Offline LabVIEW-Based EEG Signals Analysis to Detect Vehicle Driver Microsleep

Sulaiman, Norizam; Goh, King-Shy; Rashid, Mamunur; Jadin, S.; Mustafa, Mahfuzah; Ibrahim, M. Z.; Samsuri, Fahmi

doi:10.1007/978-981-15-3270-2_29

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…The Standard Deviation is a statistical feature that reveals how the data is distributed in relation to the mean [37]. According to (5) shows the formula for calculating SD.…”

Section: B Standard Deviation (Sd)mentioning

confidence: 99%

Brain signals analysis for sleep stages detection using virtual instrumentation platform

Hadiri

Bahatti²,

Magri³

et al. 2023

IJEECS

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This paper discusses the use of the Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) software tool for analyzing brain waveforms (i.e EEG: electroencephalogram) to study sleep stages such as deep sleep, light sleep and so on. The used EEG signals are generated in order to span all sleeping phases. Indeed, a mandatory step of signal processing has been performed, such as sampling, filtering and features extraction. This analysis is carried out with the LabVIEW program, which is a popular virtual instrumentation platform. The EEG signals used in the analysis were obtained from an open-source database and went through several steps, including noise removal, classification and feature extraction. To extract the feature, different filters are employed and the outputs of all filters are compared, leading to a sleep level detection. The simulation results show clearly the performances of this analysis.

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“…The Standard Deviation is a statistical feature that reveals how the data is distributed in relation to the mean [37]. According to (5) shows the formula for calculating SD.…”

Section: B Standard Deviation (Sd)mentioning

confidence: 99%

Brain signals analysis for sleep stages detection using virtual instrumentation platform

Hadiri

Bahatti²,

Magri³

et al. 2023

IJEECS

View full text Add to dashboard Cite

show abstract

“…The classification of EEG signals is based on their frequency, ranging from 0 to 100 Hz. EEG signals can also be categorized based on their amplitude, and be recognized based on their shape as illustrated in Table 1 [37][38]. 2 presents a summary of recent EEG devices commonly used in BCI applications.…”

Section: Electroencephalography (Eeg)mentioning

confidence: 99%

Brain Computer Interfaces: The Future of Communication Between the Brain and the External World

ALMofleh,

Alseddiqi,

Najam

et al. 2023

Sci. Eng. Technol.

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This paper provides a comprehensive review of the current state of research on Brain Computer Interfaces (BCIs) and their potential applications. The objective of this study was to gather information from various sources, including journal articles, conference papers, and books, to analyze the advancements and limitations of BCIs. A systematic literature review was conducted using databases such as PubMed, IEEE Xplore, and Google Scholar, with specific keywords related to BCIs and their applications. The selected studies were thoroughly analyzed to identify common themes, methodologies, and key findings. The main contributions of this review include an overview of different types of BCIs, their applications in fields such as medicine, entertainment, and education, and the challenges and limitations faced by BCI technology. The findings highlight the potential of BCIs in restoring motor function, improving the quality of life for individuals with various conditions, and enhancing human-technology interaction. Furthermore, the review identifies future research directions, including signal processing improvements, exploring hybrid and multimodal approaches, conducting long-term real-world studies, addressing ethical considerations, and prioritizing user-centred design. This comprehensive analysis of existing literature provides valuable insights for researchers and practitioners in the field of BCIs and sets the stage for future advancements in this rapidly evolving domain.

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Drugs Acting on Central Nervous System

Chakraborty,

Das

2024

Essentials of Pharmacodynamics and Drug Action

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Offline LabVIEW-Based EEG Signals Analysis to Detect Vehicle Driver Microsleep

Cited by 6 publications

References 9 publications

Brain signals analysis for sleep stages detection using virtual instrumentation platform

Brain signals analysis for sleep stages detection using virtual instrumentation platform

Brain Computer Interfaces: The Future of Communication Between the Brain and the External World

Drugs Acting on Central Nervous System

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