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A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison

Hamada M, Zaidan BB, Zaidan AA

J Med Syst, 2018 Jul 24;42(9):162.
PMID: 30043178 DOI: 10.1007/s10916-018-1020-8

The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept is limited. To extend research in this area, the researchers explored and analysed the academic articles published within the mentioned scope. Thus, in this paper a systematic review is carried out to map and draw the research scenery for EEG human emotion into a taxonomy. Systematically searched all articles about the, EEG human emotion based music in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 1999 to 2016. These databases feature academic studies that used EEG to measure brain signals, with a focus on the effects of music on human emotions. The screening and filtering of articles were performed in three iterations. In the first iteration, duplicate articles were excluded. In the second iteration, the articles were filtered according to their titles and abstracts, and articles outside of the scope of our domain were excluded. In the third iteration, the articles were filtered by reading the full text and excluding articles outside of the scope of our domain and which do not meet our criteria. Based on inclusion and exclusion criteria, 100 articles were selected and separated into five classes. The first class includes 39 articles (39%) consists of emotion, wherein various emotions are classified using artificial intelligence (AI). The second class includes 21 articles (21%) is composed of studies that use EEG techniques. This class is named 'brain condition'. The third class includes eight articles (8%) is related to feature extraction, which is a step before emotion classification. That this process makes use of classifiers should be noted. However, these articles are not listed under the first class because these eight articles focus on feature extraction rather than classifier accuracy. The fourth class includes 26 articles (26%) comprises studies that compare between or among two or more groups to identify and discover human emotion-based EEG. The final class includes six articles (6%) represents articles that study music as a stimulus and its impact on brain signals. Then, discussed the five main categories which are action types, age of the participants, and number size of the participants, duration of recording and listening to music and lastly countries or authors' nationality that published these previous studies. it afterward recognizes the main characteristics of this promising area of science in: motivation of using EEG process for measuring human brain signals, open challenges obstructing employment and recommendations to improve the utilization of EEG process.

Matched MeSH terms: Electroencephalography*
A generalized subspace approach for estimating visual evoked potentials

Kamel N, Yusoff MZ

Annu Int Conf IEEE Eng Med Biol Soc, 2008;2008:5208-11.
PMID: 19163891 DOI: 10.1109/IEMBS.2008.4650388

A "single-trial" signal subspace approach for extracting visual evoked potential (VEP) from the ongoing 'colored' electroencephalogram (EEG) noise is proposed. The algorithm applies the generalized eigendecomposition on the covariance matrices of the VEP and noise to transform them jointly into diagonal matrices in order to avoid a pre-whitening stage. The proposed generalized subspace approach (GSA) decomposes the corrupted VEP space into a signal subspace and noise subspace. Enhancement is achieved by removing the noise subspace and estimating the clean VEPs only from the signal subspace. The validity and effectiveness of the proposed GSA scheme in estimating the latencies of P100's (used in objective assessment of visual pathways) are evaluated using real data collected from Selayang Hospital in Kuala Lumpur. The performance of GSA is compared with the recently proposed single-trial technique called the Third Order Correlation (TOC).

Matched MeSH terms: Electroencephalography/methods*
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications

Kasabov N, Scott NM, Tu E, Marks S, Sengupta N, Capecci E, et al.

Neural Netw, 2016 Jun;78:1-14.
PMID: 26576468 DOI: 10.1016/j.neunet.2015.09.011

The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing modules. ECOS and eSTDM in particular can learn incrementally from data streams, can include 'on the fly' new input variables, new output class labels or regression outputs, can continuously adapt their structure and functionality, can be visualised and interpreted for new knowledge discovery and for a better understanding of the data and the processes that generated it. eSTDM can be used for early event prediction due to the ability of the SNN to spike early, before whole input vectors (they were trained on) are presented. A framework for building eSTDM called NeuCube along with a design methodology for building eSTDM using this is presented. The implementation of this framework in MATLAB, Java, and PyNN (Python) is presented. The latter facilitates the use of neuromorphic hardware platforms to run the eSTDM. Selected examples are given of eSTDM for pattern recognition and early event prediction on EEG data, fMRI data, multisensory seismic data, ecological data, climate data, audio-visual data. Future directions are discussed, including extension of the NeuCube framework for building neurogenetic eSTDM and also new applications of eSTDM.

Matched MeSH terms: Electroencephalography/methods
The Clinical Characteristics and Outcomes of Infantile Seizures in the First Year of Life: A Single-Center Study

Anuar MA, Zainal Abidin M', Tan SH, Yeap CF, Yahaya NA

Pediatr Neurol, 2024 Jan;150:10-14.
PMID: 37931500 DOI: 10.1016/j.pediatrneurol.2023.10.004

BACKGROUND: Epilepsy has a high incidence among infants during their first year of life, yet the prognosis can vary significantly. Although considerable research has been conducted on infantile spasms, studies examining infantile-onset epilepsy, excluding infantile spasms, remain limited, particularly concerning the factors influencing outcomes. Therefore, our study aims to elucidate seizure control, developmental outcomes, and prognostic factors in infants with epilepsy during their first year of life, within a single-center study in Malaysia.
METHODS: We retrieved data from patients who experienced seizures before age 12 months and were followed for over two years, using electronic patient records at Hospital Raja Perempuan Zainab II in Kelantan, a state in Malaysia's east coast. We retrospectively reviewed these records and assessed clinical outcomes based on the last follow-up.
RESULTS: Of 75 patients, 61 (81.3%) achieved good seizure control or remission. At the last follow-up, 24 (32%) exhibited developmental delay, whereas 19 (25.3%) displayed abnormal neuroimaging. Patients with abnormal background electroencephalographic (EEG) activity, as well as abnormal radiological findings, were more likely to experience poor seizure control and unfavorable developmental outcomes (P

Matched MeSH terms: Electroencephalography
Neural activation patterns and connectivity in visual attention during number and non-number processing: An ERP study using Ishihara pseudoisochromatic plates

Al-Marri F, Reza F, Begum T, Hitam WHW, Jin GK, Xiang J

J Integr Neurosci, 2018 Aug 15;17(3):257-269.
PMID: 30338955 DOI: 10.31083/JIN-170058

Visual cognitive function is important in the construction of executive function in daily life. Perception of visual number form (e.g. Arabic digits) and numerosity (numeric magnitude) is of interest to cognitive neuroscientists. Neural correlates and the functional measurement of number representations are complex events when their semantic categories are assimilated together with concepts of shape and color. Color perception can be processed further to modulate visual cognition. The Ishihara pseudoisochromatic plates are one of the best and most common screening tools for basic red-green color vision testing. However, there has been little study of visual cognitive function assessment using such pseudoisochromatic plates. 25 healthy normal trichromat volunteers were recruited and studied using a 128-sensor net to record event-related electroencephalogram. Subjects were asked to respond by pressing numbered buttons when they saw the number and non-number plates of the Ishihara color vision test. Amplitudes and latencies of N100 and P300 event related potential components were analyzed from 19 electrode sites in the international 10-20 system. A brain topographic map, cortical activation patterns, and Granger causation (effective connectivity) were analyzed from 128 electrode sites. No significant differences between N100 event related potential components for either stimulus indicates early selective attention processing was similar for number and non-number plate stimuli, but non-number plate stimuli evoked significantly higher amplitudes, longer latencies of the P300 event related potential component with a slower reaction time compared to number plate stimuli imply the allocation of attentional load was more in non-number plate processing. A different pattern of the asymmetric scalp voltage map was noticed for P300 components with a higher intensity in the left hemisphere for number plate tasks and higher intensity in the right hemisphere for non-number plate tasks. Asymmetric cortical activation and connectivity patterns revealed that number recognition occurred in the occipital and left frontal areas where as the consequence was limited to the occipital area during the non-number plate processing. Finally, results demonstrated that the visual recognition of numbers dissociates from the recognition of non-numbers at the level of defined neural networks. Number recognition was not only a process of visual perception and attention, but was also related to a higher level of cognitive function, that of language.

Matched MeSH terms: Electroencephalography
Fulltext The EEG and epilepsy in Kelantan--a hospital/laboratory-based study

Win MN

Med J Malaysia, 1993 Jun;48(2):153-9.
PMID: 8350790

Five hundred and ninety three cases of clinically diagnosed and suspected epilepsy were analysed as regards to the EEG (standard scalp electrode recording) features for confirmation and typing. Fifty-five per cent of all clinically diagnosed adult epileptics were confirmed by the EEG with the initial record, and the EEG confirmatory rate in children was higher at 92%. The frequency of generalised epilepsy as confirmed by the EEG was found to be 86% in adults and 92% in children, reflecting a higher proportion of generalised epilepsy in the population than reported elsewhere. Clinical diagnosis of partial epilepsy was often subsequently shown to be of generalised type on EEG.

Matched MeSH terms: Electroencephalography*
Fulltext Association Between Residual Inhibition and Neural Activity in Patients with Tinnitus: Protocol for a Controlled Within- and Between-Subject Comparison Study

Hu S, Anschuetz L, Huth ME, Sznitman R, Blaser D, Kompis M, et al.

JMIR Res Protoc, 2019 Jan 09;8(1):e12270.
PMID: 30626571 DOI: 10.2196/12270

BACKGROUND: Electroencephalography (EEG) studies indicate possible associations between tinnitus and changes in the neural activity. However, inconsistent results require further investigation to better understand such heterogeneity and inform the interpretation of previous findings.
OBJECTIVE: This study aims to investigate the feasibility of EEG measurements as an objective indicator for the identification of tinnitus-associated neural activities.
METHODS: To reduce heterogeneity, participants served as their own control using residual inhibition (RI) to modulate the tinnitus perception in a within-subject EEG study design with a tinnitus group. In addition, comparison with a nontinnitus control group allowed for a between-subjects comparison. We will apply RI stimulation to generate tinnitus and nontinnitus conditions in the same subject. Furthermore, high-frequency audiometry (up to 13 kHz) and tinnitometry will be performed.
RESULTS: This work was funded by the Infrastructure Grant of the University of Bern, Bern, Switzerland and Bernafon AG, Bern, Switzerland. Enrollment for the study described in this protocol commenced in February 2018. Data analysis is currently under way and the first results are expected to be submitted for publication in 2019.
CONCLUSIONS: This study design helps in comparing the neural activity between conditions in the same individual, thereby addressing a notable limitation of previous EEG tinnitus studies. In addition, the high-frequency assessment will help to analyze and classify tinnitus symptoms beyond the conventional clinical standard.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/12270.

Matched MeSH terms: Electroencephalography
The use of bispectral index during a cardiopulmonary arrest: a potential predictor of cerebral perfusion

Azim N, Wang CY

Anaesthesia, 2004 Jun;59(6):610-2.
PMID: 15144304

A 62-year-old male underwent off-pump coronary artery grafting surgery while cerebral function was monitored with bispectral index (BIS). The BIS monitoring was continued into the immediate postoperative period, during which time the patient experienced a cardiopulmonary arrest. The changes in the BIS values helped the resuscitating team in assessing the cerebral response to the cardiopulmonary resuscitation.

Matched MeSH terms: Electroencephalography*
Fulltext Effect of Muslim prayer (Salat) on α electroencephalography and its relationship with autonomic nervous system activity

Doufesh H, Ibrahim F, Ismail NA, Wan Ahmad WA

J Altern Complement Med, 2014 Jul;20(7):558-62.
PMID: 24827587 DOI: 10.1089/acm.2013.0426

OBJECTIVES: This study investigated the effect of Muslim prayer (salat) on the α relative power (RPα) of electroencephalography (EEG) and autonomic nervous activity and the relationship between them by using spectral analysis of EEG and heart rate variability (HRV).
METHODS: Thirty healthy Muslim men participated in the study. Their electrocardiograms and EEGs were continuously recorded before, during, and after salat practice with a computer-based data acquisition system (MP150, BIOPAC Systems Inc., Camino Goleta, California). Power spectral analysis was conducted to extract the RPα and HRV components.
RESULTS: During salat, a significant increase (p

Matched MeSH terms: Electroencephalography
Fulltext Epilepsy with myoclonic absences

Manonmani V, Wallace SJ

Arch Dis Child, 1994 Apr;70(4):288-90.
PMID: 8185360

The cases are described of eight children, five of them girls, who had epilepsy with myoclonic absences. The mean age of onset was 4.9 years. Brief episodes of loss of awareness with bilateral clonic jerking of the upper limbs were associated with rhythmic 3 cycles/second spike-wave discharges on electroencephalogram. Generalised tonic-clonic or astatic seizures, or both, also occurred in seven patients. All now have learning difficulties, and seven have behavioural problems. Conventional treatment for absences was effective in only two children. Of six patients treated with lamotrigine, five have improved substantially, but only one is in sustained complete remission. One recently diagnosed patient continues to have frequent myoclonic absences. As the response to treatment and long term outcome are much poorer, it is important to differentiate myoclonic absences from typical childhood absence epilepsy.

Matched MeSH terms: Electroencephalography
Empirical Wavelet Transform Based Features for Classification of Parkinson's Disease Severity

Oung QW, Muthusamy H, Basah SN, Lee H, Vijean V

J Med Syst, 2017 Dec 29;42(2):29.
PMID: 29288342 DOI: 10.1007/s10916-017-0877-2

Parkinson's disease (PD) is a type of progressive neurodegenerative disorder that has affected a large part of the population till now. Several symptoms of PD include tremor, rigidity, slowness of movements and vocal impairments. In order to develop an effective diagnostic system, a number of algorithms were proposed mainly to distinguish healthy individuals from the ones with PD. However, most of the previous works were conducted based on a binary classification, with the early PD stage and the advanced ones being treated equally. Therefore, in this work, we propose a multiclass classification with three classes of PD severity level (mild, moderate, severe) and healthy control. The focus is to detect and classify PD using signals from wearable motion and audio sensors based on both empirical wavelet transform (EWT) and empirical wavelet packet transform (EWPT) respectively. The EWT/EWPT was applied to decompose both speech and motion data signals up to five levels. Next, several features are extracted after obtaining the instantaneous amplitudes and frequencies from the coefficients of the decomposed signals by applying the Hilbert transform. The performance of the algorithm was analysed using three classifiers - K-nearest neighbour (KNN), probabilistic neural network (PNN) and extreme learning machine (ELM). Experimental results demonstrated that our proposed approach had the ability to differentiate PD from non-PD subjects, including their severity level - with classification accuracies of more than 90% using EWT/EWPT-ELM based on signals from motion and audio sensors respectively. Additionally, classification accuracy of more than 95% was achieved when EWT/EWPT-ELM is applied to signals from integration of both signal's information.

Matched MeSH terms: Electroencephalography
Fulltext Neurodevelopmental effects of childhood malnutrition: A neuroimaging perspective

Galler JR, Bringas-Vega ML, Tang Q, Rabinowitz AG, Musa KI, Chai WJ, et al.

Neuroimage, 2021 05 01;231:117828.
PMID: 33549754 DOI: 10.1016/j.neuroimage.2021.117828

Approximately one in five children worldwide suffers from childhood malnutrition and its complications, including increased susceptibility to inflammation and infectious diseases. Due to improved early interventions, most of these children now survive early malnutrition, even in low-resource settings (LRS). However, many continue to exhibit neurodevelopmental deficits, including low IQ, poor school performance, and behavioral problems over their lifetimes. Most studies have relied on neuropsychological tests, school performance, and mental health and behavioral measures. Few studies, in contrast, have assessed brain structure and function, and to date, these have mainly relied on low-cost techniques, including electroencephalography (EEG) and evoked potentials (ERP). The use of more advanced methods of neuroimaging, including magnetic resonance imaging (MRI) and functional near-infrared spectroscopy (fNIRS), has been limited by cost factors and lack of availability of these technologies in developing countries, where malnutrition is nearly ubiquitous. This report summarizes the current state of knowledge and evidence gaps regarding childhood malnutrition and the study of its impact on neurodevelopment. It may help to inform the development of new strategies to improve the identification, classification, and treatment of neurodevelopmental disabilities in underserved populations at the highest risk for childhood malnutrition.

Matched MeSH terms: Electroencephalography
Refractory seizures in a young army cohort

Loh NK, Lee WL, Yew WW, Tjia TL

Ann Acad Med Singap, 1997 Jul;26(4):471-4.
PMID: 9395813

This survey covered male Singapore citizens born in 1974 who were medically screened at the age of 18 years before enlistment for compulsory military service. Suspected epileptics were referred to government hospitals for further management. Out of 20,542 men, there were 121 epileptics, giving a cumulative incidence of 5 per 1000 by age 18 years. We had information on 106 (87%) of these individuals and were able to interview them and review their hospital records. Seventy-three of the 106 (69%) epileptics had generalised seizures while 14 (13%) had refractory seizures. There was no statistically significant racial bias amongst these epileptics. Unprovoked afebrile seizures occurred early in these patients, half of whom had seizures onset before 7 years of age. Nine refractory epileptics had a history of febrile seizures, 4 of which were complex febrile seizures. Magnetic resonance imaging identified mesial temporal sclerosis in 2 patients and a hypothalamic lesion in 1 patient. Computed tomographic scans revealed focal cortical atrophy in 2 patients. Nine other patients had normal imaging studies. Nine out of 14 (64%) patients with refractory epilepsy had partial seizures; 4 (29%) had generalised seizures and 1 (7%) was unclassified. This is in contrast to the distribution of the entire cohort of epileptics studied. Two out of 9 patients with refractory partial seizures (gelastic epilepsy and mesial temporal sclerosis) had undergone surgery while 6 of the other 7 patients refused to consider surgery.

Matched MeSH terms: Electroencephalography
Fulltext Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges

Lim JZ, Mountstephens J, Teo J

Sensors (Basel), 2020 Apr 22;20(8).
PMID: 32331327 DOI: 10.3390/s20082384

The ability to detect users' emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality.

Matched MeSH terms: Electroencephalography
Fulltext EEG-Based Emotion Recognition: A State-of-the-Art Review of Current Trends and Opportunities

Suhaimi NS, Mountstephens J, Teo J

Comput Intell Neurosci, 2020;2020:8875426.
PMID: 33014031 DOI: 10.1155/2020/8875426

Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing interest of the research community towards establishing some meaningful "emotional" interactions between humans and computers, the need for reliable and deployable solutions for the identification of human emotional states is required. Recent developments in using electroencephalography (EEG) for emotion recognition have garnered strong interest from the research community as the latest developments in consumer-grade wearable EEG solutions can provide a cheap, portable, and simple solution for identifying emotions. Since the last comprehensive review was conducted back from the years 2009 to 2016, this paper will update on the current progress of emotion recognition using EEG signals from 2016 to 2019. The focus on this state-of-the-art review focuses on the elements of emotion stimuli type and presentation approach, study size, EEG hardware, machine learning classifiers, and classification approach. From this state-of-the-art review, we suggest several future research opportunities including proposing a different approach in presenting the stimuli in the form of virtual reality (VR). To this end, an additional section devoted specifically to reviewing only VR studies within this research domain is presented as the motivation for this proposed new approach using VR as the stimuli presentation device. This review paper is intended to be useful for the research community working on emotion recognition using EEG signals as well as for those who are venturing into this field of research.

Matched MeSH terms: Electroencephalography*
Early visual analysis tool using magnetoencephalography for treatment and recovery of neuronal dysfunction

Rasheed W, Neoh YY, Bin Hamid NH, Reza F, Idris Z, Tang TB

Comput Biol Med, 2017 10 01;89:573-583.
PMID: 28551109 DOI: 10.1016/j.compbiomed.2017.05.005

Functional neuroimaging modalities play an important role in deciding the diagnosis and course of treatment of neuronal dysfunction and degeneration. This article presents an analytical tool with visualization by exploiting the strengths of the MEG (magnetoencephalographic) neuroimaging technique. The tool automates MEG data import (in tSSS format), channel information extraction, time/frequency decomposition, and circular graph visualization (connectogram) for simple result inspection. For advanced users, the tool also provides magnitude squared coherence (MSC) values allowing personalized threshold levels, and the computation of default model from MEG data of control population. Default model obtained from healthy population data serves as a useful benchmark to diagnose and monitor neuronal recovery during treatment. The proposed tool further provides optional labels with international 10-10 system nomenclature in order to facilitate comparison studies with EEG (electroencephalography) sensor space. Potential applications in epilepsy and traumatic brain injury studies are also discussed.

Matched MeSH terms: Electroencephalography
Fulltext Level 4 comprehensive epilepsy program in Malaysia, a resource-limited country

Lim, Kheng-Seang, Sherrini Ahmad Bazir Ahmad, Vairavan Narayanan, Kartini Rahmat, Norlisah Mohd Ramli, Mun, Kein-Seong, et al.

Neurology Asia, 2017;22(4):299-305.
MyJurnal

Background and Objective: There is a great challenge to establish a level 4 epilepsy care offering
complete evaluation for epilepsy surgery including invasive monitoring in a resource-limited country.
This study aimed to report the setup of a level 4 comprehensive epilepsy program in Malaysia and the
outcome of epilepsy surgery over the past 4 years.

Methods: This is a retrospective study analyzing
cases with intractable epilepsy in a comprehensive epilepsy program in University Malaya Medical
Center (UMMC), Kuala Lumpur, from January 2012 to August 2016.

Results: A total of 92 cases
had comprehensive epilepsy evaluation from January 2012 till August 2016. The mean age was 35.57
years old (range 15-59) and 54 (58.7%) were male. There were 17 cases having epilepsy surgery
after stage-1 evaluation. Eleven cases had mesial temporal sclerosis and 81% achieved Engel class
I surgical outcome. Six cases had lesionectomy and 60% had Engel class I outcome. A total of 16
surgeries were performed after stage-2 evaluation, including invasive EEG monitoring in 9 cases.
Among those with surgery performed more than 12 months from the time of data collection, 5/10
(50%) achieved Engel I outcome, whereas 2 (20%) had worthwhile improvement (Engel class III)
with 75% and 90% seizure reduction.

Conclusion: Level 4 epilepsy care has an important role and is possible with joint multidisciplinary
effort in a middle-income country like Malaysia despite resource limitation.

Matched MeSH terms: Electroencephalography
Characteristics of electroencephalogram changes and correlation with seizures in hospitalised patients

Satar SNA, Mogan S, Jaafar WPN, Maghalingam S, Affendi FAR, Ng CF, et al.

Med J Malaysia, 2023 Mar;78(2):149-154.
PMID: 36988523

INTRODUCTION: Electroencephalogram (EEG) is an important investigational tool that is widely used in the hospital settings for numerous indications. The aim was to determine factors associated with abnormal EEG and its clinical correlations in hospitalised patients.
MATERIALS AND METHODS: Patients with at least one EEG recording were recruited. The EEG and clinical data were collated.
RESULTS: Two hundred and fifty patients underwent EEG and 154 (61.6%) were found to have abnormal EEG. The abnormal changes consist of theta activity (79,31.6%), delta activity (20, 8%), focal discharges (41,16.4%) and generalised discharges (14, 5.6%). Older patients had 3.481 higher risk for EEG abnormalities, p=0.001. Patients who had focal seizures had 2.240 higher risk of having EEG abnormalities, p<0.001. Low protein level was a risk for EEG abnormalities, p=0.003.
CONCLUSION: This study emphasised that an abnormal EEG remains a useful tool in determining the likelihood for seizures in a hospital setting. The risk factors for EEG abnormality in hospitalised patients were age, focal seizures and low protein level. The EEG may have an important role as part of the workup in hospitalised patients to aid the clinician to tailor their management in a holistic manner.

Matched MeSH terms: Electroencephalography*
Neurology in Asia

Tan CT

Neurology, 2015 Feb 10;84(6):623-5.
PMID: 25666629 DOI: 10.1212/WNL.0000000000001224

Asia is important as it accounts for more than half of the world population. The majority of Asian countries fall into the middle income category. As for cultural traditions, Asia is highly varied, with many languages spoken. The pattern of neurologic diseases in Asia is largely similar to the West, with some disease features being specific to Asia. Whereas Asia constitutes 60% of the world's population, it contains only 20% of the world's neurologists. This disparity is particularly evident in South and South East Asia. As for neurologic care, it is highly variable depending on whether it is an urban or rural setting, the level of economic development, and the system of health care financing. To help remedy the shortage of neurologists, most counties with larger populations have established training programs in neurology. These programs are diverse, with many areas of concern. There are regional organizations serving as a vehicle for networking in neurology and various subspecialties, as well as an official journal (Neurology Asia). The Asian Epilepsy Academy, with its emphasis on workshops in various locations, EEG certification examination, and fellowships, may provide a template of effective regional networking for improving neurology care in the region.

Matched MeSH terms: Electroencephalography
Focal epilepsy recruiting a generalised network of juvenile myoclonic epilepsy: a case report

Khaing M, Lim KS, Tan CT

Epileptic Disord, 2014 Sep;16(3):370-4.
PMID: 25166001 DOI: 10.1684/epd.2014.0672

We report a patient with juvenile myoclonic epilepsy who subsequently developed temporal lobe epilepsy, which gradually became clinically dominant. Video telemetry revealed both myoclonic seizures and temporal lobe seizures. The temporal lobe seizures were accompanied by a focal recruiting rhythm with rapid generalisation on EEG, in which the ictal EEG pattern during the secondary generalised phase was morphologically similar to the ictal pattern during myoclonic seizures. The secondary generalised seizures of the focal epilepsy responded to sodium valproate, similar to the myoclonic epilepsy. In this rare case of coexistent Juvenile Myoclonic Epilepsy and Temporal lobe epilepsy, the possibility of focal epilepsy recruiting a generalised epileptic network was proposed and discussed.

Matched MeSH terms: Electroencephalography

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