Journal articles: 'Electroencephalography (EEG)'

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Politi, Keren, Sara Kivity, Hadassa Goldberg-Stern, Ayelet Halevi, and Avinoam Shuper. "Selective Mutism and Abnormal Electroencephalography (EEG) Tracings." Journal of Child Neurology 26, no. 11 (May 18, 2011): 1377–82. http://dx.doi.org/10.1177/0883073811406731.

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Epileptic discharges are not considered a part of the clinical picture of selective mutism, and electroencephalography is generally not recommended in its work-up. This report describes 6 children with selective mutism who were found to have a history of epilepsy and abnormal interictal or subclinical electroencephalography recordings. Two of them had benign epilepsy of childhood with centro-temporal spikes. The mutism was not related in time to the presence of active seizures. While seizures could be controlled in all children by medications, the mutism resolved only in 1. Although the discharges could be coincidental, they might represent a co-morbidity of selective mutism or even play a role in its pathogenesis. Selective mutism should be listed among the psychiatric disorders that may be associated with electroencephalographic abnormalities. It can probably be regarded as a symptom of a more complicated organic brain disorder.

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Farouk, Ayat Allah. "Digital electroencephalography and long-term video electroencephalography." Egyptian Journal of Internal Medicine 24, no. 1 (April 2012): 4. http://dx.doi.org/10.7123/01.ejim.0000415590.13433.52.

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AbstractEEG is the name commonly used for electroencephalography. EEG is an important test for diagnosing epilepsy. Conventional EEG has relatively low sensitivity in epilepsy, ranging between 25–56%. The combination of wake and sleep records gives a yield of 80% in patients with clinically confirmed epilepsy. Video-EEG is most helpful in determining whether seizures with unusual features are actually epilepsy.

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Gupta, Nidhi, and Gyaninder Singh. "Electroencephalography-based monitors." Journal of Neuroanaesthesiology and Critical Care 02, no. 03 (December 2015): 168–78. http://dx.doi.org/10.4103/2348-0548.165030.

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AbstractAn electroencephalogram (EEG), detects changes and abnormalities in the electrical activity of the brain and thus provides a way to dynamically assess brain function. EEG may be used to diagnose and manage a number of clinical conditions such as epilepsy, convulsive and non-convulsive status epilepticus, encephalitis, barbiturate coma, brain death, etc., EEG provides a large amount of information to the anaesthesiologist for routine clinical practice as depth of anaesthesia monitors and detection of sub-clinical seizures; and also for understanding the complex mechanisms of anaesthesia-induced alteration of consciousness. In the initial years, the routine clinical applicability of EEG was hindered by the complexity of the raw EEG signal. However, with technological advancement, several EEG-derived dimensionless indices have been developed that correlate with the depth of the hypnotic component of anaesthesia and are easy to interpret. Similarly, with the development of quantitative EEG tools, the routine use of continuous EEG is ever expanding in the Intensive Care Units. This review, describe various commonly used EEG-based monitors and their clinical applicability in the field of anaesthesia and critical care.

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Fenton, George W., and Kevin Standage. "The EEG in psychiatry." Psychiatric Bulletin 17, no. 10 (October 1993): 601–3. http://dx.doi.org/10.1192/pb.17.10.601.

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Although the EEG has been in constant clinical use for over 40 years, there have been surprisingly few systematic studies of the pattern of referral and clinical use of electroencephalography in a NHS psychiatric service. In view of the current concern about medical audit and cost effective use of special investigation facilities, it is an opportune time to audit the use of clinical electroencephalography in psychiatry. The current study examines the clinical use of electroencephalography in a district psychiatric service that provides comprehensive care for the population of Dundee (population 180,000).

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Qian, Xing, Hongwei Hao, Bozhi Ma, Xiongwei Wen, Chunhua Hu, and Luming Li. "Implanted rechargeable electroencephalography (EEG) device." Electronics Letters 50, no. 20 (September 2014): 1419–21. http://dx.doi.org/10.1049/el.2014.1820.

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Lee, MD, Ki Hwa. "Beyond the index of processed electroencephalography: a narrative review." Anaesthesia, Pain & Intensive Care 27, no. 1 (January 31, 2023): 112–18. http://dx.doi.org/10.35975/apic.v27i1.2128.

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There is a growing interest in monitoring the processed electroencephalography (p-EEG) as a measure of the delivery of anesthetic agent and the depth of the general anesthesia (GA). Each p-EEG monitor constructs an index that is suitable for GA. Although these monitors have become widely used, but it remains controversial whether they can become the gold standard for anesthesia monitoring like pulse oximeter and electrocardiogram. Whether p-EEG-guided anesthesia can affect perioperative outcomes remains unclear. This narrative review describes the relationship between p-EEG monitoring and perioperative outcome such as postoperative neurocognitive function, intraoperative awareness and mortality. Also, this article describes how and what to look beyond the index of processed electroencephalographic monitors. Abbreviations: GA: General anesthesia; EEG: Electroencephalogram; BIS: Bispectral index; POD: Postoperative delirium; CODA: Cognitive Dysfunction after Anaesthesia; POCD: Postoperative cognitive dysfunction; PACU: Post-anesthetic care unit; POQI-6: Perioperative Quality Initiative-6 Consensus Key words: Anesthesia; Delirium; Electroencephalography; Intraoperative awareness; Mortality Citation: Lee KH. Beyond the index of processed electroencephalography: a narrative review. Anaesth. pain intensive care 2022;27(1):112−118; DOI: 10.35975/apic.v27i1.2128 Received: April 07, 2022; Reviewed: August 16, 2022; Accepted: October 20, 2022

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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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Fonseca, Lineu Corrêa, and Gloria M. A. S. Tedrus. "Somatosensory-Evoked Spikes on Electroencephalography (EEG)." Clinical EEG and Neuroscience 43, no. 1 (January 2012): 14–17. http://dx.doi.org/10.1177/1550059411429530.

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Smith, R., M. Pitt, S. Boyd, and A. Worley. "P33.1 Interactive electroencephalography (EEG) web browser." Clinical Neurophysiology 117 (September 2006): 161. http://dx.doi.org/10.1016/j.clinph.2006.06.572.

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Büyükgöze, Selma. "NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY." International Conference on Technics, Technologies and Education, ICTTE 2019 (2019): 139–45. http://dx.doi.org/10.15547/ictte.2019.02.095.

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Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

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Yubiliana, Gilang, Raka Putra, and Andri Abdurrochman. "Q-EEG map of parietal and frontal lobes out of brain waves recording during dental hypnosis practice." Padjadjaran Journal of Dentistry 33, no. 3 (December 1, 2021): 258. http://dx.doi.org/10.24198/pjd.vol33no3.33382.

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Introduction: A patient with fear and anxiety is a common case to deal with for a dentist, therefore, dental hypnosis has been widely used to ease this situation. In a hypnotized state, the human brain may easily accept any suggestion. This is projected in the brain waves. Electroencephalograph (EEG) is a brain wave recording device, reflecting several states of consciousness. Beta for conscious, alpha and theta for subconscious, and delta for sleep. Dental hypnosis puts down beta waves to alpha or theta. Quantitative Electroencephalography (Q-EEG) or brain mapping is a comprehensive analysis of (Electroencephalography, EEG) in a colored topographic map, reflecting the brain's electrical activity. The objective of this article was reporting the parietal and frontal lobes activity during dental hypnosis based on the Q-EEG mapping. Methods: The research applied a quantitative research method using observatory study. The sample was taken with an accidental sampling method, with inclusion criteria, patients with dental anxiety and exclusion criteria was patients with special need and high level of dental anxiety. Data of the EEG records was taken in January-March 2018, and processed after in Pramita laboratorium Bandung. Results: Parietal lobe affected more during the inducement than temporal lobe. During dental hypnosis, the hypnotic markers (theta and alpha states) observed from the EEG were found to be more reactive. Conclusion: Dental hypnosis effects can be observed easily using Quantitative Electroencephalography method. Dental hypnosis affects brainwaves and brain mapping which indicate relaxations of brain waves especially on parietal lobes.

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D'Souza, Delon, Gosala R. K. Sarma, and Elizabeth V. T. "Teaching Electroencephalography: Persistent Altered Sensorium with Ominous Appearing Electroencephalographic Activity." International Journal of Epilepsy 05, no. 02 (October 2018): 110–11. http://dx.doi.org/10.1055/s-0038-1676560.

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AbstractA 51-year-old man presented with persistent altered sensorium following a seizure. His magnetic resonance imaging (MRI) showed features of focal encephalitis involving the left temporal, parietal, and occipital regions. His electroencephalogram (EEG) showed ongoing epileptiform discharges over the left hemisphere. This article discusses dilemmas in the diagnosis of nonconvulsive status epilepticus in such a case scenario.

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Ucar, Omur, and Murat Atan. "Determination of odor profile of university students using electroencephalography (EEG)." New Trends and Issues Proceedings on Humanities and Social Sciences 2, no. 1 (February 19, 2016): 36–46. http://dx.doi.org/10.18844/gjhss.v2i1.275.

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Khakim, Zulfikri, and Sri Kusrohmaniah. "Dasar - Dasar Electroencephalography (EEG) bagi Riset Psikologi." Buletin Psikologi 29, no. 1 (June 28, 2021): 92. http://dx.doi.org/10.22146/buletinpsikologi.52328.

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Electroencephalography (EEG) merupakan metode untuk merekam aktivitas elektris otak pada permukaan kulit kepala. EEG merekam fluktuasi potensial elektris yang muncul sebagai akibat dari aktivitas sel-sel otak. Seiring dengan kemajuan penelitian dan semakin canggih alat ukur, EEG semakin banyak digunakan dalam penelitian mengenai fungsi kognitif. Artikel ini bertujuan untuk menjelaskan pengantar teoretis mengenai alat EEG serta proses dalam analisis data untuk konteks penelitian dan eksperimen dalam kajian ilmu psikologi maupun ilmu sosial secara umum. Bagian awal mendeskripsikan mengenai dasar neural dan asumsi pengukuran dalam EEG, yang diikuti dengan penjelasan mengenai komponen-komponen alat EEG dan standar pemasangan. Bagian kedua menjelaskan mengenai pemrosesan sinyal yang memberikan contoh berbagai artefak yang merusak kualitas data EEG, serta beberapa metode dalam melakukan koreksi artefak yang umum digunakan. Ekstraksi fitur menjelaskan beberapa contoh metode dalam mengolah data EEG untuk kemudian fitur tersebut diasosiasikan dengan perilaku, proses mental atau aktivitas otak.

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Kim, Hong Jin, Sang Yeon Kim, Hyun Goo Kang, and Han Uk Ryu. "Revised Electroencephalography Terminology and Clinical Consideration." Journal of the Korean Neurological Association 40, no. 2 (May 1, 2022): 99–120. http://dx.doi.org/10.17340/jkna.2022.2.1.

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Electroencephalography (EEG) has been used for decades to evaluate and assess brain function. It is a useful method to diagnose brain disorders. However, confirmed interpretation of EEG is quite challenging because there is no standardized method for EEG reading and this may lead to interrater variability even among expert electroencephalographers. In this background, uniformly accepted nomenclature for EEG pattern were required to improve interrater agreement and to support communication for EEG research. American Clinical Neurophysiology Society (ACNS) established the standardized critical care EEG terminology since 2012 and has recently published the revised 2021 version of EEG terminology. This review covers new concepts of 2021 ACNS EEG terminology and clinical considerations of various EEG patterns.

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Koshchavtsev, A. G., and S. V. Grechanyi. "Interpretation of electroencephalography in infants." Epilepsy and paroxysmal conditions 12, no. 1 (April 16, 2020): 9–25. http://dx.doi.org/10.17749/2077-8333.2020.12.1.9-25.

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Aim: Based on published reports and our own observations, we aimed to assign the graphical elements of EEG into normal and abnormal groups and then identify up to five main graphic elements in each group to facilitate visual analysis and interpretation of EEG in young children.Materials and methods. We searched for the relevant sources in the Medline and Medscape databases using the following keywords: «neonatal EEG», «neonatal seizures», «theta burst», «delta brushes», «trace discontinue», «burst-suppression», hypsarrhythmia», etc. Our own research was conducted using an Encephalan-EEGR-19/26 encephalograph equipped with children size gold cup electrodes with a diameter of 0.6 cm. Encephalograms were recorded from 10 electrodes according to the international “10-20” system.Results and discussion. In early childhood EEGs, two large groups of EEG graphic elements can be discerned: the likely normative graphic elements and patterns of pediatric EEG (normal patterns) and the likely non-normative (abnormal) graphic elements and patterns of pediatric EEG. In the likely normative group, the main features are represented by: theta bursts, delta brushes, the “intermittent EEG curve” pattern, the occipital theta rhythm, and slow-sleep waves. In the likely non-normative group, those are: paroxysmal EEG graphic elements, asynchronous EEG patterns, spike-wave discharges, 3 Hz peak waves, hypsarrhythmia, burst-suppression pattern, rolandic occipital spikes, and a slowing rhythm pattern.Conclusion. Along with the numerous attempts to characterize the age-dependent graphic elements at an early age, there are few reports concerning older children and adults. Here we try to overcome this discrepancy by identifying two large groups of graphic elements in EEG that are similar between infants and children of an older age. Such an approach may contribute to a better understanding of normal and pathological ontogenesis.

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Eze, Chukwuemeka O., Olaronke F. Afolabi, Emeka O. Onwe, Richard L. Ewah, Ugochukwu U. Nnadozie, Francis C. Okoro, Eugene C. Nzei, and Chiamaka Okereke. "Electroencephalography: Experience at Abakaliki Nigeria." Global Journal of Health Science 13, no. 9 (August 11, 2021): 71. http://dx.doi.org/10.5539/gjhs.v13n9p71.

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BACKGROUND: Electroencephalography (EEG) remains the most important investigative modality in the evaluation of individuals with epilepsy and other neurological disorders. The pattern of EEG done in a tertiary hospital at Abakaliki Nigeria is not known. It is against this background that we embarked on this retrospective observational study on the EEG pattern and patient characteristics in Neurophysiology laboratory at Abakaliki Nigeria. METHOD: This is a retrospective observational hospital based study where the attendance register of the Neurophysiology laboratory was used to extract information on the demography, clinical characteristics and EEG reports of patients seen at the Laboratory from November 2018 to April 2021. RESULTS: A total of 125 (Male- 69, Female- 56) persons did EEG over the study period, and 75.2% had epileptiform waves (generalized- 16.8%, focal- 57.6%).  CONCLUSION: EEG services are been utilized at Abakaliki in evaluation of seizure disorder and other paroxysmal neurological events with more prevalent focal epileptiform waves.

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Soufineyestani, Mahsa, Dale Dowling, and Arshia Khan. "Electroencephalography (EEG) Technology Applications and Available Devices." Applied Sciences 10, no. 21 (October 23, 2020): 7453. http://dx.doi.org/10.3390/app10217453.

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The electroencephalography (EEG) sensor has become a prominent sensor in the study of brain activity. Its applications extend from research studies to medical applications. This review paper explores various types of EEG sensors and their applications. This paper is for an audience that comprises engineers, scientists and clinicians who are interested in learning more about the EEG sensors, the various types, their applications and which EEG sensor would suit a specific task. The paper also lists the details of each of the sensors currently available in the market, their technical specs, battery life, and where they have been used and what their limitations are.

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Höller, Yvonne. "Quantitative EEG in Cognitive Neuroscience." Brain Sciences 11, no. 4 (April 19, 2021): 517. http://dx.doi.org/10.3390/brainsci11040517.

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Kelleci, Ulker Anadol, Turan Calhan, Abdurrahman Sahin, Zeynep Aydin-Ozemir, Resul Kahraman, Kamil Ozdil, Haci Mehmet Sokmen, and Ayse Destina Yalcin. "Electroencephalography Findings in Crohn’s Disease." Clinical EEG and Neuroscience 50, no. 2 (April 30, 2018): 129–33. http://dx.doi.org/10.1177/1550059418767589.

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Objectives. Crohn’s Disease (CD) is a chronic systemic inflammatory disease associated with various extraintestinal manifestations, including seizure as a neurological finding. In this study, the prevalence of seizure and electroencephalographic abnormalities in patients with CD was investigated. Materials and Methods. This study involved 41 patients with CD (female/male: 25/16) and 39 subjects in the control group (female/male: 25/14). Patients in the CD group were diagnosed and monitored according to the European Crohn’s and Colitis Organization diagnostic criteria. The control group was composed of healthy subjects with similar age and sex as the CD group. Seizures were classified according to the criteria of the International League Against Epilepsy. Electroencephalography (EEG) was performed for all patients with CD and for healthy subjects. Seizure prevalence and EEG findings were also compared. Results. One patient in the CD group had history of seizures. EEG abnormality was significantly higher in the CD group (16/41, 39%) ( P = .001). The most common EEG abnormality was intermittent generalized slow wave abnormality in theta frequency. Discussion. Our study indicated that CD was associated with EEG abnormalities rather than seizure. The results also indicated that EEG was a potential indicator for detecting subclinical neurological abnormalities in CD.

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Ivanov, L. B. "Filtering in electroencephalography (lecture)." Medical alphabet 1, no. 14 (September 9, 2020): 39–44. http://dx.doi.org/10.33667/2078-5631-2020-14-39-44.

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Practical neurophysiology, as a rule, have limited knowledge of filtration in EEG. The author outlines the basic principles of filtering in electroencephalography, he clarifies the terminology, and explains the existing confusion in the concept of high and low frequency filters and analyzes the principles of selective filtering and possible errors in the interpretation of EEG with the wrong filtering mode selected.

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Sá, Catarina, Paulo Veloso Gomes, António Marques, and António Correia. "The Use of Portable EEG Devices in Development of Immersive Virtual Reality Environments for Converting Emotional States into Specific Commands." Proceedings 54, no. 1 (August 25, 2020): 43. http://dx.doi.org/10.3390/proceedings2020054043.

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The application of electroencephalography electrodes in Virtual Reality (VR) glasses allows users to relate cognitive, emotional, and social functions with the exposure to certain stimuli. The development of non-invasive portable devices, coupled with VR, allows for the collection of electroencephalographic data. One of the devices that embraced this new trend is Looxid LinkTM, a system that adds electroencephalography to HTC VIVETM, VIVE ProTM, VIVE Pro EyeTM, or Oculus Rift STM glasses to create interactive environments using brain signals. This work analyzes the possibility of using the Looxid LinkTM device to perceive, evaluate and monitor the emotions of users exposed to VR.

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Topor, Marta, Bertram Opitz, and Philip J. A. Dean. "In search for the most optimal EEG method: A practical evaluation of a water-based electrode EEG system." Brain and Neuroscience Advances 5 (January 2021): 239821282110536. http://dx.doi.org/10.1177/23982128211053698.

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The study assessed a mobile electroencephalography system with water-based electrodes for its applicability in cognitive and behavioural neuroscience. It was compared to a standard gel-based wired system. Electroencephalography was recorded on two occasions (first with gel-based, then water-based system) as participants completed the flanker task. Technical and practical considerations for the application of the water-based system are reported based on participant and experimenter experiences. Empirical comparisons focused on electroencephalography data noise levels, frequency power across four bands (theta, alpha, low beta and high beta) and event-related components (P300 and ERN). The water-based system registered more noise compared to the gel-based system which resulted in increased loss of data during artefact rejection. Signal-to-noise ratio was significantly lower for the water-based system in the parietal channels which affected the observed parietal beta power. It also led to a shift in topography of the maximal P300 activity from parietal to frontal regions. The water-based system may be prone to slow drift noise which may affect the reliability and consistency of low-frequency band analyses. Practical considerations for the use of water-based electrode electroencephalography systems are provided.

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Tran, Yvonne. "EEG Signal Processing for Biomedical Applications." Sensors 22, no. 24 (December 13, 2022): 9754. http://dx.doi.org/10.3390/s22249754.

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Samimisabet, Paria, Laura Krieger, Themis Nethar, and Gordon Pipa. "Introducing a New Mobile Electroencephalography System and Evaluating Its Quality in Comparison to Clinical Electroencephalography." Sensors 23, no. 17 (August 26, 2023): 7440. http://dx.doi.org/10.3390/s23177440.

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Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain’s electrical activity. Its applications include perception, learning, memory, language, decision making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named “DreamMachine” was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24 channels, 24-bit resolution, up to 6 h of battery life, portability, and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine’s design and compares it with the lab-based EEG system “asalabTM” in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system.

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Ekpar, Frank Edughom, and Felix Anayo Njoku. "Analysis of Electroencephalography (EEG) Electrode-Pair Correlations." European Journal of Electrical Engineering and Computer Science 7, no. 6 (November 6, 2023): 6–10. http://dx.doi.org/10.24018/ejece.2023.7.6.571.

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We measured electroencephalography (EEG) data streams from participants wearing a wireless EEG headset in two modes: eyes open and eyes closed. Then we analyzed the data by computing the correlation coefficients for a pair of electrodes in each measurement mode. We also plotted and visually inspected the associated scatter plots. We observed that for the electrodes selected, the signals were more strongly correlated in the eyes closed mode and relatively weakly correlated in the eyes open mode. In most measurements, the signals were dissimilar. These observations could be harnessed to inform expedient placement of EEG electrodes and efficient selection of data stream channels for further analysis.

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Gable, Philip A., Katharina Paul, Gilles Pourtois, and Jeffrey Burgdorf. "Utilizing electroencephalography (EEG) to investigate positive affect." Current Opinion in Behavioral Sciences 39 (June 2021): 190–95. http://dx.doi.org/10.1016/j.cobeha.2021.03.018.

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김헌민 and 황희. "Resting-State Electroencephalography (EEG) Functional Connectivity Analysis." Journal of the korean child neurology society 26, no. 3 (September 2018): 129–34. http://dx.doi.org/10.26815/jkcns.2018.26.3.129.

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Darbas, Marion, and Stephanie Lohrengel. "Review on Mathematical Modelling of Electroencephalography (EEG)." Jahresbericht der Deutschen Mathematiker-Vereinigung 121, no. 1 (July 11, 2018): 3–39. http://dx.doi.org/10.1365/s13291-018-0183-z.

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Zhao, Yifan, Fei He, and Yuzhu Guo. "EEG Signal Processing Techniques and Applications." Sensors 23, no. 22 (November 9, 2023): 9056. http://dx.doi.org/10.3390/s23229056.

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Sethi, N. K., J. Torgovnick, P. K. Sethi, and E. Arsura. "Cardiopulmonary Resuscitation Artifact during Electroencephalography." Clinical EEG and Neuroscience 39, no. 4 (October 2008): 214–16. http://dx.doi.org/10.1177/155005940803900413.

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Artifacts are signals recorded on the electroencephalogram (EEG) that are not cerebral in origin and can be divided into physiological and non-physiological artifacts. We present here an interesting non-physiological EEG artifact generated by cardiopulmonary resuscitation efforts.

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Watt, R. C., and S. R. Hameroff. "Phase space electroencephalography (EEG): A new mode of intraoperative EEG analysis." International Journal of Clinical Monitoring and Computing 5, no. 1 (March 1988): 3–13. http://dx.doi.org/10.1007/bf01739226.

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Reeves, Roy R., and Frederick A. Struve. "Quantitative Electroencephalography in Late-Onset Schizophrenia." International Psychogeriatrics 15, no. 3 (September 2003): 273–78. http://dx.doi.org/10.1017/s1041610203009529.

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Background and Objectives: A variety of electroencephalogram (EEG) abnormalities may occur in schizophrenics who had a typical onset of the disorder in early adulthood. The purpose of this study was to investigate EEG findings in patients with late-onset schizophrenia (onset of illness between ages 40 and 60). Methods: Ten patients (one male, nine female, average age 52.8 years old) with late-onset schizophrenia underwent magnetic resonance imaging (MRI) of the brain and recording of quantitative EEG. Results: MRI results for seven of the subjects were within normal limits and the other three showed nonspecific changes. Quantitative analysis of EEG variables revealed that for eight of the subjects, absolute power and relative power for the four EEG frequency bands, overall mean frequency, mean frequency for each of the EEG frequency bands, and interhemispheric coherence values did not vary significantly from a normative database of age-matched normal subjects. Conclusions: Results obtained to some degree replicate the single previous EEG study of late-onset schizophrenia. These findings suggest that the neurophysiological etiology and mechanism of late-onset schizophrenia may differ from that of schizophrenia with a typical age of onset, and that brain abnormalities are not an inevitable accompaniment to late onset of schizophrenia.

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Stankevich, Lev A., Sabina S. Amanbaeva, and Aleksandr V. Samochadin. "User Authentication by Electroencephalographic Signals when Blinkin." Computer tools in education, no. 3 (September 30, 2019): 52–69. http://dx.doi.org/10.32603/2071-2340-2019-3-52-69.

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The article presents the results of a study in the field of applying electroencephalography (EEG) for human authentication. An algorithm for EEG authentication based on blinks has been developed and described. Authentication is carried out by one blink, which takes 2-5 seconds. The data is collected using a Muse electroencephalograph. Data preprocessing includes wavelet transform and blink detection. Geometric characteristics of the EEG signals are used as features. Recognition is conducted by the Random Forest classifier. According to the test results, the percentage of correct authentication was 95 %. There is the possibility of background authentication. The implemented system may be used to authenticate students at distant education.

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Choi, Jee Hyun, Klaus Peter Koch, Wigand Poppendieck, Mina Lee, and Hee-Sup Shin. "High Resolution Electroencephalography in Freely Moving Mice." Journal of Neurophysiology 104, no. 3 (September 2010): 1825–34. http://dx.doi.org/10.1152/jn.00188.2010.

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Electroencephalography (EEG) is a standard tool for monitoring brain states in humans. Understanding the molecular and cellular mechanisms underlying diverse EEG rhythms can be facilitated by using mouse models under molecular, pharmacological, or electrophysiological manipulations. The small size of the mouse brain, however, poses a severe limitation in the spatial information of EEG. To overcome this limitation, we devised a polyimide based microelectrode array (PBM array) with nanofabrication technologies. The microelectrode contains 32 electrodes, weighs 150 mg, and yields noise-insensitive signals when applied on the mouse skull. The high-density microelectrode allowed both global and focused mapping of high resolution EEG (HR-EEG) in the mouse brain. Mapping and dynamical analysis tools also have been developed to visualize the dynamical changes of spatially resolved mouse EEG. We demonstrated the validity and utility of mouse EEG in localization of the seizure onset in absence seizure model and phase dynamics of abnormal theta rhythm in transgenic mice. Dynamic tracking of the EEG map in genetically modified mice under freely moving conditions should allow study of the molecular and cellular mechanisms underlying the generation and dynamics of diverse EEG rhythms.

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Zhang, Shufeng, Xuelei Feng, and Yong Shen. "Quantifying Auditory Presence Using Electroencephalography." Applied Sciences 11, no. 21 (November 7, 2021): 10461. http://dx.doi.org/10.3390/app112110461.

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Presence is used to assess the subjective experience of being in one place when physically situated in another. Recently, the research on presence has gained increasing attention due to the wide use of immersive audio technologies. Currently, the most widely-used measurement of presence is based on post-experiment self-report questionnaires. It is reliable but imperfect due to the psychological changes caused by the act of answering the questionnaire when immersed in the virtual environment. Therefore, the present work aims to find an objective way to measure presence, and electroencephalography (EEG) was investigated as a possible tool for this objective measurement. In this study, two listening tests were conducted, where eight loudspeakers were used to reproduce urban soundscapes to stimulate auditory presence. Presence was measured by both questionnaires and EEG. Results showed a significant correlation between T/B (Theta/Beta Ratio) extracted from EEG and subjective presence levels assessed by questionnaires, suggesting the possible use of EEG to measure presence objectively. This study could bring some insight for the research of presence, and related technologies, such as VR, video games and immersive audio production.

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Bone, Megan, Kimberly Goodspeed, and Deepa Sirsi. "Epilepsy and electroencephalography in Pitt-Hopkins syndrome." Journal of Translational Genetics and Genomics 6 (2022): 169–78. http://dx.doi.org/10.20517/jtgg.2021.56.

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Aim: Pitt-Hopkins syndrome (PTHS) is a rare neurodevelopmental disorder caused by mono-allelic loss of function variants of transcription factor 4 (TCF4), which plays a key role in early brain developmental and neuronal differentiation. Up to one-half of patients with PTHS will have epilepsy; however, little is known about the characteristic electroencephalogram (EEG) findings in this population. Because there is significant phenotypic overlap between PTHS and other neurodevelopmental disorders such as Angelman syndrome and Rett syndrome, which have characteristic EEG patterns, exploration of a potential EEG signature in patients with PTHS was warranted. Methods: We conducted a retrospective review of clinical EEGs in patients with PTHS. Results: In this cohort of patients with PTHS (n = 16), over half had abnormal EEGs; however, no characteristic EEG signature was identified. Further, all patients with epilepsy (5/16) had focal onset seizures with or without secondary generalization, and all five had focal abnormalities on EEG. There was no specific correlation between EEG results and developmental trajectories or age in our patient group, and there was no clear genotype-phenotype correlation. Conclusion: Although a distinctive EEG signature was not identified, all individuals with epilepsy in our cohort had focal onset seizures with corresponding focal epileptiform discharges or focal slowing on EEG. Future studies are needed to fully elucidate the spectrum of EEG findings in PTHS and explore the pathogenesis of focal seizures in a disorder of neuronal differentiation and development.

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Camfield, Peter, Kevin Gordon, Carol Camfield, John Tibbies, Joseph Dooley, and Bruce Smith. "EEG Results are Rarely the Same if Repeated within Six Months in Childhood Epilepsy." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 22, no. 4 (November 1995): 297–300. http://dx.doi.org/10.1017/s0317167100039512.

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AbstractObjectiveTo assess the reliability of interictal spike discharge in routine electroencephalography (EEG) testing in children.MethodEEG results of all children diagnosed in Nova Scotia with epilepsy onset between 1977–85 (excluding myoclonic, akinetic-atonic and absence) were reviewed. The results of the EEG at time of diagnosis (EEG1) were compared with those of a second EEG (EEG2) within 6 months.ResultsOf 504 children with epilepsy, 159 had both EEG1 and EEG2. EEG2 was more likely ordered if EEG1 was normal or showed focal slowing but less likely if EEG1 contained sleep (p < 0.05). EEG1 and EEG2 were both normal in 23%. If EEG1 was abnormal, there was a 40–70% discordance for the type of abnormality on EEG2. Abnormalities were present on both EEG1 and EEG2 in 67 cases. Of the 42/67 with major focal abnormalities on EEG1, 7 had only generalized spike wave on EEG2. Of the 17/67 with only generalized spike wave on EEG 1, 7 showed only major focal abnormalities on EEG2. Statistical testing showed low Kappa scores indicating low reliability.ConclusionsThe interictal EEG in childhood epilepsy appears to be an unstable test. A repeat EEG within 6 months of a first EEG may yield different and sometimes conflicting information.

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Sinkin, M. V., E. P. Bogdanova, and O. D. Elshina. "The crisis of quantitative electroencephalography. Is it a crisis? <i>Response to «Crisis of quantitative electroencephalography» by L. B. Ivanov</i>." Medical alphabet, no. 20 (October 30, 2022): 62–65. http://dx.doi.org/10.33667/2078-5631-2022-20-62-65.

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Electroencephalography (EEG) remain the key method to assess the functional state of the brain. In outpatient practice one of the most widespread EEG types is short-term or 'routine EEG', that means the registration of cerebral activity up to 30 minutes with carrying out of activation tests. The previously published 'Survey among Russian doctors on routine electroencephalography' has shown huge variability of methodology of routine EEG and caused a vibrant discussion. Thus, in the letter to editor 'Crisis of quantitative electroencephalography' by L. B. Ivanov, critical opinion was expressed about the requirement of such surveys, about the reference parameters of activation tests, and about insufficient education of functional diagnostic doctors, especially in the sphere of using quantitative EEG for diagnostics of psychiatric pathology.The manuscript presents new arguments regarding the expediency of a clear definition of the EEG terms and conditions and importance to develop official methodological guidelines for various EEG types in accordance with clinical guidelines.

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Höller, Yvonne, Christoph Helmstaedter, and Klaus Lehnertz. "Quantitative Pharmaco-Electroencephalography in Antiepileptic Drug Research." CNS Drugs 32, no. 9 (August 27, 2018): 839–48. http://dx.doi.org/10.1007/s40263-018-0557-x.

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Abstract Pharmaco-electroencephalography (pharmaco-EEG) has never gained great popularity in epilepsy research. Nevertheless, the electroencephalogram (EEG) is the most important neurological examination technique in this patient population. Development and investigation of antiepileptic drugs (AEDs) involves EEG for diagnosis and outcome evaluation. In contrast to the common use of the EEG for documenting the effect of AEDs on the presence of interictal epileptiform activities or seizures, quantitative analysis of drug responses in the EEG are not yet standard in pharmacological studies. We provide an overview of dedicated pharmaco-EEG studies with AEDs in humans. A systematic search in PubMed yielded 43 articles, which were reviewed for their relevance. After excluding studies according to our exclusion criteria, nine studies remained. These studies plus the retrieved references from the bibliographies of the identified studies yielded 37 studies to be included in the review. The most prominent method in pharmaco-EEG research for AEDs was analysis of the frequency content in response to drug intake, often with quantitative methods such as spectral analysis. Despite documenting the effect of the drug on brain activity, some studies were conducted in order to document treatment response, detect neurotoxic effects, and measure reversibility of AED-induced changes. There were some attempts to predict treatment response or side effects. We suggest that pharmaco-EEG deserves more attention in AED research, specifically because the newest drugs and techniques have not yet been subject to investigation.

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Hegerl, Ulrich, and Hans-Jürgen Möller. "Electroencephalography as a Diagnostic Instrument in Alzheimer's Disease: Reviews and Perspectives." International Psychogeriatrics 9, S1 (December 1997): 237–46. http://dx.doi.org/10.1017/s1041610297004948.

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Electroencephalography is the only diagnostic instrument directly reflecting cortical neuronal functioning, and it remains an important clinical tool in the diagnosis and differential diagnosis of Alzheimer's disease (AD). Although a normal EEG is found in many patients with mild AD, a pathological EEG is an important finding, because such a result is not in line with differential diagnoses such as depression or pseudodementia within a dissociative disorder. The vast majority of patients with moderate to servere AD have a pathological EEG. A normal EEG in this patient group is more in line with subcortical dementia or frontal lobe degeneration than with AD. Compared to SPECT or routine structural brain imaging (cCT, MRT), EEG has a comparable diagnosis sensitivity and a higher specificity. For monitoring changes of brain function by serial recordings (e.g., during therapy with antidementia drugs), EEG is the best available method.

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Huynh, Tuan Van, and Vu Quang Huynh. "Study on method of filtering noises from electroencephalography signals and its application for identification of several electroencephalography signals." Science and Technology Development Journal - Natural Sciences 1, T4 (December 31, 2017): 95–104. http://dx.doi.org/10.32508/stdjns.v1it4.497.

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Electroencephalographic (EEG) signals have usually been affected by different types of noise as 50 Hz noise, mechanical noise caused by body movements, heart disturbance, eye noise... In this paper, methods such as: independent component analysis (independent component analysis-ICA), discrete wavelet transform and design of digital filters, were used to filter the noises, to classify the basic components for EEG signals. Then the mean of energy value was calculated to identify the status of the EEG signals such as blink, thoughts, emotion, smoking and blood pressure. The results of calculations and simulations of signals EEG could demonstrate the efficiency of the method.

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Yuan, Lixue, Yinyan Fan, Quanxi Gan, and Huibin Feng. "Clinical Diagnosis of Psychiatry Based on Electroencephalography." Journal of Medical Imaging and Health Informatics 11, no. 3 (March 1, 2021): 955–63. http://dx.doi.org/10.1166/jmihi.2021.3338.

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At present, neurophysiological signals used for neuro feedback are EEG (Electroencephalogram), functional magnetic resonance imaging. Among them, the acquisition of EEG signals has the advantages of non-invasive way with low cost. It has been widely used in brain-machine interface technology in recent years. Important progress has been made in rehabilitation and environmental control. However, neural feedback and brainmachine interface technology are completely similar in signal acquisition, signal feature extraction, and pattern classification. Therefore, the related research results of brain-machine interface can be used to closely cooperate with clinical needs to research and develop neural feedback technology based on EEG. Based on neurophysiology and brain-machine interface technology, this paper develops a neural feedback training system based on the acquisition and analysis of human EEG signals. Aiming at the autonomous rhythm components in the EEG signal, such as sensorimotor rhythm and alpha rhythm, the characteristic parameters are extracted through real-time EEG signal processing to generate feedback information, and the subject is self-regulated and trained from a physiological-psychological perspective by providing adjuvant treatment, a practical and stable treatment platform for the clinic.

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Alkhorshid, Daniel Rostami, Seyyedeh Fatemeh Molaeezadeh, and Mikaeil Rostami Alkhorshid. "Analysis: Electroencephalography Acquisition System: Analog Design." Biomedical Instrumentation & Technology 54, no. 5 (September 1, 2020): 346–51. http://dx.doi.org/10.2345/0899-8205-54.5.346.

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Abstract Electroencephalography (EEG) is a sensitive and weak biosignal that varies from person to person. It is easily affected by noise and artifacts. Hence, maintaining the signal integrity to design an EEG acquisition system is crucial. This article proposes an analog design for acquiring EEG signals. The proposed design consists of eight blocks: (1) a radio-frequency interference filter and electro-static discharge protection, (2) a preamplifier and second-order high-pass filter with feedback topology and an unblocking mechanism, (3) a driven right leg circuit, (4) two-stage main and variable amplifiers, (5) an eight-order anti-aliasing filter, (6) a six-order 50-Hz notch filter (optional), (7) an opto-isolator circuit, and (8) an isolated power supply. The maximum gain of the design is approximately 94 dB, and its bandwidth ranges from approximately 0.18 to 120 Hz. The depth of the 50-Hz notch filter is −35 dB. Using this filter is optional because it causes EEG integrity problems in frequencies ranging from 40 to 60 Hz.

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Fenton, George W., and Kevin Standage. "Clinical Electroencephalography in a Psychiatric Service." Canadian Journal of Psychiatry 38, no. 5 (May 1993): 333–38. http://dx.doi.org/10.1177/070674379303800509.

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An audit of the use of clinical electroencephalography in a psychiatric service was carried out by examining the referrals for an EEG from the service over one year (11% of all referrals), comparing them with matched patient controls, rating the EEGs blindly and estimating the clinical value of the investigation for each patient; 37% were abnormal, 19% anomalous and 44% normal. The following two clusters of symptoms and signs were associated with EEG referral — the patients with “organic” mental state phenomena and/or CNS signs; EEG usually abnormal and the patients with behavioural changes that raise the suspicion of an organic process but, taken alone, are not compelling evidence of such (for example, impulsive behaviour, acute and atypical psychoses, perceptual or behavioural phenomena of the type associated with temporal lobe epilepsy in the absence of frank complex partial seizures); EEG usually normal or anomalous. Ninety-two percent of EEGs were judged to be of clinical value; 53% positive and 39% negative. Eight percent of referrals made no contribution to the clinical evaluation.

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Kumar, Pavan, Ahmed A. Abubakar, Awis Qurni Sazili, Ubedullah Kaka, and Goh Yong-Meng. "Application of Electroencephalography in Preslaughter Management: A Review." Animals 12, no. 20 (October 20, 2022): 2857. http://dx.doi.org/10.3390/ani12202857.

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Electroencephalography (EEG) can be reliable for assessing the brain’s electrical activity of preslaughter stress and pain. The duration between the ventral neck cut and induction of a state of unconsciousness/insensibility is crucial in the slaughtering of animals, reducing pain, fear, and distress. Various EEG variables, such as median frequency (F50), the total power of EEG spectrum (Ptot), waves patterns (amplitude and frequencies), epileptiform EEG, index of consciousness, and isoelectric EEG, are used to identify a valid indicator of the state of unconsciousness. Association among various behavioral, physiological, and hematological parameters with EEG variables could provide an overall assessment and deep insights into the animal stress levels or welfare status during various managemental and preslaughter operations, such as transport, stunning, and slaughtering operations. The application of EEG could help in further refining the stunning technologies and slaughter protocols in livestock, poultry, and fish. The present review analyzed the application of EEG as a neurophysiological tool for assessing animal welfare during the critical state of preslaughter handling and slaughter, thus ensuring proper compliance with animal welfare principles.

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Muthukumar, N., G. Thilagavathi, and T. Kannaian. "Polyaniline-coated foam electrodes for electroencephalography (EEG) measurement." Journal of The Textile Institute 107, no. 3 (April 7, 2015): 283–90. http://dx.doi.org/10.1080/00405000.2015.1028248.

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Kurlychek, Robert T. "Electroencephalography (EEG) in the differential diagnosis of dementia." Journal of Clinical Psychology 45, no. 1 (January 1989): 117–23. http://dx.doi.org/10.1002/1097-4679(198901)45:1<117::aid-jclp2270450118>3.0.co;2-x.

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Toderean, Roxana, Mihai Dimian, and Claudiu Cobuz. "EEG Changes Related to Gut Dysbiosis in Diabetes—Review." Applied Sciences 11, no. 24 (December 14, 2021): 11871. http://dx.doi.org/10.3390/app112411871.

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Humans are facing a devastating epidemic of metabolic syndrome that is linked to the worldwide dramatic increase in obesity and diabetes. Significant evidence suggests that the intestinal microbiota plays a major role in the pathogenesis of metabolic diseases. Due to the gut–brain axis link, dysbiosis in the gut microbiota have been demonstrated in both metabolic and neurological disease. Increasing evidence suggests that the gut microbiota is very important in maintaining health and changes in its composition may contribute to psychiatric and neurodegenerative disorders. It is also in research that changes in microbiota composition profile due to diabetes are modulated by the vagus nerve. Therefore, it is plausible that disruptions in the gut microbiota may be captured through electroencephalography signaling. Several studies which used standard methods of signal processing have highlighted some changes in electroencephalographic rhythms on patients with diabetes.

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Bogdanova, E. P., O. D. Elshina, and M. V. Sinkin. "Survey among Russian doctors on routine electroencephalography." Medical alphabet, no. 39 (December 21, 2021): 26–32. http://dx.doi.org/10.33667/2078-5631-2021-39-26-32.

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The aim of the work was to assess how accurately specialists, performing EEG, apply the recommendations in their daily practice.Materials and Methods. An anonymous survey was conducted of 210 specialists in functional diagnostics and neurologists performing routine electroencephalography. The survey consisted of nine mandatory single-choice questions.Results. Only 9 respondents out of 210 (4.3%) perform routine EEG completely in accordance with the Recommendations of the Expert Council of Neurophysiology of the Russian Anti-Epileptic League on performing the routine EEG.' Of these, only three specialists (1.4% of the total number of respondents) answered that a functional diagnostics doctor is present throughout the entire examination.Conclusion: Despite the wide distribution and extensive experience in the use of EEG, there is no uniform practice of its implementation by doctors in the Russian Federation. Standardization of the methodology of its performance will increase confidence in EEG results among doctors of clinical specialties, increase the degree of inter-expert agreement among functional diagnostics physicians, and improve the quality of diagnosis of central nervous system diseases. To do this, it is necessary to develop webinar and educational programs on the methodology of EEG under the auspices of professional associations of doctors of functional diagnostics, neurophysiologists, neurologists.

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Journal articles on the topic 'Electroencephalography (EEG)'

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