The Measurement of Anesthesia Depth Using Biomedical Signal during General Anesthesia

2013 ◽  
Vol 479-480 ◽  
pp. 468-474
Author(s):  
Byeong Cheol Choi ◽  
Soo Young Ye ◽  
Sung Jae Kim ◽  
Sung Min Kim
Keyword(s):  
Brain Function ◽  
Specific Area ◽  
Simple Method ◽  
Biomedical Signal ◽  
Rr Intervals ◽  
Anesthetic Depth ◽  
Density Peaks ◽  
Spectrum Density ◽  
2D Fft ◽  
Anesthesia Depth

The measurement of anesthetic depth is necessary in anesthesiology. NN10 is very simple method among the RR intervals analysis methods. NN10 parameter means the numbers of above the 10 ms intervals of the normal to normal RR intervals. Bispectrum analysis is defined as 2D FFT. EEG signal reflected the non-linear peristalsis phenomena according to the change brain function. After analyzing the bispectrum of the 2 dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake.In this paper, the relation between NN10 parameter using ECG and bisepctrum index using EEG is observed to estimate the depth of anesthesia during anesthesia and then we estimated the utility of the anesthetic.

scholarly journals Power spectrum density analysis for the influence of complete denture on the brain function of edentulous patients - pilot study

2016 ◽  
Vol 8 (3) ◽  
pp. 187
Author(s):  
Praveen Perumal ◽  
Gopi Naveen Chander ◽  
Kuttae Viswanathan Anitha ◽  
Jetti Ramesh Reddy ◽  
Balasubramanium Muthukumar
Keyword(s):  
Pilot Study ◽  
Power Spectrum ◽  
Brain Function ◽  
Power Spectrum Density ◽  
Complete Denture ◽  
Spectrum Density ◽  
Density Analysis ◽  
Edentulous Patients ◽  
The Brain

scholarly journals A Predictive Model of Anesthesia Depth Based on SVM in the Primary Visual Cortex

2013 ◽  
Vol 7 (1) ◽  
pp. 71-80 ◽  
Author(s):  
Li Shi ◽  
Xiaoyuan Li ◽  
Hong Wan
Keyword(s):  
Visual Cortex ◽  
Predictive Model ◽  
Primary Visual Cortex ◽  
Complexity Analysis ◽  
Support Vector ◽  
Field Potentials ◽  
Anesthetic Depth ◽  
Precise Analysis ◽  
Novel Model ◽  
Anesthesia Depth

In this paper, a novel model for predicting anesthesia depth is put forward based on local field potentials (LFPs) in the primary visual cortex (V1 area) of rats. The model is constructed using a Support Vector Machine (SVM) to realize anesthesia depth online prediction and classification. The raw LFP signal was first decomposed into some special scaling components. Among these components, those containing higher frequency information were well suited for more precise analysis of the performance of the anesthetic depth by wavelet transform. Secondly, the characteristics of anesthetized states were extracted by complexity analysis. In addition, two frequency domain parameters were selected. The above extracted features were used as the input vector of the predicting model. Finally, we collected the anesthesia samples from the LFP recordings under the visual stimulus experiments of Long Evans rats. Our results indicate that the predictive model is accurate and computationally fast, and that it is also well suited for online predicting.

scholarly journals Anesthesia Depth–dependent Features of Electroencephalographic Bicoherence Spectrum during Sevoflurane Anesthesia

2008 ◽  
Vol 108 (5) ◽  
pp. 841-850 ◽  
Author(s):  
Kazuko Hayashi ◽  
Teiji Sawa ◽  
Megumi Matsuura
Keyword(s):  
Growth Pattern ◽  
Sevoflurane Anesthesia ◽  
Anesthetic Depth ◽  
Double Frequency ◽  
Diagonal Line ◽  
Key Factor ◽  
Electroencephalographic Signals ◽  
High Concentrations ◽  
Anesthesia Depth ◽  
40 Hz

Background Growth pattern in the electroencephalographic bicoherence spectrum has recently been found to relate to anesthetic depth, and bicoherence analysis can reflect behavior of the thalamocortical reverberating network. Because the thalamocortical network is known to represent a key factor in sleep by anesthesia, systematic and qualitative bicoherence studies of different anesthetic depths is necessary throughout all pairs of frequencies. Methods Sixteen patients were anesthetized using sevoflurane (1, 2, or 3%) combined with remifentanil (0.4 microg x kg x min). Raw electroencephalographic signals were collected, and bicoherence was estimated in all pairs of frequencies, between 0.5 and 40 Hz at 0.5-Hz intervals. Results Sevoflurane (1%) caused two main peaks, spindle frequencies (11.0 +/- 1.2 Hz, 44.7 +/- 12.3% [bicoherence growth]) and delta-theta frequencies (5.4 +/- 0.5 Hz, 33.0 +/- 8.4%), in the diagonal line of biphasic bicoherence plots. High concentrations of sevoflurane (2% and 3%) shifted these peaks to 9.8 +/- 1.1 Hz, 46.2 +/- 12.7%; 8.7 +/- 1.3 Hz, 37.2 +/- 13.7% and 4.9 +/- 0.5 Hz, 44.6 +/- 7.0%; 4.3 +/- 0.8 Hz, 45.2 +/- 10.6%, respectively. Sevoflurane caused a third bicoherence peak to appear in another heterogeneous pair frequency (pair of alpha basal frequency and its double frequency), outside the diagonal line, which also inherited the behavior of alpha bicoherence peaks at different anesthetic depths. Conclusions Sevoflurane anesthesia caused bicoherence peaks in alpha and delta-theta areas and also formed secondary third peaks. Deeper sevoflurane anesthesia shifted all bicoherence peaks to lower frequencies and caused increased bicoherence growth in the delta-theta area. The obtained features are consistent with characteristics of the thalamocortical reverberating network and suggest the importance of bicoherence analysis for the thalamic system.

scholarly journals Simultaneous comparison of depth of sedation performance between SedLine and BIS during general anesthesia using custom passive interface hardware: study protocol for a prospective, non-blinded, non-randomized trial

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
James Harvey Jones ◽  
Vinay Ravikumar Nittur ◽  
Neal Fleming ◽  
Richard L. Applegate
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
General Anesthesia ◽  
Brain Function ◽  
Anesthesia Induction ◽  
Anesthetic Depth ◽  
Clinical Assessments ◽  
Link Type ◽  
Processed Eeg ◽  
Brain Function Monitoring

Abstract Background Intraoperative brain function monitoring with processed electroencephalogram (EEG) indices, such as the bispectral index (BIS) and patient state index (PSI), may improve characterization of the depth of sedation or anesthesia when compared to conventional physiologic monitors, such as heart rate and blood pressure. However, the clinical assessment of anesthetic depth may not always agree with available processed EEG indices. To concurrently compare the performance of BIS and SedLine monitors, we present a data collection system using shared individual generic sensors connected to a custom-built passive interface box. Methods This prospective, non-blinded, non-randomized study will enroll 100 adult American Society of Anesthesiologists (ASA) class I-III patients presenting for elective procedures requiring general anesthesia. BIS and SedLine electrodes will be placed preoperatively according to manufacturer recommendations and their respective indices tracked throughout anesthesia induction, maintenance and emergence. The concordance between processed EEG indices and clinical assessments of anesthesia depth will be analyzed with chi-square and kappa statistic. Discussion Prior studies comparing brain function monitoring devices have applied both sensors on the forehead of study subjects simultaneously. With limited space and common sensor locations between devices, it is not possible to place both commercial sensor arrays according to the manufacturer’s recommendations, thus compromising the validity of these comparisons. This trial utilizes a custom interface allowing signals from sensors to be shared between BIS and SedLine monitors to provide an accurate comparison. Our results will also characterize the degree of agreement between processed EEG indices and clinical assessments of anesthetic depth as determined by the anesthesiologists’ interpretations of acute changes in blood pressure and heart rate as well as the administration, or change to the continuous delivery, of medications at these timepoints. Patient factors (such as burst suppression state or low power EEG conditions from aging brain), surgical conditions (such as use of electrocautery), artifacts (such as electromyography), and anesthesia medications and doses (such as end-tidal concentration of volatile anesthetic or hypnotic infusion dose) that lead to lack of agreement will be explored as well. Trial registration Clinical Trials (ClinicalTrials.gov), NCT03865316. Registered on 4 February 2019 – retrospectively registered. Sponsor: Masimo Corporation.

A Simple Method to Detect Atrial Fibrillation Using RR Intervals

2011 ◽  
Vol 107 (10) ◽  
pp. 1494-1497 ◽  
Author(s):  
Jie Lian ◽  
Lian Wang ◽  
Dirk Muessig
Keyword(s):  
Atrial Fibrillation ◽  
Simple Method ◽  
Rr Intervals

scholarly journals Heavy-Tailed Prediction Error: A Difficulty in Predicting Biomedical Signals of1/fNoise Type

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Ming Li ◽  
Wei Zhao ◽  
Biao Chen
Keyword(s):  
Long Range ◽  
Prediction Error ◽  
Power Spectrum Density ◽  
Biomedical Signal ◽  
Biomedical Signals ◽  
Noise Type ◽  
Spectrum Density ◽  
Fractal Signal ◽  
Heavy Tailed ◽  
Probability Density Function Pdf

A fractal signalx(t)in biomedical engineering may be characterized by1/fnoise, that is, the power spectrum density (PSD) divergences atf=0. According the Taqqu’s law,1/fnoise has the properties of long-range dependence and heavy-tailed probability density function (PDF). The contribution of this paper is to exhibit that the prediction error of a biomedical signal of1/fnoise type is long-range dependent (LRD). Thus, it is heavy-tailed and of1/fnoise. Consequently, the variance of the prediction error is usually large or may not exist, making predicting biomedical signals of1/fnoise type difficult.

A challenge for predictive coding: Representational or experiential diversity?

2020 ◽  
Vol 43 ◽  
Author(s):  
Martina G. Vilas ◽  
Lucia Melloni
Keyword(s):  
Brain Function ◽  
Predictive Coding ◽  
Predictive Processing ◽  
Process Theory

Abstract To become a unifying theory of brain function, predictive processing (PP) must accommodate its rich representational diversity. Gilead et al. claim such diversity requires a multi-process theory, and thus is out of reach for PP, which postulates a universal canonical computation. We contend this argument and instead propose that PP fails to account for the experiential level of representations.

A simple way for producing holographic filters suitable for image improvement

1978 ◽  
Vol 36 (1) ◽  
pp. 226-227
Author(s):  
K.-H. Herrmann ◽  
E. Reuber ◽  
P. Schiske
Keyword(s):  
Transfer Functions ◽  
Diffraction Order ◽  
Lateral Position ◽  
Simple Method ◽  
Spatial Frequencies ◽  
Resolution Electron ◽  
Wiener Filters ◽  
Image Improvement ◽  
Optical Reconstruction ◽  
Set Up

Aposteriori deblurring of high resolution electron micrographs of weak phase objects can be performed by holographic filters [1,2] which are arranged in the Fourier domain of a light-optical reconstruction set-up. According to the diffraction efficiency and the lateral position of the grating structure, the filters permit adjustment of the amplitudes and phases of the spatial frequencies in the image which is obtained in the first diffraction order.In the case of bright field imaging with axial illumination, the Contrast Transfer Functions (CTF) are oscillating, but real. For different imageforming conditions and several signal-to-noise ratios an extensive set of Wiener-filters should be available. A simple method of producing such filters by only photographic and mechanical means will be described here.A transparent master grating with 6.25 lines/mm and 160 mm diameter was produced by a high precision computer plotter. It is photographed through a rotating mask, plotted by a standard plotter.

Rotary Beveling for In Situ Thin-Section Microscopy of Cell Cultures

1981 ◽  
Vol 39 ◽  
pp. 550-551
Author(s):  
Dean A. Handley ◽  
Jack T. Alexander ◽  
Shu Chien
Keyword(s):  
Cell Growth ◽  
Cell Cultures ◽  
Molecular Interactions ◽  
Convenient Method ◽  
Petri Dish ◽  
Simple Method ◽  
Thin Section Microscopy ◽  
Thin Sectioning ◽  
Organic Fluids

In situ preparation of cell cultures for ultrastructural investigations is a convenient method by which fixation, dehydration and embedment are carried out in the culture petri dish. The in situ method offers the advantage of preserving the native orientation of cell-cell interactions, junctional regions and overlapping configurations. In order to section after embedment, the petri dish is usually separated from the polymerized resin by either differential cryo-contraction or solvation in organic fluids. The remaining resin block must be re-embedded before sectioning. Although removal of the petri dish may not disrupt the native cellular geometry, it does sacrifice what is now recognized as an important characteristic of cell growth: cell-substratum molecular interactions. To preserve the topographic cell-substratum relationship, we developed a simple method of tapered rotary beveling to reduce the petri dish thickness to a dimension suitable for direct thin sectioning.

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