Performance of the bispectral index and electroencephalograph derived parameters of anesthetic depth during emergence from xenon and sevoflurane anesthesia.

Many processed EEG monitors (pEEG) are unreliable when non-GABAergic anesthetic agents are used. The primary aim of the study was to compare the response of the Bispectral Index (BIS) during emergence from anesthesia maintained by xenon and sevoflurane. To better understand the variation in response of pEEG to these agents, we also compared several EEG derived parameters relevant to pEEG monitoring during emergence. Twenty-four participants scheduled for lithotripsy were randomized to receive xenon or sevoflurane anesthesia. Participants were monitored with the BIS and had simultaneous raw EEG collected. BIS index values were compared at three key emergence timepoints: first response, eyes open and removal of airway. Two sets of EEG derived parameters, three related to the BIS: relative beta ratio, SynchFastSlow and SynchFastSlow biocoherence, and two unrelated to the BIS: spectral edge frequency and the composite cortical state, were calculated for comparison. BIS index values were significantly lower in the xenon group than the sevoflurane group at each emergence timepoint. The relative beta ratio parameter increased significantly during emergence in the sevoflurane group but not in the xenon group. The spectral edge frequency and composite cortical state parameters increased significantly in both groups during emergence. The BIS index is lower at equivalent stages of behavioural response during emergence from xenon anesthesia when compared to sevoflurane anesthesia, most likely due to differences in how these two agents influence the relative beta ratio. The spectral edge frequency and composite cortical state might better reflect emergence from xenon anaesthesia.Clinical trial number and registry Australia New Zealand Clinical Trials Registry Number: ACTRN12618000916246.

Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea.

Pediatric obstructive sleep apnea (OSA) is a breathing disorder that alters heart rate variability (HRV) dynamics during sleep. HRV in children is commonly assessed through conventional spectral analysis. However, bispectral analysis provides both linearity and stationarity information and has not been applied to the assessment of HRV in pediatric OSA. Here, this work aimed to assess HRV using bispectral analysis in children with OSA for signal characterization and diagnostic purposes in two large pediatric databases (0-13 years). The first database (training set) was composed of 981 overnight ECG recordings obtained during polysomnography. The second database (test set) was a subset of the Childhood Adenotonsillectomy Trial database (757 children). We characterized three bispectral regions based on the classic HRV frequency ranges (very low frequency: 0-0.04 Hz; low frequency: 0.04-0.15 Hz; and high frequency: 0.15-0.40 Hz), as well as three OSA-specific frequency ranges obtained in recent studies (BW1: 0.001-0.005 Hz; BW2: 0.028-0.074 Hz; BWRes: a subject-adaptive respiratory region). In each region, up to 14 bispectral features were computed. The fast correlation-based filter was applied to the features obtained from the classic and OSA-specific regions, showing complementary information regarding OSA alterations in HRV. This information was then used to train multi-layer perceptron (MLP) neural networks aimed at automatically detecting pediatric OSA using three clinically defined severity classifiers. Both classic and OSA-specific MLP models showed high and similar accuracy (Acc) and areas under the receiver operating characteristic curve (AUCs) for moderate (classic regions: Acc = 81.0%, AUC = 0.774; OSA-specific regions: Acc = 81.0%, AUC = 0.791) and severe (classic regions: Acc = 91.7%, AUC = 0.847; OSA-specific regions: Acc = 89.3%, AUC = 0.841) OSA levels. Thus, the current findings highlight the usefulness of bispectral analysis on HRV to characterize and diagnose pediatric OSA.

[EEG Signal Analysis Methods and Their Applications].

EEG is a weak physiological electrical signal, which has important value in clinical and laboratory research. This paper mainly introduces several common methods of EEG signal processing, including power spectrum analysis, time-frequency analysis, bispectral analysis, etc, it mainly introduces their principles and applications in EEG signal processing, and provides methods and approaches for studying EEG.

EEG Signal Analysis Methods and Their Applications / 中国医疗器械杂志

EEG is a weak physiological electrical signal, which has important value in clinical and laboratory research. This paper mainly introduces several common methods of EEG signal processing, including power spectrum analysis, time-frequency analysis, bispectral analysis, etc, it mainly introduces their principles and applications in EEG signal processing, and provides methods and approaches for studying EEG.

Proximal detection of guide wire perforation using feature extraction from bispectral audio signal analysis combined with machine learning.

Artery perforation during a vascular catheterization procedure is a potentially life threatening event. It is of particular importance for the surgeons to be aware of hidden or non-obvious events. To minimize the impact it is crucial for the surgeon to detect such a perforation very early. We propose a novel approach to identify perforations based on the acquisition and analysis of audio signals on the outside proximal end of a guide wire. The signals were acquired using a stethoscope equipped with a microphone and attached to the proximal end of the guide wire via a 3D printed adapter. Bispectral analysis was employed to extract acoustic signatures in the signal and several features were extracted from the bispectrum of the signal. Finally, three machine learning algorithms - K-nearest Neighbor, Support Vector Machine (SVM), and Artificial Neural Network (ANN)- were used to classify a signal as a perforation or as an artifact. The bispectrum-based features resulted in valuable features allowing a perforation to be clearly identifiable from other occurring events. A perforation leaves a clear audio signal trace in the time-frequency domain. The recordings were classified as perforation, friction or guide wire bump using SVM with 97% (polykernel) and 98.62% (RBF) accuracy, k-nearest Neighbor an accuracy of 98.28% and ANN with accuracy of 98.73% was obtained. The presented approach shows that interactions starting at the tip of a guide wire can be picked up at its proximal end providing a valuable additional information that could be used during a guide wire procedure.

Coupling of Blood Pressure and Subarachnoid Space Oscillations at Cardiac Frequency Evoked by Handgrip and Cold Tests: A Bispectral Analysis.

The aim of the study was to assess blood pressure-subarachnoid space (BP-SAS) width coupling properties using time-frequency bispectral analysis based on wavelet transforms during handgrip and cold tests. The experiments were performed on a group of 16 healthy subjects (F/M; 7/9) of the mean age 27.2 ± 6.8 years and body mass index of 23.8 ± 4.1 kg/m2. The sequence of challenges was first handgrip and then cold test. The handgrip challenge consisted of a 2-min strain, indicated by oral communication from the investigator, at 30% of maximum strength. The cold test consisted of 2 min of hand immersion to approximately wrist level in cold water of 4 °C, verified by a digital thermometer. Each test was preceded by 10 min at baseline and was followed by 10-min recovery recordings. BP and SAS were recorded simultaneously. Three 2-min stages of the procedure, baseline, test, and recovery, were analyzed. We found that BP-SAS coupling was present only at cardiac frequency, while at respiratory frequency both oscillators were uncoupled. Handgrip and cold test failed to affect BP-SAS cardiac-respiratory coupling. We showed similar handgrip and cold test cardiac bispectral coupling for individual subjects. Further studies are required to establish whether the observed intersubject variability concerning the BP-SAS coupling at cardiac frequency has any potential clinical predictive value.

Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice.

Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz), the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST). The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i) the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii) the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of considering the effects of the reference choice in the interpretation and comparison of the results of bispectral analysis of scalp EEG.

Evolution of the early Antarctic ice ages.

Understanding the stability of the early Antarctic ice cap in the geological past is of societal interest because present-day atmospheric CO2 concentrations have reached values comparable to those estimated for the Oligocene and the Early Miocene epochs. Here we analyze a new high-resolution deep-sea oxygen isotope (δ18O) record from the South Atlantic Ocean spanning an interval between 30.1 My and 17.1 My ago. The record displays major oscillations in deep-sea temperature and Antarctic ice volume in response to the ∼110-ky eccentricity modulation of precession. Conservative minimum ice volume estimates show that waxing and waning of at least ∼85 to 110% of the volume of the present East Antarctic Ice Sheet is required to explain many of the ∼110-ky cycles. Antarctic ice sheets were typically largest during repeated glacial cycles of the mid-Oligocene (∼28.0 My to ∼26.3 My ago) and across the Oligocene-Miocene Transition (∼23.0 My ago). However, the high-amplitude glacial-interglacial cycles of the mid-Oligocene are highly symmetrical, indicating a more direct response to eccentricity modulation of precession than their Early Miocene counterparts, which are distinctly asymmetrical-indicative of prolonged ice buildup and delayed, but rapid, glacial terminations. We hypothesize that the long-term transition to a warmer climate state with sawtooth-shaped glacial cycles in the Early Miocene was brought about by subsidence and glacial erosion in West Antarctica during the Late Oligocene and/or a change in the variability of atmospheric CO2 levels on astronomical time scales that is not yet captured in existing proxy reconstructions.

The bilateral bispectral and the composite variability indexes during anesthesia for unilateral surgical procedure.

BACKGROUND: The composite variability index (CVI), derived from the bispectral analysis (BIS), has been designed to detect nociception; however, there is no evidence that bilateral BIS and CVI show intrapatient reproducibility or variability. METHODS: We conducted an observational study in patients who underwent for total knee arthroplasty. A BIS Bilateral Sensor was applied and continuously recorded at different points of the anesthesia procedure. Bland-Altman limits of agreement and dispersion for BIS and for CVI were applied. RESULTS: Forty-nine right-handed patients were studied. There were differences between the right and left BIS values after tracheal intubation (which was higher on the right side) and at surgical stimulus (higher on the left side). The maximum BIS and minimum, mean, and maximum CVI scores were higher on the left side for left-side procedures, but there were no differences in any indexes for the right-side procedures. Except for the baseline measurements, both CVI and BIS scores presented high interpatient variability. Although the right to left bias was < 3% for the BIS index, dispersion was large at different stages of the anesthesia. The right to left bias for the CVI was 3.8% at tracheal intubation and 5.7% during surgical stimulus. CONCLUSIONS: Our results indicate that the large interindividual variability of BIS and CVI limits their usefulness. We found differences between the left and right measurements in a right-handed series of patients during surgical stimuli though they were not clinically relevant.

Nonlinear elastic wave tomography for the imaging of corrosion damage.

This paper presents a nonlinear elastic wave tomography method, based on ultrasonic guided waves, for the image of nonlinear signatures in the dynamic response of a damaged isotropic structure. The proposed technique relies on a combination of high order statistics and a radial basis function approach. The bicoherence of ultrasonic waveforms originated by a harmonic excitation was used to characterise the second order nonlinear signature contained in the measured signals due to the presence of surface corrosion. Then, a radial basis function interpolation was employed to achieve an effective visualisation of the damage over the panel using only a limited number of receiver sensors. The robustness of the proposed nonlinear imaging method was experimentally demonstrated on a damaged 2024 aluminium panel, and the nonlinear source location was detected with a high level of accuracy, even with few receiving elements. Compared to five standard ultrasonic imaging methods, this nonlinear tomography technique does not require any baseline with the undamaged structure for the evaluation of the corrosion damage, nor a priori knowledge of the mechanical properties of the specimen.

Sleep Stage Detection Using Tracheal Breathing Sounds: A Pilot Study.

Sleep stage detection is needed in many sleep studies and clinical assessments. Generally, sleep stages are identified using spectral analysis of electrocephologram (EEG) and electrooculogram (EOG) signals. This study, for the first time, has investigated the feasibility of detecting sleep stages using tracheal breathing sounds, and whether the change of breathing sounds due to sleeping stage differs at different periods of sleeping time; the motivation was seeking an alternative technique for sleep stage identification. The tracheal breathing sounds of 12 individuals, who were referred for full overnight polysomnography (PSG) assessment, were recorded using a microphone placed over the suprasternal notch, and analyzed using higher order statistical analysis. Five noise-and-snore-free breathing cycles from wakefulness, REM and Stage II of sleep were selected from each subject for analysis. Data of the REM and Stage II were selected from beginning, middle and close to end of sleeping time. Hurst exponent was calculated from the bispectra of the inspiratory sounds of each subject at each sleeping stage in different periods of sleeping time. The participants' sleep stage were determined by sleep lab technologists during the PSG study using EEG and EOG signals. The results show separate and non-overlapping clusters for wakefulness, REM and Stage II for each subject. Thus, using a simple linear classifier, we were able to classify REM and Stage II of each subject with 100% accuracy. In addition, the results show that the same pattern existed as long as the REM and Stage II segments were close (less than 3 h) to each other in terms of time.

Effects of intravenous procaine on CNS by EEG power spectral analysis and bispectral analysis / 中华麻醉学杂志

Objective: To study the effects ot intravenous 1％ procaine on cortex. Method: Ten patients,aged 29-59 years,for elective surgical operations,were observed the changes of spectral edge frequency(SEF), medium power frequency (MPF)and ? rate(?R)on power spectral analysis and bispectral index(Bl)on bispectral analysis during intravenous propofol 4 mg?kg~(-1)? h~(-1) purely for 15 min,intravenous combination of 1％ procaine 1mg?kg~(-1)?min~(-1) and propofol for 30 min, then intravenous propofol 4mg?kg~(-1)?h~(-1)purely for 15min. Result: SEF,MPF and BI values during combination stage were lower significantly (15.46?1.87Hz, 7.21?2.01Hz, 68.77?7.99 respectively)than the values during other two stages(stage 1 and stage 2 were 21.36?2.79Hz,11.55?2.62Hz,85.6?8.84 and 20.59?3.10Hz, 9.5?3.44Hz, 84.97?8.71 respectively, P

Effects of sevoflurane inhalation in different concentrations on thyroid operation under real-time monitoring of the recurrent laryngeal nerve / 解放军医学杂志

140?V)when the end tidal concentration of sevoflurane increased during the operation.The BIS were between 43-61 when the end tidal concentration of sevuflnrane was lower than 1.0 MAC.The BP and HR in the group decreased(P