scholarly journals Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Rupert Faltermeier ◽  
Martin A. Proescholdt ◽  
Sylvia Bele ◽  
Alexander Brawanski
Keyword(s):  
Cerebral Perfusion ◽  
Neurocritical Care ◽  
Daily Practice ◽  
Statistical Testing ◽  
Huge Amount ◽  
Time Resolved ◽  
Testing Method ◽  
Arterial Blood ◽  
Windowing Technique ◽  
Statistical Testing Method

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

scholarly journals Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Rupert Faltermeier ◽  
Martin A. Proescholdt ◽  
Sylvia Bele ◽  
Alexander Brawanski
Keyword(s):  
Correlation Analysis ◽  
Cerebral Autoregulation ◽  
High Sensitivity ◽  
Mathematical Tool ◽  
Time Resolved ◽  
Arterial Blood ◽  
Severe Impairment ◽  
Windowing Technique ◽  
Tool Set ◽  
Real Time Application

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

scholarly journals Order Selection in Unsupervised Learning and Clustering for Arbitrary and Non-Arbitrary Shaped Data

2021 ◽  
Author(s):  
Mahdi Shahbaba
Keyword(s):  
Objective Function ◽  
Unsupervised Learning ◽  
Minimum Spanning Tree ◽  
Statistical Testing ◽  
Adjusted Rand Index ◽  
Order Selection ◽  
Clustering Methods ◽  
Conventional Methods ◽  
Anderson Darling ◽  
Statistical Testing Method

This thesis focuses on clustering for the purpose of unsupervised learning. One topic of our interest is on estimating the correct number of clusters (CNC). In conventional clustering approaches, such as X-means, G-means, PG-means and Dip-means, estimating the CNC is a preprocessing step prior to finding the centers and clusters. In another word, the first step estimates the CNC and the second step finds the clusters. Each step having different objective function to minimize. Here, we propose minimum averaged central error (MACE)-means clustering and use one objective function to simultaneously estimate the CNC and provide the cluster centers. We have shown superiority of MACEmeans over the conventional methods in term of estimating the CNC with comparable complexity. In addition, on average MACE-means results in better values for adjusted rand index (ARI) and variation of information (VI). Next topic of our interest is order selection step of the conventional methods which is usually a statistical testing method such as Kolmogrov-Smrinov test, Anderson-Darling test, and Hartigan's Dip test. We propose a new statistical test denoted by Sigtest (signature testing). The conventional statistical testing approaches rely on a particular assumption on the probability distribution of each cluster. Sigtest on the other hand can be used with any prior distribution assumption on the clusters. By replacing the statistical testing of the mentioned conventional approaches with Sigtest, we have shown that the clustering methods are improved in terms of having more accurate CNC as well as ARI and VI. Conventional clustering approaches fail in arbitrary shaped clustering. Our last contribution of the thesis is in arbitrary shaped clustering. The proposed method denoted by minimum Pathways is Arbitrary Shaped (minPAS) clustering is proposed based on a unique minimum spanning tree structure of the data. Our simulation results show advantage of minPAS over the state-of-the-art arbitrary shaped clustering methods such as DBSCAN and Affinity Propagation in terms of accuracy, ARI and VI indexes.

scholarly journals The effect of selective cerebral perfusion on cerebral versus somatic tissue oxygenation during aortic coarctation repair in neonates and infants

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li Zhang ◽  
Lu Liu ◽  
Zhiqiu Zhong ◽  
Hengfang Jin ◽  
Jian Jia ◽  
...  
Keyword(s):  
Aortic Coarctation ◽  
Cerebral Perfusion ◽  
Tissue Oxygenation ◽  
Perioperative Complications ◽  
Somatic Tissue ◽  
Tissue Oxygen Saturation ◽  
Selective Cerebral Perfusion ◽  
Arterial Blood ◽  
Coarctation Repair ◽  
Neonates And Infants

Abstract Background Suboptimal tissue perfusion and oxygenation may be the root cause of certain perioperative complications in neonates and infants having complicated aortic coarctation repair. Practical, effective, and real-time monitoring of organ perfusion and/or tissue oxygenation may provide early warning of end-organ mal-perfusion. Methods Neonates/infants who were scheduled for aortic coarctation repair with cardiopulmonary bypass (CPB) and selective cerebral perfusion (SCP) from January 2015 to February 2017 in Children’s Hospital of Nanjing Medical University participated in this prospective observational study. Cerebral and somatic tissue oxygen saturation (SctO2 and SstO2) were monitored on the forehead and at the thoracolumbar paraspinal region, respectively. SctO2 and SstO2 were recorded at different time points (baseline, skin incision, CPB start, SCP start, SCP end, aortic opening, CPB end, and surgery end). SctO2 and SstO2 were correlated with mean arterial pressure (MAP) and partial pressure of arterial blood carbon dioxide (PaCO2). Results Data of 21 patients were analyzed (age=75±67 days, body weight=4.4±1.0 kg). SstO2 was significantly lower than SctO2 before aortic opening and significantly higher than SctO2 after aortic opening. SstO2 correlated with leg MAP when the measurements during SCP were (r=0.67, p<0.0001) and were not included (r=0.46, p<0.0001); in contrast, SctO2 correlated with arm MAP only when the measurements during SCP were excluded (r=0.14, p=0.08 vs. r=0.66, p<0.0001). SCP also confounded SctO2/SstO2’s correlation with PaCO2; when the measurements during SCP were excluded, SctO2 positively correlated with PaCO2 (r=0.65, p<0.0001), while SstO2 negatively correlated with PaCO2 (r=-0.53, p<0.0001). Conclusions SctO2 and SstO2 have distinct patterns of changes before and after aortic opening during neonate/infant aortic coarctation repair. SctO2/SstO2’s correlations with MAP and PaCO2 are confounded by SCP. The outcome impact of combined SctO2/SstO2 monitoring remains to be studied.

Mechanical Strength of Sago/Urea Formaldehyde Particleboard Affected by the Particle Size

2016 ◽  
Vol 833 ◽  
pp. 3-10
Author(s):  
Tay Chen Chiang ◽  
Sinin Hamdan ◽  
Mohd Shahril Osman
Keyword(s):  
Mechanical Properties ◽  
Manufacturing Industry ◽  
Urea Formaldehyde ◽  
Great Influence ◽  
Single Layer ◽  
Milling Process ◽  
Raw Material ◽  
Huge Amount ◽  
Testing Method ◽  
Sago Waste

Every year, the sago processing industry in Sarawak-Mukah had generated huge amount of sago waste after the milling process and scientists have employ the waste into composite material. The fabrication and testing method are based on the Japanese A5908 Industrial Standard. Single-layer particleboards with targeted density of 600kg/m3 were produced from different sizes of sago particles. The mechanical properties of sago waste were investigated to study the feasibility of using this sample as a raw material in particleboard manufacturing. The results of the test demonstrate that samples with different sizes of particles have great influence on the mechanical properties such as Young’s Modulus, Tensile Strength and Impact Strength. The findings show that the performance of the board is affected by the different sizes of sago particles used in the experiment and had proved that sago plants can be used as an alternative raw material in the particleboard manufacturing industry.

scholarly journals Comparison of static and dynamic cerebral autoregulation under anesthesia influence in a controlled animal model

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245291
Author(s):  
Alexander Ruesch ◽  
Deepshikha Acharya ◽  
Samantha Schmitt ◽  
Jason Yang ◽  
Matthew A. Smith ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Animal Model ◽  
Blood Flow ◽  
Intracranial Pressure ◽  
Cerebral Perfusion Pressure ◽  
Cerebral Autoregulation ◽  
Cerebral Perfusion ◽  
Perfusion Pressure ◽  
Phase Lag ◽  
Arterial Blood

The brain’s ability to maintain cerebral blood flow approximately constant despite cerebral perfusion pressure changes is known as cerebral autoregulation (CA) and is governed by vasoconstriction and vasodilation. Cerebral perfusion pressure is defined as the pressure gradient between arterial blood pressure and intracranial pressure. Measuring CA is a challenging task and has created a variety of evaluation methods, which are often categorized as static and dynamic CA assessments. Because CA is quantified as the performance of a regulatory system and no physical ground truth can be measured, conflicting results are reported. The conflict further arises from a lack of healthy volunteer data with respect to cerebral perfusion pressure measurements and the variety of diseases in which CA ability is impaired, including stroke, traumatic brain injury and hydrocephalus. To overcome these differences, we present a healthy non-human primate model in which we can control the ability to autoregulate blood flow through the type of anesthesia (isoflurane vs fentanyl). We show how three different assessment methods can be used to measure CA impairment, and how static and dynamic autoregulation compare under challenges in intracranial pressure and blood pressure. We reconstructed Lassen’s curve for two groups of anesthesia, where only the fentanyl anesthetized group yielded the canonical shape. Cerebral perfusion pressure allowed for the best distinction between the fentanyl and isoflurane anesthetized groups. The autoregulatory response time to induced oscillations in intracranial pressure and blood pressure, measured as the phase lag between intracranial pressure and blood pressure, was able to determine autoregulatory impairment in agreement with static autoregulation. Static and dynamic CA both show impairment in high dose isoflurane anesthesia, while low isoflurane in combination with fentanyl anesthesia maintains CA, offering a repeatable animal model for CA studies.

Neurological assessment of the acute cardiac care patient

2018 ◽  
Author(s):  
Cathy De Deyne ◽  
Ward Eertmans ◽  
Jo Dens
Keyword(s):  
Clinical Examination ◽  
Cerebral Perfusion ◽  
Cerebral Oxygenation ◽  
Blood Pressure Monitoring ◽  
Gas Analysis ◽  
Cardiac Care ◽  
Arterial Blood Gas ◽  
Physiological Variables ◽  
Arterial Blood ◽  
Cerebral Monitoring

Many techniques are currently available for cerebral physiological monitoring in the intensive cardiac care unit environment. The ultimate goal of cerebral monitoring applied during the acute care of any patient with/or at risk of a neurological insult is the early detection of regional or global hypoxic/ischaemic cerebral insults. In the most ideal situation, cerebral monitoring should enable the detection of any deterioration before irreversible brain damage occurs or should at least enable the preservation of current brain function (such as in comatose patients after cardiac arrest). Most of the information that affects bedside care of patients with acute neurologic disturbances is now derived from clinical examination and from knowledge of the pathophysiological changes in cerebral perfusion, cerebral oxygenation, and cerebral function. Online monitoring of these changes can be realized by many non-invasive techniques, without neglecting clinical examination and basic physiological variables—with possible impact on optimal cerebral perfusion/oxygenation—such as invasive arterial blood pressure monitoring or arterial blood gas analysis.

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