Identification of Anesthesia Stages from EEG Signals using Wavelet Entropy and Backpropagation Neural Network

This study focuses on entropy based analysis of EEG signals for extracting features for a neural network based solution for identifying anesthetic levels. The process involves an optimized back propagation neural network with a supervised learning method. We provided the extracted features from EEG signals as training data for the neural network. The target outputs provided are levels of anesthesia stages. Wavelet analysis provides more effective extraction of key features from EEG data than power spectral density analysis using Fourier transform. The key features are used to train the Back Propagation Neural Network (BPNN) for pattern classification network. The final result shows that entropybased feature extraction is an effective procedure for classifying EEG data

Wearable, Integrated EEG-fNIRS Technologies: A Review.

There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG-fNIRS can provide a comprehensive picture of brain electrical and hemodynamic function and has been applied across various fields of brain science. The development of wearable, mechanically and electrically integrated EEG-fNIRS technology is a critical next step in the evolution of this field. A suitable system design could significantly increase the data/image quality, the wearability, patient/subject comfort, and capability for long-term monitoring. Here, we present a concise, yet comprehensive, review of the progress that has been made toward achieving a wearable, integrated EEG-fNIRS system. Significant marks of progress include the development of both discrete component-based and microchip-based EEG-fNIRS technologies; modular systems; miniaturized, lightweight form factors; wireless capabilities; and shared analogue-to-digital converter (ADC) architecture between fNIRS and EEG data acquisitions. In describing the attributes, advantages, and disadvantages of current technologies, this review aims to provide a roadmap toward the next generation of wearable, integrated EEG-fNIRS systems

A Newcomer\u27s Guide to Functional Near Infrared Spectroscopy Experiments

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs

Development of a novel diffuse correlation spectroscopy platform for monitoring cerebral blood flow and oxygen metabolism: from novel concepts and devices to preclinical live animal studies

New optical technologies were developed to continuously measure cerebral blood flow (CBF) and oxygen metabolism (CMRO2) non-invasively through the skull. Methods and devices were created to improve the performance of near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) for use in experimental animals and humans. These were employed to investigate cerebral metabolism and cerebrovascular reactivity under different states of anesthesia and during models of pathological states. Burst suppression is a brain state arising naturally in pathological conditions or under deep general anesthesia, but its mechanism and consequences are not well understood. Electroencephalography (EEG) and cortical hemodynamics were simultaneously measured in rats to evaluate the coupling between cerebral oxygen metabolism and neuronal activity in the burst suppressed state. EEG bursts were used to deconvolve NIRS and DCS signals into the hemodynamic and metabolic response function for an individual burst. This response was found to be similar to the stereotypical functional hyperemia evoked by normal brain activation. Thus, spontaneous burst activity does not cause metabolic or hemodynamic dysfunction in the cortex. Furthermore, cortical metabolic activity was not associated with the initiation or termination of a burst. A novel technique, time-domain DCS (TD-DCS), was introduced to significantly increase the sensitivity of transcranial CBF measurements to the brain. A new time-correlated single photon counting (TCSPC) instrument with a custom high coherence pulsed laser source was engineered for the first-ever simultaneous measurement of photon time of flight and DCS autocorrelation decays. In this new approach, photon time tags are exploited to determine path-length-dependent autocorrelation functions. By correlating photons according to time of flight, CBF is distinguished from superficial blood flow. Experiments in phantoms and animals demonstrate TD-DCS has significantly greater sensitivity to the brain than existing transcranial techniques. Intracranial pressure (ICP) modulates both steady-state and pulsatile CBF, making CBF a potential marker for ICP. In particular, the critical closing pressure (CrCP) has been proposed as a surrogate measure of ICP. A new DCS device was developed to measure pulsatile CBF non-invasively. A novel method for estimating CrCP and ICP from DCS measurement of pulsatile microvascular blood flow in the cerebral cortex was demonstrated in rats.2018-03-08T00:00:00

Identification of Anesthesia Stages from EEG Signals using Wavelet Entropy and Backpropagation Neural Network

This study focuses on entropy based analysis of EEG signals for extracting features for a neural network based solution for identifying anesthetic levels. The process involves an optimized back propagation neural network with a supervised learning method. We provided the extracted features from EEG signals as training data for the neural network. The target outputs provided are levels of anesthesia stages. Wavelet analysis provides more effective extraction of key features from EEG data than power spectral density analysis using Fourier transform. The key features are used to train the Back Propagation Neural Network (BPNN) for pattern classification network. The final result shows that entropybased feature extraction is an effective procedure for classifying EEG data

Review of recent advances in frequency-domain near-infrared spectroscopy technologies [Invited]

Over the past several decades, near-infrared spectroscopy (NIRS) has become a popular research and clinical tool for non-invasively measuring the oxygenation of biological tissues, with particular emphasis on applications to the human brain. In most cases, NIRS studies are performed using continuous-wave NIRS (CW-NIRS), which can only provide information on relative changes in chromophore concentrations, such as oxygenated and deoxygenated hemoglobin, as well as estimates of tissue oxygen saturation. Another type of NIRS known as frequency-domain NIRS (FD-NIRS) has significant advantages: it can directly measure optical pathlength and thus quantify the scattering and absorption coefficients of sampled tissues and provide direct measurements of absolute chromophore concentrations. This review describes the current status of FD-NIRS technologies, their performance, their advantages, and their limitations as compared to other NIRS methods. Significant landmarks of technological progress include the development of both benchtop and portable/wearable FD-NIRS technologies, sensitive front-end photonic components, and high-frequency phase measurements. Clinical applications of FD-NIRS technologies are discussed to provide context on current applications and needed areas of improvement. The review concludes by providing a roadmap toward the next generation of fully wearable, low-cost FD-NIRS systems

Tehohoitopotilaiden neuromonitorointi

In critical illness the risk of neurological insults is high, whether because of the illness itself, or as a treatment complication. As a result, the length of hospital stay and the risk of both further morbidity and mortality are all roughly doubled. One of the major challenges is the inability to monitor a sedated, mechanically ventilated patient’s neurological symptoms during intensive care treatment, due to a lack of reliable methods. The aims of this thesis research were to identify and test potential non-invasive methods, which would be predictive of neurological outcome, showing potential as neuromonitoring methods of critical care patients unable to self-report. As a guiding theme, all tested methods could be applied to actual critical care with relative ease. Patients were included from two groups with a notably high incidence of neurological complications, namely acute liver failure patients with hepatic encephalopathy (I), and aortic surgery patients operated during hypothermic circulatory arrest (II). The first group included 20 patients, and the latter 30 patients. Late mortality and quality of life was assessed for the aortic surgery patients (III), and the postoperative development of certain blood biomarkers (IV). The tested non-invasive neuromonitoring methods included electroencephalogram (EEG) variables from frontal or fronto-temporal abbreviated monitoring, frontal near-infrared spectroscopy, transcranial Doppler ultrasound measurements of the intracranial blood flow, and finally biomarkers. The last included established biomarkers with an association with neurological complications, namely neuron-specific enolase, and protein S100β, and several interesting biomarkers normally associated with tumours and pancreatitis. Of the tested methods, the frontal EEG variables showed greatest promise, but the addition of the temporal channels did not increase sensitivity. Spectral EEG variables were predictive of the stage of hepatic encephalopathy (I), while a novel EEG variable called wavelet subband entropy was predictive of neurological outcome (I). The hemispheric asymmetry of frontal EEG was reasonably predictive of neurological outcome after aortic surgery (II). None of the other tested methods were predictive of outcome (I, II, IV), except protein S100β, which was significantly higher in the poor outcome group 48 to 72 hours after hypothermic circulatory arrest (II). The quality of life of aortic surgery patients was good after 5 to 8 years, and comparable with the general population of chronically ill patients (III). The aim of this explorative research was to identify and test non-invasive neuromonitoring methods, suitable for use in critical care. Based on the results, frontal EEG variables are promising and predict the grade of hepatic encephalopathy and neurological outcome. The other tested methods were not predictive of neurological outcome. The long-term quality of life of aortic surgery patients is very good, despite the high risk for neurological complications.Kriittisissä sairauksissa neurologisen komplikaation riski on suuri, sekä itse kriittisen sairauden että varsinaisen hoidon seurauksena. Haittatapahtuman johdosta sairaalahoidon kesto sekä sairastuvuuden ja kuolleisuuden riskit kaksinkertaistuvat. Yksi suurimmista haasteista on luotettavien menetelmien puute, joilla voitaisiin arvioida mekaanisen hengitystuen varassa olevan ja rauhoittavia lääkkeitä saavan potilaan neurologisia oireita tehohoidon aikana. Tämän väitöskirjatyön tarkoituksena oli tunnistaa ja testata lupaavia ei-kajoavia menetelmiä, jotka ennustaisivat neurologista lopputulosta, ja jotka soveltuisivat kriittisesti sairaan tehohoitopotilaan neuromonitorointiin. Kantavana teemana kaikki testatut menetelmät voitaisiin soveltaa kliiniseen työhön suhteellisen helposti. Potilaita kerättiin kahteen ryhmään, joissa neurologisten komplikaatioiden esiintyvyys on huomattavan suuri. Ensimmäinen ryhmä käsitti akuuttia maksan vajaatoimintaa ja hepaattista enkefalopatiaa sairastavat potilaat (I), toinen hypotermisen verenkierron pysäytyksen aikana rinta-aortan leikkauksen läpikäyvät potilaat (II). Ensimmäiseen ryhmään kuului 20 potilasta, jälkimmäiseen 30 potilasta. Aorttaleikatuilta potilailta arvioitiin myös elämänlaatua sekä myöhäiskuolleisuutta (III), lisäksi tiettyjen biomerkkiaineiden aorttaleikkauksen jälkeistä kehitystä ja soveltuvuutta neuromonitorointiin arvioitiin yhdessä osatyössä (IV). Tutkimuksessa arvioituihin ei-kajoaviin neuromonitorointimenetelmiin lukeutuivat otsa- ja ohimolohkon elektroenkefalografia (EEG), lähi-infrapunaspektroskopia, transkraniaalinen Doppler-ultraäänimittaus sekä verestä mitattavat biomerkkiaineet. Biomerkkiaineet kattoivat sekä vakiintuneita aivovauriota heijastavia merkkiaineita (hermostoperäinen enolaasi, proteiini S100β) että useita mielenkiintoisia merkkiaineita, jotka liittyvät kasvaintauteihin ja haimatulehdukseen. Testatuista menetelmistä otsalohkon EEG muuttujat olivat lupaavia, mutta ohimolohkon EEG lisääminen ei parantanut menetelmien herkkyyttä. EEG spektrimuuttujat ennustivat hepaattisen enkefalopatian astetta (I) luotettavasti, kun taas kokeellinen EEG-muuttuja (aalloke-alitaajuuden entropia) ennusti luotettavasti neurologista lopputulosta akuutin maksan vajaatoimintaa sairastavilla potilailla (I). Otsalohkon aivopuoliskojen EEG-rekisteröinnin hetkellinen epäsymmetria ennusti kohtalaisella tarkkuudella neurologisten päätetapahtumien esiintymisen aorttaleikatuilla potilailla (II). Muut testatut menetelmät eivät ennustaneet neurologista lopputulemaa (I, II, IV), paitsi proteiini S100β, joka oli merkittävästi korkeampi 48–72 tuntia leikkauksen jälkeen niillä potilailla, joiden neurologinen toipuminen oli huono (IV). Aorttaleikattujen potilaiden elämänlaatu oli hyvä 5–8 vuotta leikkauksen jälkeen ja verrattavissa kroonisesti sairaan väestön elämänlaatuun (III). Tämän kartoittavan tutkimuksen tarkoituksena oli tunnistaa ja testata ei-kajoavia neuromonitorointimenetelmiä, jotka soveltuvat tehohoitoon. Tulosten perusteella otsalohkon EEG-muuttujat ennustavat hepaattisen enkefalopatian astetta sekä potilaan neurologista toipumista. Muut testatut menetelmät eivät ennustaneet neurologista toipumista luotettavasti. Aorttaleikattujen potilaiden pitkäaikainen (5–8 vuoden) terveyteen liittyvä elämänlaatu on erittäin hyvä, vaikka leikkaukseen liittyy korkea aivovaurion riski

Multimodality Neuromonitoring in Adult Traumatic Brain Injury A Narrative Review

Neuromonitoring plays an important role in the management of traumatic brain injury. Simultaneous assessment of cerebral hemodynamics, oxygenation, and metabolism allows an individualized approach to patient management in which therapeutic interventions intended to prevent or minimize secondary brain injury are guided by monitored changes in physiologic variables rather than generic thresholds. This narrative review describes various neuromonitoring techniques that can be used to guide the management of patients with traumatic brain injury and examines the latest evidence and expert consensus guidelines for neuromonitoring

Study of the Hemodynamic Response to Interictal Epileptiform Discharges in Human Epilepsy Using Functional Near Infrared Spectroscopy

RÉSUMÉ L'imagerie spectroscopique proche infrarouge fonctionnelle (ISPIf) s'est imposée comme technique d’imagerie neuronale prometteuse. Cette dernière permet une surveillance non invasive de l'évolution chronique de l'activité hémodynamique corticale. Durant la dernière décennie, ISPIf combiné avec l'électroencéphalographie (EEG) a été appliqué dans le contexte de l'épilepsie humaine, et a permi d’explorer le lien entre l’activité neurale et hémodynamique. Cependant, la plupart des travaux antérieurs sont uniquement axés sur l'étude des crises d'épilepsie qui sont aléatoires et se produisent rarement pendant un test de l’EEG-ISPIf. Cette thèse cherche à évaluer la capacité de l'EEG-ISPIf à observer les changements hémodynamiques associés aux décharges épileptiformes intercritiques (DEIs), et à déterminer si ces DEIs peuvent également être utilisés pour extraire de l'information additionnelle servant à la localisation du site d’un foyer épileptique. En se basant sur des données multimodales EEG-ISPIf recueillies sur un grand échantillon de patients (40), combiné à l'utilisation d'un modèle linéaire généralisé (MLG), une première étude a permis la quantification préliminaire de la sensibilité et la spécificité de la technique en utilisant la détection des zones cérébrales activées par des DEIs pour la localisation de la région du foyer épileptique. Dans un sous-groupe de 29 patients atteints au niveau de la région néocorticale, lorsque mesuré durant des évènements de DEIs, des diminutions de la concentration d’hémoglobine désoxygénée (HbR) (chez 62% des sujets) et des augmentations de la concentration de l’hémoglobine oxygénée (HbO) (chez 38% des sujets) ont été observées. De plus, cette variation en HbR et HbO était significativement plus forte dans la région du foyer épileptique (qui donc pourrait conduire à une localisation du foyer épileptique) dans 28% / 21% des patients. Ces estimations modestes de la sensibilité et de la spécificité suggèrent que l'utilisation d'une fonction de réponse hémodynamique (FRH) canonique n’est pas optimale dans l’analyse des DEIs par MLG classique. Par conséquent, une seconde approche a été explorée dans le cadre d’une deuxième étude par modélisation des variations spécifiques à chaque patient dans la construction de la réponse hémodynamique associée aux DEIs. Un terme quadratique a également été ajouté au modèle pour tenir compte de la non-linéarité de la réponse associée à une fréquence plus élevée d’évènements lors de l'enregistrement. Ces nouveaux modèles ont d'abord été validés numériquement par simulations, avant d’être appliqués à l'analyse de données de cinq patients sélectionnés. Lorsque comparée à la FRH canonique, l'utilisation de la FRH spécifique au patient dans l'analyse MLG a non seulement amélioré considérablement les scores statistiques et les étendues spatiales des----------ABSTRACT Functional near-infrared spectroscopy (fNIRS) has emerged as a promising neuroimaging technique as it allows non-invasive and long-term monitoring of cortical hemodynamics. For the last decades, fNIRS combined with electroencephalography (EEG) has been applied in the context of human epilepsy, and has yielded good results. However, most previous work only focused on the study of epileptic seizures which are random and seldom occur during EEG-fNIRS testing. This thesis sought to evaluate the potential of EEG-fNIRS in observing the hemodynamic changes associated with interictal epileptiform discharges (IEDs), and to determine whether these IEDs can also be used to extract useful information in the localization of the epileptic focus site. Based on the EEG-fNIRS data collected from a relatively large number of patients (40) and using a standard general linear model (GLM) approach, the first study of this thesis provided preliminary estimates of the sensitivity and the specificity of EEG-fNIRS in detecting brain areas activated by IEDs and in localizing the epileptic focus region. In the 29 patients with neocortical epilepsies, significant deoxygenated hemoglobin (HbR) concentration decreases and oxygenated hemoglobin (HbO) concentration increases corresponding to IEDs were observed in 62% and 38% of patients respectively. This HbR/HbO response was most significant in the epileptic focus region among all the activations, and thus could lead to successful identification of the epileptic focus site in 28%/21% of the patients. These modest estimates of the sensitivity and the specificity suggested that using a standard GLM with a canonical hemodynamic response function (HRF) might not be the optimal method in the analysis of IEDs. Therefore, the second study of this thesis made a first attempt to model the patient-specific variations in the shape of the hemodynamic response to IEDs. A quadratic term was also added to the model to account for the nonlinearity in the response when frequent IEDs were present in the recording. The new models were first validated through carefully designed simulations, and were then applied in the data analysis of five selected patients. Compared with the canonical HRF, including patient-specific HRFs in the GLM analysis not only significantly improved the statistical scores and the spatial extents of existing activations, but also was able to detect new brain regions activated by IEDs on all of the five patients. These improvements in activation detection also helped obtain more accurate focus localization results in some cases

Early brain activity : Translations between bedside and laboratory

Neural activity is both a driver of brain development and a readout of developmental processes. Changes in neuronal activity are therefore both the cause and consequence of neurodevelopmental compromises. Here, we review the assessment of neuronal activities in both preclinical models and clinical situations. We focus on issues that require urgent translational research, the challenges and bottlenecks preventing translation of biomedical research into new clinical diagnostics or treatments, and possibilities to overcome these barriers. The key questions are (i) what can be measured in clinical settings versus animal experiments, (ii) how do measurements relate to particular stages of development, and (iii) how can we balance practical and ethical realities with methodological compromises in measurements and treatments.Peer reviewe