and power spectrum electroencephalographic density were collected and analyzed. The methodology involved collecting EEG data from participants exposed to controlled noise stimuli and a subsequent PSD analysis to uncover frequency-specific patterns associated with cognitive processes. Attention levels were measured by examining beta wave activity, while stress responses were evaluated through an alpha wave analysis. Additionally, mental workload was assessed by considering the overall distribution of PSD through the theta-to-alpha ratio. The results revealed a significant relationship between the exposure to noise types and levels and human cognitive ability. The analysis of the power spectrum density on the cognitive aspects of attention and stress yielded results indicating that participants were in the best attention condition and in a relaxed or unstressed state when exposed to noise levels of 65 dB in both continuous and intermittent noise types. For the mental workload aspect, participants exposed to both continuous and intermittent noise types at a noise level of 70 dB began to indicate the presence of mental workload. These findings supported the importance of considering the impact of environmental noise on human cognitive well-being and demonstrated the potential of EEG monitoring as an objective tool for assessing the impact of noise on cognitive performance.

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Section: Eeg Recording and Analysismentioning

confidence: 99%

Investigating the Relationship between Noise Exposure and Human Cognitive Performance: Attention, Stress, and Mental Workload Based on EEG Signals Using Power Spectrum Density

Astuti,

Suhardi,

Laksono

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…This setting is done to avoid signal interference. Measurement space validation has been carried out in previous studies [10,11]. The investigation for consumer-grade EEG was done before the experiment for medical-grade EEG.…”

Section: Data Acquisitionmentioning

confidence: 99%

A Comparative Study of Alpha Frequency Analysis between Medical and Consumer-grade Electroencephalography Devices on the Measurement of Male Healthy Subjects

Suwandi,

Risyad,

Khotimah

et al. 2023

Mal. J. Fund. Appl. Sci.

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The relatively high cost of medical-grade electroencephalography (EEG) devices has pushed the production of low-cost wireless consumer-grade devices. Therefore, it is essential to assess the performance of wireless consumer devices to determine whether they are sufficient for medical purposes. This research assessed consumer-grade EEG (C-EEG) recording quality by quantitatively comparing the consumer-grade EEG with a medical-grade EEG device (M-EEG). Recording data from C-EEG and M-EEG were obtained from 20 male subjects in age 19-23 years old. Recording for both devices was done sequentially with similar methods of recording. Upon EEG recording, the subject is asked to sit in a chair facing the screen. EEG recording was performed when the subject was asked to open and close their eyes for 30 seconds each. Subsequently, subjects took a verbal memory test. This research compared the following parameters: power spectral density (PSD), full width at half max (FWHM) from PSD, and individual peak alpha frequency (IPAF) shift. P-value, standard error, mean absolute percentage error (MAPE) and mean squared error (MSE) were also obtained based on mentioned parameters. Based on the IPAF shift, it was concluded that C-EEG could read EEG signals against time well. Based on PSD and FWHM results, it was concluded that the C-EEG could not read EEG signal amplitudes well compared to the M-EEG device. The results of this research are important as a benchmark for carrying out further research using EEG, both medical and consumer-grade.

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“…Data is acquired in the laboratory with specific settings to minimize noise and artifacts from external electromagnetic fields. The arrangement and testing of the room for data acquisition have been obtained in previous studies [44], [45]. Fig.…”

Section: Data Acquisitionmentioning

confidence: 99%

Electroencephalography Signal Analysis for Virtual Reality Sickness: Head-mounted Display and Screen-based

Suwandi,

Khotimah,

Haryanto

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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The use of virtual reality (VR) technology is growing in the current era of the COVID-19 pandemic. However, the use of VR is causing problems for its users. Some symptoms, such as nausea, headache, and eye strain, are felt after using VR. These symptoms are called VR sickness. This study used electroencephalography (EEG) to record participants' brain activity changes when experiencing VR sickness. Participants are given VR impressions via screens and head-mounted displays (HMD). In addition, the subject also filled out a simulator sickness questionnaire (SSQ) before and after being given a VR. Brain waves in the alpha frequency range (8 Hz-13 Hz) and low beta frequency (13 Hz-21 Hz) were analyzed through the power spectral density (PSD). From the SSQ results, participants who saw VR through the screen experienced increased nausea symptoms. On the other hand, participants who saw VR through HMD experienced an increase in nausea and oculomotor symptoms (p

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Electroencephalography Signal Power Spectral Density from Measurements in Room with and Without Faraday Cage: A Comparative Study

Cited by 5 publications

References 20 publications

Investigating the Relationship between Noise Exposure and Human Cognitive Performance: Attention, Stress, and Mental Workload Based on EEG Signals Using Power Spectrum Density

Investigating the Relationship between Noise Exposure and Human Cognitive Performance: Attention, Stress, and Mental Workload Based on EEG Signals Using Power Spectrum Density

A Comparative Study of Alpha Frequency Analysis between Medical and Consumer-grade Electroencephalography Devices on the Measurement of Male Healthy Subjects

Electroencephalography Signal Analysis for Virtual Reality Sickness: Head-mounted Display and Screen-based

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