Journal articles: 'ELECTROENCEPHALOGRA'

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Noach, LA, Jla Eekhof, LJ Bour, FE Posthumus Meyjes, Gnj Tytgat, and BW Ongerboer de Visser. "Bismuth salts and neurotoxicity. A randomised, single-blind and controlled study." Human & Experimental Toxicology 14, no. 4 (April 1995): 349–55. http://dx.doi.org/10.1177/096032719501400405.

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The aim of this work was to investigate whether the nor mal use of colloidal bismuth subcitrate (CBS) and bismuth subnitrate (BSN) exhibits neurotoxic side-effects. A ran domised, single-blind controlled study was carried out in 66 patients with H. pylori associated gastritis. Patients were randomised to receive either amoxicillin (control group) for 4 weeks or BSN for 8 weeks or CBS for 8 weeks. Clinical and neurophysiological tests including elec troneurography (ENG) and spectral electroencephalogra phy (EEG) were performed before and after therapy. No clinically relevant changes were observed with clinical tests as well as with ENG and spectral EEG recordings within each group and between the groups. It was con cluded that the normal use of CBS and BSN does not exhibit clinical neurotoxicity.

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Prendergast, Erica, Michele Grimason Mills, Jonathan Kurz, Joshua Goldstein, and Andrea C. Pardo. "Implementing Quantitative Electroencephalogram Monitoring by Nurses in a Pediatric Intensive Care Unit." Critical Care Nurse 42, no. 2 (April 1, 2022): 32–40. http://dx.doi.org/10.4037/ccn2022680.

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Background Nonconvulsive seizures occur frequently in pediatric intensive care unit patients and can be impossible to detect clinically without electroencephalogram monitoring. Quantitative electroencephalography uses mathematical signal analysis to compress data, monitoring trends over time. Nonneurologists can identify seizures with quantitative electroencephalography, but data on its use in the clinical setting are limited. Local Problem Bedside quantitative electroencephalography was implemented and nurses received education on its use for seizure detection. This quality improvement project aimed to describe the time between nurses’ recognition of electrographic seizures and seizure treatment. Methods Education was provided in phases over several months. Retrospective medical record review evaluated quantitative electroencephalograms and medication interventions from September 2019 through March 2020. A bedside form was used to measure nurses’ use of quantitative electroencephalograms, change recognition, clinician notification, and seizure treatment. A nurse survey evaluated the education after implementation. Results Data included 44 electroencephalograms from 30 pediatric intensive care unit patients aged 18 years or less with electroencephalogram monitoring durations of 4 hours or longer. Nurses monitored quantitative electroencephalograms in 73% of cases, documented at least 1 change in the quantitative electroencephalogram display in 28% of these cases, and contacted the neurocritical care team in 78% of cases in which they documented a change. Seizure treatment was initiated in response to the nursing call in 1 patient. Time to treatment was approximately 20 minutes. Conclusions An education program for quantitative electroencephalogram interpretation by nurse providers is feasible yet complex, requiring multiple reeducation cycles.

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Shafait, Saima, Wasim Alamgir, Imran Ahmad, Saeed Arif, Jahanzeb Liaqat, and Asif Hashmat. "A STUDY ON COMPARATIVE YIELDS OF STANDARD SHORT TERM ELECTROENCEPHALOGRAM AND LONG TERM ELECTROENCEPHALOGRAM RECORDING IN SUSPECTED EPILEPSY PATIENTS." PAFMJ 71, no. 5 (October 31, 2021): 1727–31. http://dx.doi.org/10.51253/pafmj.v71i5.5921.

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Objective: To compare the yield of interictal epileptiform discharges on prolonged (1-2 hours) electroencephalogram (EEG) as compared to standard routine (30 minutes) electroencephalogram (EEG). Study Design: Comparative observational study. Place and Duration of Study: Pak Emirates Military Hospital, Rawalpindi from Oct 2019 to Sep 2020. Methodology: A total of 364 outdoor patients with suspected epilepsy were recruited for the study. Out of these 55 electroencephalograms were excluded after applying exclusion criteria and 309 were included for final analysis. Electro-encephalograms were recorded using a 10-20 international system of electrode placement. The duration of each standard electroencephalogram was 30 minutes. It was followed by recording for an extended period of 60 minutes at least. The time to the appearance of the first abnormal interictal epileptiform discharge was noted. For analytical purposes, epileptiform discharges were classified as “early” if they appeared within the first 30 minutes and as “late” if appeared afterward. All electro-encephalograms were evaluated independently by two neurologists. Results: A total of 309 electroencephalograms were included for final analysis. Interictal epileptiform discharges were seen in 48 (15.6%) recordings. The mean time to appearance of first interictal epileptiform discharge was 14.6 ± 19.09 minutes. In 36 (11.7%) cases, discharges appeared early (within the first 30 minutes) whereas in the remaining 12 (3.9%) cases, discharges appeared late. This translates into a 33% increase in the diagnostic yield of electroencephalogram with an extended period of recording. Conclusion: Extending the electroencephalogram recording time results in a significantly better diagnostic yield of outdoor electroencephalogram.

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Zhu, Qianwen, Jianmin Zhang, Xingnan Wang, and Yueying Fang. "Influencing factors for cognitive impairment in patients with dorsolateral frontal lobe epilepsy." Neurology Asia 27, no. 2 (June 2022): 301–8. http://dx.doi.org/10.54029/2022crv.

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Background & Objective: To explore the influencing factors for cognitive impairment in patients with dorsolateral frontal lobe epilepsy (FLE) and the correlation between cognitive function and abnormal electroencephalograms. Methods: Eighty-two patients with dorsolateral FLE treated from April 2018 to April 2020 were selected. According to cognitive function test results, they were divided into a normal group (n=47) and an impairment group (n=35). Their general data were compared. The factors affecting cognitive function were assessed by univariate and multivariate logistic regression analyses. A nomogram prediction model was constructed for predicting cognitive impairment, and the predictive accuracy was assessed. The cognitive function and electroencephalogram results were compared. The correlation between abnormal electroencephalograms and cognitive function was analyzed. Results: Onset age ≥20 years old, educational years ≤12 years, course of disease ≥8 years, seizure frequency ≥once every 4 months, seizure duration ≥1.5 min and medication type were independent risk factors influencing the cognitive function of patients with dorsolateral FLE. The nomogram prediction model was highly accurate for predicting cognitive impairment. The levels of directional memory, associative learning memory, free recall of images, re-recognition of meaningless images, recall of character features, digital symbol substitution test, verbal fluency test, and backward digital span test of the impairment group were significantly lower than those of the normal group, and the number of patients with abnormal electroencephalograms was remarkably larger in the former group. Abnormal electroencephalogram had a significant negative correlation with cognitive impairment. Conclusion: Onset age, educational years, course of the disease, seizure frequency, seizure duration and medication type influence the cognitive function of patients with dorsolateral FLE. Abnormal electroencephalograms are closely correlated with cognitive function.

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Sidorenko, A. V., and M. A. Saladukha. "Evaluation of the depressive state of mobile technical systems operator subjected to electromagnetic noise radiation." Doklady BGUIR 18, no. 4 (June 25, 2020): 53–61. http://dx.doi.org/10.35596/1729-7648-2020-18-4-53-61.

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This paper presents the results of the work aimed at a study of the patterns of changes in the nonlinear electroencephalogram (EEG) parameters, including fractal dimension and self-similarity exponent, when the operator is irradiated with electromagnetic noise radiation. Together with the above-mentioned nonlinear parameters, a change in the spectral power density of the rhythmic components in EEG (delta-, theta-, alpha-, and beta-rhythms) has been studied. Investigation of the fractal dimension, self-similarity exponent, and spectral power density during irradiation was associated with possible changes of the parameters in the case of operator’s depression or minor depression. The radiation source was represented by a transistor electromagnetic-noise generator with the power of 30 mW operating over the frequency range of 5 GHz. The methods for calculation of the nonlinear parameters including fractal dimension and self-similarity exponent have been described. To realize the principal objectives of the work, the Java-based software was developed. The relevant literature demonstrating the changes in fractal dimension, self-similarity exponent, spectral power density of the delta-, theta-, alpha-, beta-rhythms in the case of depression and minor depression has been reviewed. Electroencephalograms were registered according to the “10/20” scheme using the MBN Neurocartograph electroencephalograph. The analyzed leads were Fp1, Fp2, T3, T4, P3, P4, O1, O2, F3, F4, C3, C4. As shown by the results of this work, there is no distinct depressive state of the operator exposed to electromagnetic noise radiation, judging by changes in the self-similarity exponent, fractal dimension, and spectral power density. However, when the operator was irradiated with electromagnetic noise radiation, the observed tendency in variation of the parameters was characteristic for minor depression.

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Bragin, A. D., and V. G. Spitsyn. "Motor imagery recognition in electroencephalograms using convolutional neural networks." Computer Optics 44, no. 3 (June 2020): 482–87. http://dx.doi.org/10.18287/2412-6179-co-669.

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Electroencephalography is a widespread method to record brain signals with the use of electrodes located on the surface of the head. This method of recording the brain activity has become popular because it is relatively cheap, compact, and does not require implanting the electrodes directly into the brain. The article is devoted to a problem of recognition of motor imagery by electroencephalogram signals. The nature of such signals is complex. Characteristics of electroencephalograms are individual for every person, also depending on their age and mental state, as well as the presence of noise and interference. The multitude of these parameters should be taken into account when analyzing encephalograms. Artificial neural networks are a good tool for solving this class of problems. Their application allows combining the tasks of extracting, selecting and classifying features in one signal processing unit. Electroencephalograms are time signals and we note that Gramian Angular Fields and Markov Transition Field transforms are used to represent time series in the form of images. The article shows the possibility of using the Gramian Angular Fields and Markov Transition Field transformations of the electroencephalogram (EEG) signal for motor imagery recognition using examples of imaginary movements with the right and left hand, also studying the effect of the resolution of Gramian Angular Fields and Markov Transition Field images on the classification accuracy. The best classification accuracy of the EEG signal into the motion and state-of-rest classes is about 99%. In future, the research results can be applied in constructing the brain-computer interface.

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Berezovchuk, L. V., and M. E. Makarchuk. "About bioelectric buffer system of the brain." Klinicheskaia khirurgiia 87, no. 7-8 (September 30, 2020): 53–57. http://dx.doi.org/10.26779/2522-1396.2020.7-8.53.

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Objective. Elaboration of objective quantitative criterion of electroencephalogram for estimation of the brain functional state in man. Маterials and methods. The background electroencephalograms analysis was conducted in 6 groups of the examined patients with various diagnosis (41 patients at all). Control group consisted of 7 patients, ageing 20 - 56 yrs (average age 35 yrs). Recording of EEG was conducted, using 16-channel electroencephalograph «NeuroCom standart» (KhАI - Меdika, Ukraine) in accordance to international system of recording «10-20». There were analyzed a quantity of meaningful interhemispheric asymmetries in accordance to power of summarized bioelectric signal in bilateral-synchronous points of the head in every group. The analysis time have constituted 1 min. Results. There was established, that the least meaningful difference in accordance to the bioelectrical signal power in bilateral-synchronous points of head may be considered in 1.4 times. Quantity of meaningful interhemispheric asymmetries in man may vary in large diapason - from 9 tо 25. Not all meaningful interhemispheric asymmetries in accordance to power of signals of separate rhythms are preserved while doing analysis of meaningful interhemispheric asymmetries in accordance to power of a summarized bioelectrical signal. Interhemispheric asymmetries in accordance to power of the summarized bioelectric signal in bilateral-synchronous points of the head may have more important informative meaning, than interhemispheric asymmetry in accordance to the signals power of separate rhythms. Conclusion. Quantity of meaningful interhemispheric asymmetries in accordance to power of signals of separate rhythms in healthy persons may vary from 16 tо 18. The interhemispheric asymmetries quantity reduction in accordance to power of the summarized bioelectric signal, comparing with quantity of interhemispheric asymmetries in accordance to power of signals of separate rhythms more than in 4 times, witnesses presence of the brain bioelectrical buffer system.

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Fonseca, Lineu C., Glória M. A. S. Tedrus, Marcelo G. Chiodi, Jaciara Näf Cerqueira, and Josiane M. F. Tonelotto. "Quantitative EEG in children with learning disabilities: analysis of band power." Arquivos de Neuro-Psiquiatria 64, no. 2b (June 2006): 376–81. http://dx.doi.org/10.1590/s0004-282x2006000300005.

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In order to better understand the mechanisms of learning disabilities it is important to evaluate the electroencephalogram parameters and their relation to the results of the Wechsler Intelligence Scale. Thirty-six children with complaints of learning disability were studied. Electroencephalograms were carried out while awake and resting, and the values for absolute and relative powers calculated. The results were compared with those of 36 healthy children paired with respect to age, gender and maternal scholastic level. In the group with learning disabilities, the absolute (in the delta, theta and alpha 1 bands) and relative (theta) power values were higher and the relative power alpha 2 value significantly lower at the majority of the electrodes in relation to the control group. There was a high positive correlation in the children with learning disabilities between the relative power alpha 2 and the verbal, performance and total IQ values. These quantitative electroencephalogram findings in children with learning disabilities have a clear relation with psychological measurements and could be due to brain immaturity.

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Patil, Miss N. R., and Prof S. N. Patil. "Review:Wavelet transform based electroencephalogram methods." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1776–79. http://dx.doi.org/10.31142/ijtsrd11542.

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Araki, Ryuhei, Kazuko Hayashi, and Teiji Sawa. "Dopamine D2-receptor Antagonist Droperidol Deepens Sevoflurane Anesthesia." Anesthesiology 128, no. 4 (April 1, 2018): 754–63. http://dx.doi.org/10.1097/aln.0000000000002046.

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Abstract Background Although midbrain dopaminergic pathways are known to contribute to arousal and emergence from anesthesia, few reports exist regarding the anesthetic effects of dopamine D2 receptor antagonism in humans. This study examined the effect of the D2 receptor antagonist droperidol on sevoflurane anesthesia by examining α and slow wave electroencephalogram oscillations. Methods Forty-five patients, age 20 to 60 yr, were enrolled. Frontal electroencephalograms were continuously collected for offline analysis via Bispectral Index monitoring. After induction of anesthesia, end-tidal sevoflurane concentration was deliberately maintained at 1%, and intravenous droperidol (0.05 mg/kg bolus) was administered. Electroencephalogram changes were examined in power spectrum and bicoherence, before and 10 min after droperidol injection, then compared using the Wilcoxon signed-ranks test and/or paired t test. Results Droperidol significantly augmented the α-bicoherence peak induced by sevoflurane from 30.3% (24.2%, 42.4%) to 50.8% (41.7%, 55.2%) (median [25th, 75th percentiles]; P < 0.0001), Hodges-Lehman median difference, 15.8% (11.3 to 21.4%) (95% CI). The frequency of the α-bicoherence peak was simultaneously shifted to the lower frequency; from 11.5 (11.0, 13.0) to 10.5 (10.0, 11.0) Hz (median [25th, 75th percentiles], P < 0.0001). Averaged bicoherence in the δ-θ area increased conspicuously from 17.2% (15.6 to 18.7%) to 25.1% (23.0 to 27.3%) (mean [95% CI]; P < 0.0001), difference, 8.0% (6.0 to 9.9%). Conclusions Droperidol augments both α and δ-θ bicoherences while shifting the α-bicoherence peaks to lower frequencies, and enhances the effect of sevoflurane anesthesia on the electroencephalogram via γ-aminobutyric acid–mediated oscillatory network regulation.

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Carolis, Piero de, Paolo Tinuper, and Tommaso Sacquegna. "Migraine with Aura and Photosensitive Epileptic Seizures: A Case Report." Cephalalgia 11, no. 3 (July 1991): 151–53. http://dx.doi.org/10.1046/j.1468-2982.1991.1103151.x.

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An 18-year-old female presented with two seizures induced by photic stimulation. She had a positive family history for migraine and a history of febrile convulsions. Since the age of 13 she had suffered from migraine attacks with aura. A brain computerized tomography with contrast enhancement was negative and several electroencephalograms showed a photoparoxysmal response. At the age of 18 she had a partial secondary generalized seizure after photic stimulation during routine electroencephalogram. The onset of seizure was in the occipital region. Two days later, the patient presented with a typical migrainous attack with aura. Interictal apomorphine test (1.5 mg s.c.) blocked the photoparoxysmal response. According to Quesnay, dopaminergic failure of the occipital cortex may account for both epileptic and migraine features.

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Krivonogova, E. V., L. V. Poskotinova, D. B. Demin, and O. A. Stavinskaya. "SEROTONIN LEVEL IN PERIPHERAL BLOOD AND THE BRAIN’S BIOELECTRICAL ACTIVITY IN YOUNG PEOPLE 15-17 YEARS." Medical academic journal 19, no. 1S (December 15, 2019): 137–38. http://dx.doi.org/10.17816/maj191s1137-138.

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The purpose of the work is to evaluate the features of the organization of the bioelectrical activity of the brain with different levels of serotonin in the serum of peripheral blood in young people 15-17 years old. The study involved 93 healthy girls and boys (15-17 years) of the Arkhangelsk region and the Nenets autonomous okrug. A serotonin level is determined in serum by enzyme immunoassay using a set of “Serotonin ELISA”. The electroencephalogram (EEG) power spectrum (PS) in the alpha, beta and theta frequencies ranges was recorded using an electroencephalograph “Encephalan” (Medicom, Taganrog). Age-dependent electroencephalogram (EEG) patterns is associated with the level of serotonin in peripheral blood in adolescents. On the background of a higher level of serotonin in the blood, compared to girls, boys have localized associations of theta and beta1 activity of EEG and serotonin levels, mainly in the right frontal-temporal region. In girls, the spectral power level of the EEG theta activity is more dependent on the level of serotonin in the blood, and a greater number of brain areas are involved in correlation interactions in comparison with young men (temporal regions on the left and frontal, central, parietal regions of both hemispheres of the brain).

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Poskotinova, L. V., E. V. Krivonogova, N. M. Khasanova, and M. N. Krasnikova. "The Predictability of Motor and Cognitive Impairment According to Brain Asymmetry of Cognitive Evoked Potentials P300 and Features of Symptom Complex in Patients with Parkinson’s Disease." Annals of the Russian academy of medical sciences 71, no. 1 (November 19, 2015): 41–45. http://dx.doi.org/10.15690/vramn519.

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Link the degree of progression of motor and cognitive impairment in Parkinson’s disease and parameters of cognitive evoked potentials brain activity recognized not always unambiguous. This is due to the wide range of differences in amplitude and latency time of evoked potentials in the different leads of electroencephalogram caused functional reorganization of neuronal activity in brain structures in the early stages of the disease. Objective. The aim is to determine the correlation of the cognitive auditory evoked potentials P300 characteristics and symptom features in patients with Parkinson’s disease. Methods. The study involved 60 people, right-handers: 34 people (24 women and 10 men) with a verified diagnosis of Parkinson’s disease and the control group — 26 people (20 women and 6 men). The disease duration, severity of symptoms (Unified Parkinson’s Disease Rating Scale), and stage of the disease (Hoehn, Yahr) were determined, the 15-item Geriatric Depression Scale was used to indicate the depression symptoms. Assessment of the electroencephalogram and auditory evoked potentials P300 was performed by an electroencephalograph «Encephalan» (Medicom, Taganrog, Russia). The minimum amplitude and the maximum latency of P300 in electroencephalogram-leads (F3, F4, C3, C4, P3, P4, F7, F8, T3, T4, T5 and T6) on the right and left sides were determined. Results. A significant positive correlation between the amplitude of evoked potential P300 on the left and duration of Parkinson’s disease was revealed, moreover the severity of disease symptoms such as left-side resting tremors of the hand, left-side muscle tension of the hand and/or foot, rising from a chair without using their hands, posture disorder were established. Conclusion. Marked brain asymmetry in the form of increase of the P300 amplitude on the left side combined with a significant reduction in the P300 amplitude on the right side in contra lateral electroencephalogram-lead indicates unfavorable prognosis in relation to cognitive dysfunction and motor disorders identified with left-sided Parkinson’s disease onset.

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Ashwal, Stephen, and Sanford Schneider. "Brain Death in the Newborn." Pediatrics 84, no. 3 (September 1, 1989): 429–37. http://dx.doi.org/10.1542/peds.84.3.429.

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The clinical courses of 18 preterm and term infants less than 1 month of age in whom brain death was diagnosed were retrospectively reviewed. Clinical diagnosis was determined neurologically and included (1) coma, (2) apnea, manifested by inability to sustain respiration, and (3) absent brainstem reflexes. Electroencephalograms were performed in all patients; 17 patients had adequate cerebral blood flow as estimated by radionuclide imaging. The results indicate that (1) neurodiagnostic tests such as electroencephalograms and radionuclide scanning reconfirmed clinically determined brain death in only one half to two thirds of patients; (2) electrocerebral silence in the absence of barbiturates, hypothermia, or cerebral malformations during 24 hours was confirmatory of brain death if the clinical findings remained unchanged; (3) absence of radionuclide uptake associated with initial electrocerebral silence was associated with brain death; (4) term infants clinically brain dead for 2 days and preterm infants brain dead for 3 days did not survive despite electroencephalogram or cerebral blood flow status; and (5) phenobarbital levels > 25 µg/ mL may suppress electroencephalographic activity in this age group. The findings suggest that determination of brain death in the newborn can be made solely by using clinical criteria. Confirmatory neurodiagnostic studies are of value because they can potentially shorten the period of observation.

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Nunez, Paul, and Ramesh Srinivasan. "Electroencephalogram." Scholarpedia 2, no. 2 (2007): 1348. http://dx.doi.org/10.4249/scholarpedia.1348.

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Valdés Sedeño, Raúl, Lilia Morales Chacón, and Abel Sánchez Coroneux. "Association Between Quantitative Electroencephalogram Frequency Composition and Post-Surgical Evolution in Pharmacoresistant Temporal Lobe Epilepsy Patients." Behavioral Sciences 9, no. 3 (March 4, 2019): 23. http://dx.doi.org/10.3390/bs9030023.

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The purpose of this paper is to estimate the association between quantitative electroencephalogram frequency composition (QEEGC) and post-surgical evolution in patients with pharmacoresistant temporal lobe epilepsy (TLE) and to evaluate the predictive value of QEEGC before and after surgery. A prospective, longitudinal study was made at International Neurological Restoration Center, Havana, Cuba. Twenty-nine patients with TLE submitted to epilepsy surgery were evaluated before surgery, and six months and two years after. They were classified as unsatisfactory and satisfactory post-surgical clinical evolution using the Modified Engels Scale. Eighty-seven electroencephalograms with quantitative narrow- and broad-band measures were analyzed. A Mann Whitney test (p > 0.05) showed that QEEGC before surgery was similar between groups independently of two years post-surgical evolution. A Mann Whitney test (p ˂ 0.05) showed that subjects with two years satisfactory post-surgical evolution had greater alpha power compared to subjects with two years unsatisfactory post-surgical evolution that showed greater theta power. A Wilcoxon test (p ˂ 0.05) showed that alpha and theta power increased for two groups from pre-surgical state to post-surgical state. Logit regression (p ˂ 0.05) showed that six months after surgery, quantitative electroencephalogram frequency value with the greatest power at occipital regions shows predictive value for two years evolution. QEEGC can be a tool to predict the outcome of epilepsy surgery.

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Lee, Wankiun, and Jae-Moon Kim. "Dizziness in Patients with Vestibular Epilepsy." Research in Vestibular Science 22, no. 1 (March 15, 2023): 7–13. http://dx.doi.org/10.21790/rvs.2023.22.1.7.

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Objectives: Vestibular epilepsy refers to epilepsy in which vertigo is the sole or main symptom of a seizure. However, epilepsy is rarely considered as a differential diagnosis in patients complaining of dizziness. Here, we reviewed ten cases of vestibular epilepsy and analyzed the dizziness complained by the patient.Methods: In this study, the medical records of dizziness patients with epileptic discharges observed on electroencephalogram were retrospectively analyzed. Patients who had other obvious causes of dizziness, lacked a description of dizziness, or were not taking antiseizure medications were excluded. We finally recruited 10 patients, and investigated their dizziness characteristic, brain imaging tests, electroencephalograms, and blood test findings.Results: Patients with vestibular epilepsy usually felt dizzy abruptly while not moving, and often complained of dizziness in the form of spinning around or becoming dazed. Dizziness was short, usually between a few seconds and a few minutes, and the frequency of occurrence was variable, so there was no consistent trend. There were no abnormal findings in blood tests. In brain imaging test, most patients did not show significant abnormalities. The electroencephalographic abnormalities of the patients were mainly observed in the temporal lobe, and the dizziness they complained of improved when they started taking antiseizure medications.Conclusions: If a patient with dizziness complains of dizziness that occurs suddenly and lasts for a short time, early electroencephalogram should be considered to prevent the diagnosis of epilepsy from being overlooked or delayed.

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Babbysh, N. A. "Software Platform for Reading, Processing and Analyzing EEG Data." Programmnaya Ingeneria 14, no. 5 (May 23, 2023): 254–60. http://dx.doi.org/10.17587/prin.14.254-260.

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Electroencephalogram (EEG) data can be used in many different areas. For example, for diagnosing brain diseases, in brain computer interfaces, for conducting various studies, and much more. To apply EEG data, a large set of different algorithms for preprocessing and analyzing these data is needed. This paper describes a software platform containing a set of tools for automated processing of EEG signals and their analysis, including machine learning methods. The platform has a flexible architecture and consists of modules, which allows it to be used for various purposes. Data can be obtained both from files and directly from the electroencephalograph device in real time. The graphical interface provides a convenient way to configure the modules of the software. The software interface of client applications (API) makes it possible to use this platform to create prototypes of devices that use EEG data for their work.

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Pinheiro, Francisco Edes da Silva, Liliana Silva, and João-Batista Destro-Filho. "Morte encefálica no paciente adulto: uma revisão integrativa da literatura." Research, Society and Development 11, no. 16 (December 18, 2022): e598111638865. http://dx.doi.org/10.33448/rsd-v11i16.38865.

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Morte encefálica pode ser definida como o estado irreversível das funções cerebrais, considerando os hemisférios cerebrais como também o tronco encefálico. São exigidos dois exames que possam confirmar a ausência ou a cessação de atividades do tronco cerebral para diagnóstico de ME no Brasil. Foi utilizada a busca por meio de levantamento e análise crítica dos documentos publicados através das plataformas de busca da PubMed, Scielo e Lilacs. Foram utilizados os seguintes descritores: “Morte encefálica”, “diagnóstico”, “adulto” e “eletroencefalograma”, “brain death AND electroencephalogram”, “brain death AND noise AND electroencephalogram”, “electroencephalograms AND brain death” e “brain death AND electroencephalogram AND intensivecareunits”. A abertura do protocolo de ME deve englobar todos os pacientes que se apresentem como não perceptivos, em ausência de reatividade supra espinhal e em apneia persistente de causa conhecida, irreversível e capaz de causar tal fim, seguindo protocolo de observação em ambiente hospitalar. Para início da abertura de protocolo, é necessário que haja uma lesão encefálica de causa conhecida, irreversível e capaz de causar a ME, além de ausência de fatores tratáveis que possam confundir o diagnóstico, tratamento e observação em ambiente hospitalar pelo período mínimo descrito, temperatura corporal superior a 35° C, saturação arterial de oxigênio acima de 94% e pressão arterial sistólica maior ou igual a 100 mmHg. São utilizadas medidas para a avaliação do nível de consciência, como a escala de Glasgow, além de testes para a avaliação de atividade do tronco cerebral e o teste da apneia, que é obrigatório para tal diagnóstico. Dentre os testes gráficos, se fazem de extrema relevância o eletroencefalograma (EEG), a angiografia cerebral, a doppler fluxometria transcraniana de artérias cerebrais e a cintilografia, sendo o EEG considerado um método factível realizado à beira leito, de baixo custo e baixo risco ao paciente quando comparado à cintilografia e arteriografia. Para fins de diagnóstico no protocolo, o médico capacitado, com experiência, se responsabilizará pelo laudo final.

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Lai, Chi Qin, Haidi Ibrahim, Mohd Zaid Abdullah, Jafri Malin Abdullah, Shahrel Azmin Suandi, and Azlinda Azman. "Current Practical Applications of Electroencephalography (EEG)." Journal of Computational and Theoretical Nanoscience 16, no. 12 (December 1, 2019): 4943–53. http://dx.doi.org/10.1166/jctn.2019.8546.

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Electroencephalogram (EEG) is used to study the activities of human brain using instrument named electroencephalograph. The usage of EEG is now widened to many fields due to its great temporal resolution and other advantages. In this paper, a literature survey has been carried out to explore and categorize applications that have been invented from EEG. The literature survey is done on works from year 2011 up to the present. Three main research areas have been explored, which are medical applications, brain–computer interface and neuromarketing. In medical applications, EEG is used to detect brain abnormality, such as seizures or brain injury. As for BCI, many applications have been proposed for object control, object recognition, rehabilitation and human assistance. In neuromarketing, EEG is used to recognize consumers’ preference such as their preferable products or movies. This literature review shows that the research on EEG is still growing, and the area of applications are expanding.

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Zhang, Li-tang, Su-xia Zhang, and Song-di Wu. "Electroencephalogram Analysis." Clinical EEG and Neuroscience 45, no. 2 (September 4, 2013): 92–97. http://dx.doi.org/10.1177/1550059413488107.

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Deepeshwar, Singh, Dwivedi Krishna, Krishna Prasanna, Basavaraj Angadi, BikeshKumar Singh, and Shrivastava Anurag. "Heartfulness meditation alters electroencephalogram oscillations: An electroencephalogram study." International Journal of Yoga 15, no. 3 (2022): 205. http://dx.doi.org/10.4103/ijoy.ijoy_138_22.

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Kortelainen, Jukka, Eero Väyrynen, Usko Huuskonen, Jouko Laurila, Juha Koskenkari, Janne T. Backman, Seppo Alahuhta, Tapio Seppänen, and Tero Ala-Kokko. "Pilot Study of Propofol-induced Slow Waves as a Pharmacologic Test for Brain Dysfunction after Brain Injury." Anesthesiology 126, no. 1 (January 1, 2017): 94–103. http://dx.doi.org/10.1097/aln.0000000000001385.

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Abstract Background Slow waves (less than 1 Hz) are the most important electroencephalogram signatures of nonrapid eye movement sleep. While considered to have a substantial importance in, for example, providing conditions for single-cell rest and preventing long-term neural damage, a disturbance in this neurophysiologic phenomenon is a potential indicator of brain dysfunction. Methods Since, in healthy individuals, slow waves can be induced with anesthetics, the authors tested the possible association between hypoxic brain injury and slow-wave activity in comatose postcardiac arrest patients (n = 10) using controlled propofol exposure. The slow-wave activity was determined by calculating the low-frequency (less than 1 Hz) power of the electroencephalograms recorded approximately 48 h after cardiac arrest. To define the association between the slow waves and the potential brain injury, the patients’ neurologic recovery was then followed up for 6 months. Results In the patients with good neurologic outcome (n = 6), the low-frequency power of electroencephalogram representing the slow-wave activity was found to substantially increase (mean ± SD, 190 ± 83%) due to the administration of propofol. By contrast, the patients with poor neurologic outcome (n = 4) were unable to generate propofol-induced slow waves. Conclusions In this experimental pilot study, the comatose postcardiac arrest patients with poor neurologic outcome were unable to generate normal propofol-induced electroencephalographic slow-wave activity 48 h after cardiac arrest. The finding might offer potential for developing a pharmacologic test for prognostication of brain injury by measuring the electroencephalographic response to propofol.

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Ohene-Adjei, Michael, Sabrina Leone Begley, Richard Temes, and Michael Schulder. "Efficacy of continuous electroencephalogram for the management of altered mental status in the neurosurgical intensive care unit." Surgical Neurology International 14 (July 7, 2023): 235. http://dx.doi.org/10.25259/sni_409_2023.

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Background: Continuous electroencephalograms (cEEGs) are often used in the neurosurgical intensive care unit (NSICU) to detect subclinical seizures (SCSs) in patients with altered mental status (AMS). This retrospective study evaluated the efficacy of this approach for improving patient outcomes. Methods: We reviewed the records of 100 patients admitted to the NSICU between 2015 and 2020 who underwent continous electroencephalograms (cEEG) during workup of unexplained AMS. Patient outcomes were classified as positive (discharged), neutral (transfer of care), or negative (dead). Incidence of SCSs on cEEG and association with patient outcomes was analyzed with Chi-square analysis and relative risk (RR). Results: For the 99 included patients, median age was 62 years and 43% were female. About 15.2% had a known or newly diagnosed brain tumor. Outcomes were positive in 22 patients, neutral in four, and negative in 73. SCSs were detected in 15 patients, of whom 12 died, two were discharged, and one whose care was transferred. Chi-square association between SCS and outcome (P = 0.59) and RR of death associated with SCS diagnosis (1.1) was not significant. Conclusion: We found a lower incidence of SCSs (15.2%) than reported in the literature. In the absence of clinically evident seizures, continous cEEGs performed in the NSICU to determine the etiology of AMS did not yield an improvement in patient outcomes, and patients diagnosed and treated for SCS did not have statistically decreased risk of death. In summary, electroencephalogram monitoring for SCS is important but should not delay diagnosis and treatment of other, potentially life-threating etiologies of AMS.

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Kit, G. V. "ANALYSIS OF PEAK-WAVE DISCHARGES OF EEG WITH THE USE OF WAVELET TRANSFORMATIONS." Visnyk Universytetu “Ukraina”, no. 1 (28) 2020 (2020): 224–34. http://dx.doi.org/10.36994/2707-4110-2020-1-28-19.

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The method of analysis of electroencephalograms (EEG) on the basis of wavelet transformations is offered. Electroencephalogram (EEG) analysis is widely used in clinical practice for diagnosing such neurological diseases as epilepsy, Parkinson's disease and others. Traditional approaches to EEG analysis, generally accepted in the clinical diagnosis of diseases, are due to the fact that for a certain time after the stimulus, the EEG amplitudes are calculated at time intervals that depend on the frequency of signal quantization. Therefore, it is important to develop algorithms for classifying EEG signals using wavelet transforms. The analysis of peak-wave EEG discharges, which are indicators of the presence or absence of absence epilepsy, was performed. The EEG recording areas were decomposed into the main EEG frequency bands. Wavelet transform in combination with artificial neural networks makes it possible to implement a classifier based on the energy distribution of the components of the EEG signal. Determining the activity of individual components of EEG signals, as well as the materiality of the processes that take place in the sources of these waves, may be the subject of further research.

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Kreuzer, Matthias, Eberhard F. Kochs, Stefanie Pilge, Gudrun Stockmanns, and Gerhard Schneider. "Construction of the Electroencephalogram Player: A Device to Present Electroencephalogram Data to Electroencephalogram-Based Anesthesia Monitors." Anesthesia & Analgesia 104, no. 1 (January 2007): 135–39. http://dx.doi.org/10.1213/01.ane.0000249045.52690.e8.

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Gurskaya, O. E., V. N. Tsygan, and A. V. Mirolubov. "Quantitative electrophysiological pattern of neurodegeneration in encephalopathies of various origin." Bulletin of the Russian Military Medical Academy 20, no. 1 (March 15, 2018): 7–12. http://dx.doi.org/10.17816/brmma12189.

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Electrophysiological characteristics of patients with encephalopathy of different etiology are presented. Pathogenic mechanisms affecting the electroencephalographic pattern and quantitative components of electroencephalogram are discussed. The aim of the study was to determine a universal quantitative electrophysiological criterion for the evaluation of neurodegenerative changes in the brain of patients with encephalopathy. We analyzed the data of anamnesis, neurological examination, laboratory tests and electroencephalograms from 389 patients with encephalopathy of post-traumatic, infectious, vascular and mixed etiology. Spectral analysis of electroencephalograms was performed and the values of relative quantitative electrophysiological criterion - the ratio of spectral power in the alpha/theta ranges at rest and during the test with hyperventilation were counted. The ratio of spectral power in the alpha/theta ranges was the lowest in patients of older age group and low - in patients with encephalopathy of infectious etiology. The ratio of the spectral power in the alpha-theta ranges in patients with post-traumatic encephalopathy was significantly different depending on the severity of the traumatic brain injury - mild or moderate/severe. We studied the possibilities of practical application of selected electrophysiological criterion - the ratio of spectral power of rhythms in the alpha-theta ranges. We counted this criterion in 150 patients with encephalopathy for the effectiveness evaluation of the neuroprotective therapy with сortexin. The chosen electrophysiological criterion had proved its effectiveness in therapy monitoring in patients with encephalopathy. In this article we demonstrated the advantages of additional neuroprotective therapy with сortexin. Increase in spectral power of alpha rhythm and decrease in spectral power of slow-wave components in the electroencephalographic pattern characterizes successful neuroprotective therapy with neuropeptides, such as сortexin.

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Bottros, Michael M., Ben Julian A. Palanca, George A. Mashour, Ami Patel, Catherine Butler, Amanda Taylor, Nan Lin, and Michael S. Avidan. "Estimation of the Bispectral Index by Anesthesiologists." Anesthesiology 114, no. 5 (May 1, 2011): 1093–101. http://dx.doi.org/10.1097/aln.0b013e31820e7c5c.

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Background Processed electroencephalographic indices, such as the bispectral index (BIS), are potential adjuncts for assessing anesthetic depth. While BIS® monitors might aid anesthetic management, unprocessed or nonproprietary electroencephalographic data may be a rich source of information for clinicians. We hypothesized that anesthesiologists, after training in electroencephalography interpretation, could estimate the index of a reference BIS as accurately as a second BIS® monitor (twin BIS®) (Covidien Medical, Boulder, CO) when provided with clinical and electroencephalographic data. Methods Two sets of electrodes connected to two separate BIS® monitors were placed on the foreheads of 10 surgical patients undergoing general anesthesia. Electroencephalographic parameters, vital signs, and end-tidal anesthetic gas concentrations were recorded at prespecified time points, and were provided to two sets of anesthesiologists. Ten anesthesiologists received brief structured training in electroencephalograph interpretation and 10 were untrained. Although electroencephalographic waveforms and open-source processed electroencephalograph metrics were provided from the reference BIS®, both groups were blinded to BIS values and were asked to estimate BIS. Results The trained anesthesiologists averaged as close to or closer to the reference BIS® compared with the twin BIS® monitor for 34% of their BIS estimates versus 26% for the untrained anesthesiologists. Using linear mixed effects model analysis, there was a statistically significant difference between the trained and untrained anesthesiologists (P = 0.02), but no difference between the twin BIS® monitor and trained anesthesiologists (P = 0.9). Conclusion With limited electroencephalography training and access to clinical data, anesthesiologists can estimate the BIS almost as well as a second BIS® monitor. These results reinforce the potential utility of training anesthesia practitioners in unprocessed electroencephalogram interpretation.

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Kurtieva, Shadie. "CHANGES IN ELECTROENCEPHALOGRAM INDICATORS IN ADOLESCENTS WITH VEGETATIVE DYSFUNCTION." UZBEK MEDICAL JOURNAL Special issue, no. 3 (September 30, 2021): 17–20. http://dx.doi.org/10.26739/2181-0664-2021-si-3-3.

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This work is based on the results of a study of the assessment of physical parameters of the electroencephalogram in adolescents with autonomic dysfunction, depending on gender and the presence of perinatal pathology in the anamnesis. We examined 87 adolescents 12-18 years old with clinically and laboratory-instrumental confirmed dysfunction of the autonomic nervous system -autonomic dystonia syndrome (ADS). The average age of the clinical manifestation of ADS in girls was 12.2 ± 1.8 years, in boys -13.5 ± 2.1 years. As a result of the study, it was revealed that adolescents with a history of perinatal pathology have the maximum risk of disturbances in the processes of myocardial repolarization at the end of the recovery period after physical exertion, especially in females

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Kurtieva, Shadie. "CHANGES IN ELECTROENCEPHALOGRAM INDICATORS IN ADOLESCENTS WITH VEGETATIVE DYSFUNCTION." UZBEK MEDICAL JOURNAL Special issue, no. 3 (September 30, 2021): 17–20. http://dx.doi.org/10.26739/2181-0664-2021-si-3-3.

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This work is based on the results of a study of the assessment of physical parameters of the electroencephalogram in adolescents with autonomic dysfunction, depending on gender and the presence of perinatal pathology in the anamnesis. We examined 87 adolescents 12-18 years old with clinically and laboratory-instrumental confirmed dysfunction of the autonomic nervous system -autonomic dystonia syndrome (ADS). The average age of the clinical manifestation of ADS in girls was 12.2 ± 1.8 years, in boys -13.5 ± 2.1 years. As a result of the study, it was revealed that adolescents with a history of perinatal pathology have the maximum risk of disturbances in the processes of myocardial repolarization at the end of the recovery period after physical exertion, especially in females

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Савинов, В. Б., С. А. Ботман, В. В. Сапунов, В. А. Петров, И. Г. Самусев, and Н. Н. Шушарина. "Определение эмоционального состояния свёрточной нейронной сетью по данным электроэнцефалографии." Вестник Российского государственного медицинского университета, no. 3 (May 29, 2019): 34–38. http://dx.doi.org/10.24075/vrgmu.2019.037.

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Существующие методы определения эмоционального состояния, основанные на регистрации тональности голоса и мимики, не обладают достаточной точностью и специфичностью. Эти показатели можно повысить с помощью анализа биосигналов, которые не проходят через сознательные фильтры, для чего необходимо создание эффективного алгоритма определения эмоционального состояния на основании анализа электрофизиологических сигналов. Целью работы было провести бинарную классификацию валентности эмоционального состояния по данным электроэнцефалографии с использованием сверточной нейронной сети и сравнить эффективность ее работы с эффективностью метода случайного леса. В качестве подопытного был выбран здоровый 30-летний мужчина. В течение 10 сессий по 2 ч каждая с подопытного производили запись электроэнцефалограммы во время просмотра им специально сформированного набора видеофильмов. Полученный сигнал фильтровали, сегментировали и использовали для обучения классификаторов. При использовании сети удалось достичь значения F1-меры, равного 87%, что превышает показатель, полученный при использовании метода случайного леса с входными данными в виде вектора признаков (67%). Достигнутые результаты свидетельствуют о высокой перспективности применения нейронных сетей сверточного типа в общем, и предложенной архитектуры, в частности, для решения задач по распознаванию эмоционального состояния по данным электрофизиологических сигналов. Дальнейшие работы по развитию подхода могут быть направлены на оптимизацию архитектуры сети для расширения числа идентифицируемых классов, а также повышения обобщающей способности сети при работе с большим количеством испытуемых.

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Ju, Ming-Shaung, H. S. Cheng, C. W. Chen, W. Y. Hsu, C. C. K. Lin, and Y. N. Sun. "APPLICATIONS OF ELECTROMYOGRAM, ELECTROENCEPHALOGRAM AND ELECTRONEUROGRAM TO PROSTHESIS CONTROL." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2007.3 (2007): S2. http://dx.doi.org/10.1299/jsmeapbio.2007.3.s2.

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Sittiprapa, Wichian. "Electroencephalogram Technology Synopsis." Journal of Engineering and Applied Sciences 7, no. 6 (June 1, 2012): 395–98. http://dx.doi.org/10.3923/jeasci.2012.395.398.

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Golomolzina, Diana Rashidovna, Maxim Alexandrovich Gorodnichev, Evgeny Andreevich Levin, Alexander Nikolaevich Savostyanov, Ekaterina Pavlovna Yablokova, Arthur C. Tsai, Mikhail Sergeevich Zaleshin, et al. "Advanced Electroencephalogram Processing." International Journal of E-Health and Medical Communications 5, no. 2 (April 2014): 49–69. http://dx.doi.org/10.4018/ijehmc.2014040103.

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The study of electroencephalography (EEG) data can involve independent component analysis and further clustering of the components according to relation of the components to certain processes in a brain or to external sources of electricity such as muscular motion impulses, electrical fields inducted by power mains, electrostatic discharges, etc. At present, known methods for clustering of components are costly because require additional measurements with magnetic-resonance imaging (MRI), for example, or have accuracy restrictions if only EEG data is analyzed. A new method and algorithm for automatic clustering of physiologically similar but statistically independent EEG components is described in this paper. Developed clustering algorithm has been compared with algorithms implemented in the EEGLab toolbox. The paper contains results of algorithms testing on real EEG data obtained under two experimental tasks: voluntary movement control under conditions of stop-signal paradigm and syntactical error recognition in written sentences. The experimental evaluation demonstrated more than 90% correspondence between the results of automatic clustering and clustering made by an expert physiologist.

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Jallon, P. "Electroencephalogram and Epilepsy." European Neurology 34, no. 1 (1994): 18–23. http://dx.doi.org/10.1159/000119504.

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Schwartz, Arthur E. "Electroencephalogram and Anesthetics." Anesthesiology 129, no. 2 (August 1, 2018): 375. http://dx.doi.org/10.1097/aln.0000000000002288.

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Markand, Omkar N. "Electroencephalogram in Dementia." American Journal of EEG Technology 26, no. 1 (March 1986): 3–17. http://dx.doi.org/10.1080/00029238.1986.11080186.

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Kaibara, Masako, and Warren T. Blume. "The postictal electroencephalogram." Electroencephalography and Clinical Neurophysiology 70, no. 2 (August 1988): 99–104. http://dx.doi.org/10.1016/0013-4694(88)90109-5.

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Sheshadri, Veena, and Suparna Bharadwaj. "Continuous Electroencephalogram (cEEG)." Journal of Neurosurgical Anesthesiology 26, no. 4 (October 2014): 414–15. http://dx.doi.org/10.1097/ana.0000000000000055.

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Piryatinska, Alexandra. "Electroencephalogram-sleep study." Wiley Interdisciplinary Reviews: Computational Statistics 5, no. 4 (June 5, 2013): 326–33. http://dx.doi.org/10.1002/wics.1261.

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Kernich, Catherine A. "THE ELECTROENCEPHALOGRAPH." Neurologist 7, no. 4 (July 2001): 261–62. http://dx.doi.org/10.1097/00127893-200107000-00006.

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Xavier, Gregory, Anselm Su Ting, and Norsiah Fauzan. "Quantifying Conventional Electroencephalogram Recordings and Examining its Output Computation with a Quantitative Electroencephalogram." Journal of Cognitive Sciences and Human Development 7, no. 2 (September 22, 2021): 108–20. http://dx.doi.org/10.33736/jcshd.3656.2021.

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Quantitative electroencephalogram enables mathematical analysis of neurological recordings while conventional electroencephalogram lacks the mathematical output; hence, its usage is limited to neurological experts. This study was to determine if quantified conventional electroencephalogram recordings were compatible and comparable with quantitative electroencephalogram recordings. A group of post-call doctors was recruited and subjected to an EEG recording using a conventional electroencephalogram followed by a quantitative electroencephalogram device. The patterns and quantified recording results were compared. A comparative analysis of the two recording sets did not find differences in the recording patterns and statistical analysis. The findings promoted the use of a readily available conventional electroencephalogram in quantitative brain wave studies and have cleared potential compatibility bias towards data merging.

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Katona, Jozsef, and A. Kovari. "EEG-based Computer Control Interface for Brain-Machine Interaction." International Journal of Online Engineering (iJOE) 11, no. 6 (November 5, 2015): 43. http://dx.doi.org/10.3991/ijoe.v11i6.5119.

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Recently more and more research methods are available to observe brain activity; for instance, Functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET), Transcranial Magnetic Stimulation (TMS), Near Infrared Spectroscopy (NIRS), Electroencephalograph (EEG) or Magnetoencephalography (MEG), which provide new research opportunities for several applications. For example, control methods based on the evaluation of measurable signals of human brain activity. In the past few years, more mobile EEG (electroencephalogram) based brain activity biosensor and signal processing devices have become available not only for medical examinations, but also to be used in different scopes; for instance, in control applications. These methods provide completely new possibilities in human-machine interactions by digital signal processing of brain signals. In this study, the program model, the establishment, the implementation and the test results of the quantitative EEG-based computer control interface, protocol and digital signal processing application are demonstrated. The user-friendly visualization of the evaluated brain wave signals is implemented in visual C# object-oriented language. This EEG-based control unit and interface provides an adequate basis for further research in different fields of brain-machine control methods regarding the examination of possible machine control applications.

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FAUST, OLIVER, U. RAJENDRA ACHARYA, LIM CHOO MIN, and BERNHARD H. C. SPUTH. "AUTOMATIC IDENTIFICATION OF EPILEPTIC AND BACKGROUND EEG SIGNALS USING FREQUENCY DOMAIN PARAMETERS." International Journal of Neural Systems 20, no. 02 (April 2010): 159–76. http://dx.doi.org/10.1142/s0129065710002334.

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The analysis of electroencephalograms continues to be a problem due to our limited understanding of the signal origin. This limited understanding leads to ill-defined models, which in turn make it hard to design effective evaluation methods. Despite these shortcomings, electroencephalogram analysis is a valuable tool in the evaluation of neurological disorders and the evaluation of overall cerebral activity. We compared different model based power spectral density estimation methods and different classification methods. Specifically, we used the autoregressive moving average as well as from Yule-Walker and Burg's methods, to extract the power density spectrum from representative signal samples. Local maxima and minima were detected from these spectra. In this paper, the locations of these extrema are used as input to different classifiers. The three classifiers we used were: Gaussian mixture model, artificial neural network, and support vector machine. The classification results are documented with confusion matrices and compared with receiver operating characteristic curves. We found that Burg's method for spectrum estimation together with a support vector machine classifier yields the best classification results. This combination reaches a classification rate of 93.33%, the sensitivity is 98.33% and the specificy is 96.67%.

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Yusoff, Nasir, Nik NurAzhani Anuar, Wan Nor Arifin, Tahamina Begum, and Faruque Reza. "Emotional Arousal Substrate in Relation to Eysenck Theory of Extraversion." International Journal of Engineering & Technology 7, no. 3.22 (August 8, 2018): 14. http://dx.doi.org/10.14419/ijet.v7i3.22.17115.

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Background: Eysenck theory posits that extraverts possess a trait of personality that is associated with personal enjoyment. Objectives: This study aims to examine the combination effect of extraversion and arousal intensity on the neural process of emotional arousal. Methods: This study was implemented in two parts – (1) Validation of Extraversion-Five Factor Non Verbal Personality Questionnaire (E-FF-NPQ) for personality screening, and (2) Event Related Potential (ERP)/electroencephalograph (EEG) recording session. In part one, the E-FF-NPQ was validated by 153 respondents, recruited from Universiti Sains Malaysia. In part two, after having their personality trait screened, electroencephalogram was recorded in 90 participants (N=30 for each personality) during the Event Related Potential session. Emotional arousal pictures that were taken randomly from the International Affective Picture System (IAPS) were used as visual stimuli and divided into three categories (high, moderate, low) based on the normative mean values of IAPS. Results: Interaction effect of the extraversion trait and emotional arousal intensity was detected in the frontal region as indicated by the latency of N200. Conclusion: The Theory of Eysenck on the connection between extraversion and well-being is almost supported.

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Wang, Kunkun, Xiaoling Lu, and Shan Sun. "Application of auditory mismatch negativity in tinnitus patients based on high-resolution electroencephalogram signals." Translational Neuroscience 13, no. 1 (January 1, 2022): 460–69. http://dx.doi.org/10.1515/tnsci-2022-0264.

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Abstract Objective The purpose of this study was to investigate the significance of mismatch negativity (MMN) by comparing high-resolution electroencephalogram signals from tinnitus patients and healthy controls. Methods The study included eight subjects with chronic subjective idiopathic tinnitus and seven healthy controls. Participants with clinical speech (512–2,000 Hz) hearing thresholds less than 25 dB HL and with negative Hospital Anxiety and Depression Scale scores were included in the study. The E-Prime 2.0 software and a 256-electrode EGI Net Station system were used to evoke and record the MMN signal, and the amplitude and latency parameters of the MMN responses were compared between the two groups. Results From 150 ms, there was a significant difference between the amplitude of standard stimulation and deviation stimulation, and the event-related potential amplitude under deviation stimulation in the tinnitus patient group was significantly different from that in the healthy group. The MMN amplitude of the FCz electrode was statistically significantly lower in the tinnitus patients compared to healthy controls. Conclusion MMN has application value in the evaluation of abnormal electrical activity in the auditory pathway, and electroencephalograms are feasible for follow-up monitoring after acoustic therapy.

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Venkatesan, K. G. S., Kishore Kumar Mamidala, and Swaroopa Rani B. "Detecting Optimal Regions for a Single EEG Channel Biometric System." International Journal of Scientific Methods in Engineering and Management 01, no. 07 (2022): 09–20. http://dx.doi.org/10.58599/ijsmem.2023.1702.

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Innovative security systems are increasingly making use of biometric modalities as an authentication method. However, the biometric technology that is presently available on the market provides solutions to a significant number of these difficulties. The widespread use of bogus biometrics in today’s society is one of the most significant reasons for concern. The results of an electroencephalogram (EEG) can provide some interesting information on the matter. This is a highly challenging endeavour since reproduction calls for careful preparation on your part. Several different investigations have shown that the procedure may be trusted to provide accurate results. Nonetheless, the collecting of data necessitates a large expenditure of time in addition to the sensors. In this study, we provide a biometric technique that takes use of EO resting-state EEG recordings that were taken from a single-channel electrode placement on the scalp. These recordings were generated in order to determine the precision of the method. The electroencephalograms (EEGs) of all nine persons who were examined yielded a total of 45 different signals. The interval of time that passed between each EEG wave segment was under five seconds. This specific piece of study focused its attention on the

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Purdon, Patrick L., Aaron Sampson, Kara J. Pavone, and Emery N. Brown. "Clinical Electroencephalography for Anesthesiologists." Anesthesiology 123, no. 4 (October 1, 2015): 937–60. http://dx.doi.org/10.1097/aln.0000000000000841.

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Abstract The widely used electroencephalogram-based indices for depth-of-anesthesia monitoring assume that the same index value defines the same level of unconsciousness for all anesthetics. In contrast, we show that different anesthetics act at different molecular targets and neural circuits to produce distinct brain states that are readily visible in the electroencephalogram. We present a two-part review to educate anesthesiologists on use of the unprocessed electroencephalogram and its spectrogram to track the brain states of patients receiving anesthesia care. Here in part I, we review the biophysics of the electroencephalogram and the neurophysiology of the electroencephalogram signatures of three intravenous anesthetics: propofol, dexmedetomidine, and ketamine, and four inhaled anesthetics: sevoflurane, isoflurane, desflurane, and nitrous oxide. Later in part II, we discuss patient management using these electroencephalogram signatures. Use of these electroencephalogram signatures suggests a neurophysiologically based paradigm for brain state monitoring of patients receiving anesthesia care.

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Millichap, J. Gordon. "Surfactant and Neonatal Electroencephalogram." Pediatric Neurology Briefs 26, no. 9 (September 1, 2012): 71. http://dx.doi.org/10.15844/pedneurbriefs-26-9-9.

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Oka, Eiji. "The Electroencephalogram of Epilepsy." Journal of the Japan Epilepsy Society 18, no. 2 (2000): 103–13. http://dx.doi.org/10.3805/jjes.18.103.

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Journal articles on the topic 'ELECTROENCEPHALOGRA'

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