scholarly journals The Status of Textile-Based Dry EEG Electrodes

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Granch Berhe Tseghai ◽  
Benny Malengier ◽  
Kinde Anlay Fante ◽  
Lieva Van Langenhove
Keyword(s):  
Neurological Disorders ◽  
Continuous Monitoring ◽  
Brain Activity ◽  
Conductive Polymer ◽  
Clinical Applications ◽  
Actual Application ◽  
The Status ◽  
Patients With Epilepsy ◽  
Published Research ◽  
Electroencephalogram Eeg

AbstractElectroencephalogram (EEG) is the biopotential recording of electrical signals generated by brain activity. It is useful for monitoring sleep quality and alertness, clinical applications, diagnosis, and treatment of patients with epilepsy, disease of Parkinson and other neurological disorders, as well as continuous monitoring of tiredness/ alertness in the field. We provide a review of textile-based EEG. Most of the developed textile-based EEGs remain on shelves only as published research results due to a limitation of flexibility, stickability, and washability, although the respective authors of the works reported that signals were obtained comparable to standard EEG. In addition, nearly all published works were not quantitatively compared and contrasted with conventional wet electrodes to prove feasibility for the actual application. This scenario would probably continue to give a publication credit, but does not add to the growth of the specific field, unless otherwise new integration approaches and new conductive polymer composites are evolved to make the application of textile-based EEG happen for bio-potential monitoring.

scholarly journals Electroencephalogram (EEG) Based Imagined Speech Decoding and Recognition

2021 ◽  
Vol 2 (2) ◽  
pp. 74-84
Author(s):  
Sani Saminu ◽  
Guizhi Xu ◽  
Zhang Shuai ◽  
Abd El Kader Isselmou ◽  
Adamu Halilu Jabire ◽  
...  
Keyword(s):  
Neurological Disorders ◽  
Brain Activity ◽  
Low Cost ◽  
High Temporal Resolution ◽  
Human Cortex ◽  
Prosthetic Devices ◽  
Neurological Processes ◽  
Electroencephalogram Eeg ◽  
Neuroprosthetic Devices ◽  
Neuroimaging Techniques

The recent investigations and advances in imagined speech decoding and recognition has tremendously improved the decoding of speech directly from brain activity with the help of several neuroimaging techniques that assist us in exploring the neurological processes of imagined speech. This development leads to assist people with disabilities to benefit from neuroprosthetic devices that improve the life of those suffering from neurological disorders. This paper presents the summary of recent progress in decoding imagined speech using Electroenceplography (EEG) signal, as this neuroimaging method enable us to monitor brain activity with high temporal resolution, it is very portable, low cost, and safer as compared to other methods. Therefore, it is a good candidate in investigating an imagined speech decoding from the human cortex which remains a challenging task. The paper also reviews some recent techniques, challenges, future recommendations and possible solutions to improve prosthetic devices and the development of brain computer interface system (BCI).

scholarly journals Monitoring electroconvulsive therapy by electroencephalogram: an update for ECT practitioners

2007 ◽  
Vol 13 (4) ◽  
pp. 298-304 ◽  
Author(s):  
Allan I. F. Scott
Keyword(s):  
Electroconvulsive Therapy ◽  
Seizure Activity ◽  
Eeg Monitoring ◽  
The Real ◽  
End Point ◽  
The Status ◽  
Published Research ◽  
Electroencephalogram Eeg

The purpose of this article is to update practitioners on the latest published research into the prevalence of prolonged cerebral seizure activity following electroconvulsive therapy (ECT). This research is drawing attention to the real practical challenges of recording and reading an electroencephalogram (EEG) tracing in the ECT clinic. In particular, determination of the seizure end-point is not always practicable and this poses a major problem in the detection and management of prolonged cerebral seizure activity. Some practical tips are suggested, and an update is given on the status of EEG monitoring in the assessment of seizure adequacy.

scholarly journals BRAIN COMPUTER INTERFACE APPLICATION IN STROKE DISEASE DIAGNOSIS

2016 ◽  
Vol 4 (7) ◽  
pp. 94-101
Author(s):  
Igwe J. S. ◽  
Inyiama ◽  
OgbuNwani Henry
Keyword(s):  
Brain Activity ◽  
Brain Computer Interface ◽  
Research Work ◽  
Disease Diagnosis ◽  
Computer Interface ◽  
Theta Wave ◽  
Brain Signals ◽  
The Status ◽  
Electroencephalogram Eeg ◽  
The Brain

Every discovery is geared towards problem solving. This is manifested by the advent of brain computer interface (BCI). Brain computer interface (BCI) is a field of study concern with the detection and utilization of brain signals in establishing the communication path between the brain and the computer system. The knowledge of this science has helped in no small measure in providing solutions to several challenges befalling man and his environment. In this paper, we explored those areas where BCI has proved useful and pointed out as well its possible application in diagnosis of stroke disease. The discourse was centered on detection of electrochemical signals from the brain called electroencephalogram (EEG). The research work also highlighted the technique of recording brain activity via electroencephalogram and using it in making deduction on the status of stroke attack on individual. This can either be normal or abnormal. The presence of delta or theta wave in an awaked adult suggests an abnormal situation. While the observance of alpha, beta and gamma waves are interpreted as normal.

CRITICAL DETERMINANTS OF HERITAGE PROPERTY VALUE: A CONCEPTUAL FRAMEWORK

2019 ◽  
Vol 17 (9) ◽  
Author(s):  
Normayuni Mat Zin ◽  
Suriatini Ismail ◽  
Junainah Mohamad ◽  
Nurul Hana Adi Maimun ◽  
Fatin Afiqah Md. Azmi
Keyword(s):  
Real Estate ◽  
Conceptual Framework ◽  
Structural Characteristics ◽  
Property Values ◽  
Property Value ◽  
Architectural Styles ◽  
Online Databases ◽  
The Status ◽  
Conference Papers ◽  
Published Research

Real estate is complex in nature, whereby its value is determined by many characteristics. Heritage property is different as compared with non-heritage property, thus; it is essential to identify the heritage property value determinants due to limited published research about it. This paper closes the gap by reviewing the literature to identify the determinants. To achieve this, academic journals and conference papers in online databases from 1974 to 2017 have been reviewed. The results indicated that there are four groups of heritage property value determinants namely; i) transaction characteristics, ii) structural characteristics, iii) spatial characteristics, and iv) historical characteristics. It can be concluded that heritage property values are differentiated by historical characteristics notably on their architectural styles or design and the status of the heritage property itself. This finding should be a useful guidance for the valuers in valuation practice.

scholarly journals AI MSK clinical applications: spine imaging

2021 ◽  
Author(s):  
Florian A. Huber ◽  
Roman Guggenberger
Keyword(s):  
Artificial Intelligence ◽  
Clinical Application ◽  
Value Chain ◽  
Clinical Applications ◽  
Status Quo ◽  
Use Cases ◽  
Musculoskeletal Imaging ◽  
Future Perspective ◽  
Spine Imaging ◽  
The Status

AbstractRecent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain in spine imaging, independent from modality or specific application. This review aims to summarize the status quo and future perspective regarding utilization of AI for spine imaging. First, the basics of AI concepts are clarified. Second, the different tasks and use cases for AI applications in spine imaging are discussed and illustrated by examples. Finally, the authors of this review present their personal perception of AI in daily imaging and discuss future chances and challenges that come along with AI-based solutions.

scholarly journals The relationship between fasting-induced torpor, sleep and waking in laboratory mice

SLEEP ◽  
2021 ◽  
Author(s):  
Yi-Ge Huang ◽  
Sarah J Flaherty ◽  
Carina A Pothecary ◽  
Russell G Foster ◽  
Stuart N Peirson ◽  
...  
Keyword(s):  
Body Temperature ◽  
Rem Sleep ◽  
Brain Activity ◽  
Mammalian Species ◽  
Nrem Sleep ◽  
Laboratory Mice ◽  
State Classification ◽  
Metabolic Suppression ◽  
The Relationship ◽  
Electroencephalogram Eeg

Abstract Study objectives Torpor is a regulated and reversible state of metabolic suppression used by many mammalian species to conserve energy. Whereas the relationship between torpor and sleep has been well-studied in seasonal hibernators, less is known about the effects of fasting-induced torpor on states of vigilance and brain activity in laboratory mice. Methods Continuous monitoring of electroencephalogram (EEG), electromyogram (EMG) and surface body temperature was undertaken in adult, male C57BL/6 mice over consecutive days of scheduled restricted feeding. Results All animals showed bouts of hypothermia that became progressively deeper and longer as fasting progressed. EEG and EMG were markedly affected by hypothermia, although the typical electrophysiological signatures of NREM sleep, REM sleep and wakefulness enabled us to perform vigilance-state classification in all cases. Consistent with previous studies, hypothermic bouts were initiated from a state indistinguishable from NREM sleep, with EEG power decreasing gradually in parallel with decreasing surface body temperature. During deep hypothermia, REM sleep was largely abolished, and we observed shivering-associated intense bursts of muscle activity. Conclusions Our study highlights important similarities between EEG signatures of fasting-induced torpor in mice, daily torpor in Djungarian hamsters and hibernation in seasonally-hibernating species. Future studies are necessary to clarify the effects on fasting-induced torpor on subsequent sleep.

AGE-BASED VARIATIONS OF FRACTAL STRUCTURE OF EEG SIGNAL IN PATIENTS WITH EPILEPSY

Fractals ◽  
2018 ◽  
Vol 26 (04) ◽  
pp. 1850051 ◽  
Author(s):  
HAMIDREZA NAMAZI ◽  
SAJAD JAFARI
Keyword(s):  
Fractal Dimension ◽  
Brain Research ◽  
Age Groups ◽  
Eeg Signal ◽  
Brain Disorders ◽  
Eeg Signals ◽  
Important Challenge ◽  
Patients With Epilepsy ◽  
Process Complexity ◽  
Electroencephalogram Eeg

It is known that aging affects neuroplasticity. On the other hand, neuroplasticity can be studied by analyzing the electroencephalogram (EEG) signal. An important challenge in brain research is to study the variations of neuroplasticity during aging for patients suffering from epilepsy. This study investigates the variations of the complexity of EEG signal during aging for patients with epilepsy. For this purpose, we employed fractal dimension as an indicator of process complexity. We classified the subjects in different age groups and computed the fractal dimension of their EEG signals. Our investigations showed that as patients get older, their EEG signal will be more complex. The method of investigation that has been used in this study can be further employed to study the variations of EEG signal in case of other brain disorders during aging.

scholarly journals Real-World Failure Prevention Framework for Manufacturing Facilities Using Text Data

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 676
Author(s):  
Jonghyuk Park ◽  
Eunyoung Choi ◽  
Yerim Choi
Keyword(s):  
Real World ◽  
Failure Pattern ◽  
Shop Floor ◽  
Manufacturing Companies ◽  
Text Data ◽  
Failure Prevention ◽  
Actual Application ◽  
The Status ◽  
Sensor Signals ◽  
Smart Factories

In recent years, manufacturing companies have been continuously engaging in research for the full implementation of smart factories, with many studies on methods to prevent facility failures that directly affect the productivity of the manufacturing sites. However, most studies have only analyzed sensor signals rather than text manually typed by operators. In addition, existing studies have not proposed an actual application system considering the manufacturing site environment but only presented a model that predicts the status or failure of the facility. Therefore, in this paper, we propose a real-world failure prevention framework that alerts the operator by providing a list of possible failure categories based on a failure pattern database before the operator starts work. The failure pattern database is constructed by analyzing and categorizing manually entered text to provide more detailed information. The performance of the proposed framework was evaluated utilizing actual manufacturing data based on scenarios that can occur in a real-world manufacturing site. The performance evaluation experiments demonstrated that the proposed framework could prevent facility failures and enhance the productivity and efficiency of the shop floor.

Epilepsy in Nicolaides–Baraitser Syndrome: Review of Literature and Report of 25 Patients Focusing on Treatment Aspects

2021 ◽  
Author(s):  
Benedikt Hofmeister ◽  
Celina von Stülpnagel ◽  
Cornelia Betzler ◽  
Francesca Mari ◽  
Alessandra Renieri ◽  
...  
Keyword(s):  
Neurodevelopmental Outcome ◽  
Initial Response ◽  
Clinical Findings ◽  
Generalized Seizures ◽  
Parent Support Group ◽  
Anticonvulsive Drugs ◽  
Epilepsy Classification ◽  
Structural Epilepsy ◽  
Patients With Epilepsy ◽  
Electroencephalogram Eeg

AbstractNicolaides–Baraitser syndrome (NCBRS), caused by a mutation in the SMARCA2 gene, which goes along with intellectual disability, congenital malformations, especially of face and limbs, and often difficult-to-treat epilepsy, is surveyed focusing on epilepsy and its treatment. Patients were recruited via “Network Therapy of Rare Epilepsies (NETRE)” and an international NCBRS parent support group. Inclusion criterion is NCBRS-defining SMARCA2 mutation. Clinical findings including epilepsy classification, anticonvulsive treatment, electroencephalogram (EEG) findings, and neurodevelopmental outcome were collected with an electronic questionnaire. Inclusion of 25 NCBRS patients with epilepsy in 23 of 25. Overall, 85% of the participants (17/20) reported generalized seizures, the semiology varied widely. EEG showed generalized epileptogenic abnormalities in 53% (9/17), cranial magnetic resonance imaging (cMRI) was mainly inconspicuous. The five most frequently used anticonvulsive drugs were valproic acid (VPA [12/20]), levetiracetam (LEV [12/20]), phenobarbital (PB [8/20]), topiramate (TPM [5/20]), and carbamazepine (CBZ [5/20]). LEV (9/12), PB (6/8), TPM (4/5), and VPA (9/12) reduced the seizures' frequency in more than 50%. Temporary freedom of seizures (>6 months) was reached with LEV (4/12), PB (3/8), TPM (1/5, only combined with PB and nitrazepam [NZP]), and VPA (4/12). Seizures aggravation was observed under lamotrigine (LTG [2/4]), LEV (1/12), PB (1/8), and VPA (1/12). Ketogenic diet (KD) and vagal nerve stimulation (VNS) reduced seizures' frequency in one of two each. This first worldwide retrospective analysis of anticonvulsive therapy in NCBRS helps to treat epilepsy in NCBRS that mostly shows only initial response to anticonvulsive therapy, especially with LEV and VPA, but very rarely shows complete freedom of seizures in this, rather genetic than structural epilepsy.

Data Acquisition and Data Processing using Electroencephalogram in Neuromarketing: A Review

2021 ◽  
Vol 30 (1) ◽  
pp. 19-33
Author(s):  
Annis Shafika Amran ◽  
Sharifah Aida Sheikh Ibrahim ◽  
Nurul Hashimah Ahamed Hassain Malim ◽  
Nurfaten Hamzah ◽  
Putra Sumari ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Linear Models ◽  
Brain Activity ◽  
Generative Models ◽  
Education Management ◽  
Latent Space ◽  
Latent Space Models ◽  
Cost Feasibility ◽  
Medical Healthcare ◽  
Electroencephalogram Eeg

Electroencephalogram (EEG) is a neurotechnology used to measure brain activity via brain impulses. Throughout the years, EEG has contributed tremendously to data-driven research models (e.g., Generalised Linear Models, Bayesian Generative Models, and Latent Space Models) in Neuroscience Technology and Neuroinformatic. Due to versatility, portability, cost feasibility, and non-invasiveness. It contributed to various Neuroscientific data that led to advancement in medical, education, management, and even the marketing field. In the past years, the extensive uses of EEG have been inclined towards medical healthcare studies such as in disease detection and as an intervention in mental disorders, but not fully explored for uses in neuromarketing. Hence, this study construes the data acquisition technique in neuroscience studies using electroencephalogram and outlines the trend of revolution of this technique in aspects of its technology and databases by focusing on neuromarketing uses.

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