Theoretical basis for identification of different anesthetic states based on routinely recorded EEG during operation

Nguyen-Ky, Tai; Wen, Peng; Li, Yan

doi:10.1016/j.compbiomed.2008.10.007

Cited by 27 publications

(13 citation statements)

References 21 publications

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“…The method of EEG analysis in this particular study was by thorough and repeated observations of the video and electrical brain activity recorded simultaneously. Although studies of EEG under anesthesia analyze the data using fast Fourier transforms (FFT), 20 EEG is a mixture of various frequency activities, and the predominant frequency activity observed is what defines the state of vigilance in individuals. Even under ideal circumstances, artifacts can alter EEG signal, and thus, quantitative EEG results should be interpreted with caution as numbers given by FFT may not always correlate with the actual event observed in the patient plus artifacts may be overlooked.…”

Section: Discussionmentioning

confidence: 99%

Electrophysiological studies in American Quarter horses with neuroaxonal dystrophy

Finno

Aleman

Ofri

et al. 2012

Veterinary Ophthalmology

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Section: Discussionmentioning

confidence: 99%

Electrophysiological studies in American Quarter horses with neuroaxonal dystrophy

Finno

Aleman

Ofri

et al. 2012

Veterinary Ophthalmology

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“…The discrete Wavelet transform (DWT) was employed for decomposing the EEG signals. The DWT of an EEG signal was defined [24] as…”

Section: Discrete Wavelet Transformmentioning

confidence: 99%

“…Among the many DoA monitoring devices, the Bispectral index (BIS), developed in 1992 by Aspect Medical Systems [21,22], is the most popular. The BIS index was designed using a set of parameters that were derived from different transformation techniques, such as the techniques from time domain and frequency domain [23][24][25][26]. Monitoring the depth of anaesthesia accurately can prevent intraoperative awareness and overdose.…”

Section: Introductionmentioning

confidence: 99%

Robust approach to depth of anaesthesia assessment based on hybrid transform and statistical features

Diykh

Miften

Abdulla

et al. 2020

IET Science, Measurement & Technology

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To develop an accurate and efficient depth of anaesthesia (DoA) assessment technique that could help anaesthesiologists to trace the patient's anaesthetic state during surgery, a new automated DoA approach was proposed. It applied Wavelet-Fourier analysis (WFA) to extract the statistical characteristics from an anaesthetic EEG signal and to designed a new DoA index. In this proposed method, firstly, the wavelet transform was applied to a denoised EEG signal, and a Fast Fourier transform was then applied to the wavelet detail coefficient D3. Ten statistical features were extracted and analysed, and from these, five features were selected for designing a new index for the DoA assessment. Finally, a new DoA () was developed and compared with the most popular Bispectral index (BIS) monitor. The results from the testing set showed that there were very high correlations between the and the BIS index during the awake, light and deep anaesthetic stages. In the case of poor signal quality, the BIS index and the were also tested, and the obtained results demonstrated that the could indicate the DoA values, while the BIS failed to show valid outputs for those situations.. Auto-generated PDF by ReView IET Science, Measurement & Technology IET Submission R evised M ohammed.docxM ainDocument IET Review Copy Only 2 This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication in an issue of the journal. To cite the paper please use the doi provided on the Digital Library page.

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“…Other factors may confound the interpretation of BIS when the anesthesiologists use ketamine and N 2 O, wherein the BIS index may increase or may not change even when the patient is unconscious. This discrepancy is because BIS detects cerebral hypoperfusion, which is concomitant with anesthesia, particularly when combined with ketamine, propofol, and fentanyl [66–68]. Therefore, BIS monitoring devices do not reliably assess the DOA, especially when ketamine–nitrous oxide is used.…”

Section: Anesthetic Agents and Monitoring General Anesthesiamentioning

confidence: 99%

Evolution of Electroencephalogram Signal Analysis Techniques during Anesthesia

Al-Kadi

Reaz

Ali

2013

Sensors

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Biosignal analysis is one of the most important topics that researchers have tried to develop during the last century to understand numerous human diseases. Electroencephalograms (EEGs) are one of the techniques which provides an electrical representation of biosignals that reflect changes in the activity of the human brain. Monitoring the levels of anesthesia is a very important subject, which has been proposed to avoid both patient awareness caused by inadequate dosage of anesthetic drugs and excessive use of anesthesia during surgery. This article reviews the bases of these techniques and their development within the last decades and provides a synopsis of the relevant methodologies and algorithms that are used to analyze EEG signals. In addition, it aims to present some of the physiological background of the EEG signal, developments in EEG signal processing, and the effective methods used to remove various types of noise. This review will hopefully increase efforts to develop methods that use EEG signals for determining and classifying the depth of anesthesia with a high data rate to produce a flexible and reliable detection device.

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Theoretical basis for identification of different anesthetic states based on routinely recorded EEG during operation

Cited by 27 publications

References 21 publications

Electrophysiological studies in American Quarter horses with neuroaxonal dystrophy

Electrophysiological studies in American Quarter horses with neuroaxonal dystrophy

Robust approach to depth of anaesthesia assessment based on hybrid transform and statistical features

Evolution of Electroencephalogram Signal Analysis Techniques during Anesthesia

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