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https://www.readbyqxmd.com/read/28237416/the-combined-effects-of-menstrual-cycle-phase-and-acute-stress-on-reward-related-processing
#1
Stella Banis, Monicque M Lorist
We investigated the combined effects of menstrual cycle phase and acute stress on reward-related processing, employing a monetary incentive delay task in combination with EEG. Females participated during late follicular and late luteal phases, performing in both control and stress conditions. We found evidence for both independent and interaction effects of phase and stress on reward-related brain activity. Phase modulated the sensitivity to feedback valence, with a stronger signaling of negative performance outcomes in the late follicular versus late luteal phase...
February 22, 2017: Biological Psychology
https://www.readbyqxmd.com/read/28235654/is-burned-out-hippocampus-syndrome-a-distinct-electro-clinical-variant-of-mtle-hs-syndrome
#2
Pradeep P Nair, Ramshekhar N Menon, Ashalatha Radhakrishnan, Ajit Cherian, Mathew Abraham, George Vilanilam, C Kesavadas, Bejoy Thomas, Aley Alexander, Sanjeev V Thomas
AIM: To study the clinical, electrophysiological and imaging characteristics of patients with unilateral mesial temporal lobe epilepsy (MTLE) with contralateral ictal onset on scalp EEG, viz. 'burned-out hippocampus' syndrome (MTLE-BHS). METHODS: MTLE-BHS was defined as TLE with unilateral hippocampal sclerosis (HS) without any dual pathology on MRI and contralateral ictal onset on scalp EEG, unlike in classical hippocampal sclerosis (HS). Consecutive "MTLE-BHS" patients evaluated at our Centre for Comprehensive Epilepsy Care from January 2005 to July 2014 were studied...
February 21, 2017: Epilepsy & Behavior: E&B
https://www.readbyqxmd.com/read/28231475/the-use-and-yield-of-continuous-eeg-in-critically-ill-patients-a-comparative-study-of-three-centers
#3
Vincent Alvarez, Andres A Rodriguez Ruiz, Suzette LaRoche, Lawrence J Hirsch, Christopher Parres, Paula E Voinescu, Andres Fernandez, Ognen A Petroff, Nishi Rampal, Hiba Arif Haider, Jong Woo Lee
OBJECTIVE: Continuous EEG (cEEG) monitoring of critically ill patients has gained widespread use, but there is substantial reported variability in its use. We analyzed cEEG and antiseizure drug (ASD) usage at three high volume centers. METHODS: We utilized a multicenter cEEG database used daily as a clinical reporting tool in three tertiary care sites (Emory Hospital, Brigham and Women's Hospital and Yale - New Haven Hospital). We compared the cEEG usage patterns, seizure frequency, detection of rhythmic/periodic patterns (RPP), and ASD use between the sites...
January 17, 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28227981/assessment-of-sedation-analgesia-by-means-of-poincare%C3%AC-analysis-of-the-electroencephalogram
#4
Jose D Bolanos, Montserrat Vallverdu, Pere Caminal, Daniel F Valencia, Xavi Borrat, Pedro L Gambus, Jose F Valencia, Jose D Bolanos, Montserrat Vallverdu, Pere Caminal, Daniel F Valencia, Xavi Borrat, Pedro L Gambus, Jose F Valencia, Jose D Bolanos, Xavi Borrat, Jose F Valencia, Montserrat Vallverdu, Pere Caminal, Pedro L Gambus, Daniel F Valencia
Monitoring the levels of sedation-analgesia may be helpful for managing patient stress on minimally invasive medical procedures. Monitors based on EEG analysis and designed to assess general anesthesia cannot distinguish reliably between a light and deep sedation. In this work, the Poincaré plot is used as a nonlinear technique applied to EEG signals in order to characterize the levels of sedation-analgesia, according to observed categorical responses that were evaluated by means of Ramsay Sedation Scale (RSS)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227962/personalization-of-noneeg-based-seizure-detection-systems
#5
D Cogan, M Heydarzadeh, M Nourani, D Cogan, M Heydarzadeh, M Nourani, M Heydarzadeh, D Cogan, M Nourani
Seizures affect each patient differently, so personalization is a vital part of developing a reliable nonEEG based seizure detection system. This personalization must be done while the patient is undergoing video EEG monitoring in an epilepsy monitoring unit (EMU) because seizure detection by EEG is considered to be the ground truth. We propose the use of confidence interval analysis for determining how many seizures must be captured from a patient before we can reliably personalize such a seizure detection system for him/her...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227950/designing-and-testing-a-wearable-wireless-fnirs-patch
#6
Mohammadreza Abtahi, Gozde Cay, Manob Jyoti Saikia, Kunal Mankodiya, Mohammadreza Abtahi, Gozde Cay, Manob Jyoti Saikia, Kunal Mankodiya, Manob Jyoti Saikia, Kunal Mankodiya, Gozde Cay, Mohammadreza Abtahi
Optical brain monitoring using near infrared (NIR) light has got a lot of attention in order to study the complexity of the brain due to several advantages as oppose to other methods such as EEG, fMRI and PET. There are a few commercially available functional NIR spectroscopy (fNIRS) brain monitoring systems, but they are still non-wearable and pose difficulties in scanning the brain while the participants are in motion. In this work, we present our endeavors to design and test a low-cost, wireless fNIRS patch using NIR light sources at wavelengths of 770 and 830nm, photodetectors and a microcontroller to trigger the light sources, read photodetector's output and transfer data wirelessly (via Bluetooth) to a smart-phone...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227806/a-new-soft-material-based-in-the-ear-eeg-recording-technique
#7
Hao Dong, Paul M Matthews, Yike Guo, Hao Dong, Paul M Matthews, Yike Guo, Hao Dong, Paul M Matthews, Yike Guo
Long-term electroencephalogram (EEG) is important for seizure detection, sleep monitoring and etc. In-the- ear EEG device makes such recording robust to noise and privacy protected (invisible to other people). However, the state-of-art techniques suffer from various drawbacks such as customization for specific users, manufacturing difficulties and short life cycle. To address these issues, we proposed silvered glass silicone based in-the-ear electrode which can be manufactured using conventional compression moulding...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227805/modular-multipin-electrodes-for-comfortable-dry-eeg
#8
P Fiedler, D Strohmeier, A Hunold, S Griebel, R Muhle, M Schreiber, P Pedrosa, B Vasconcelos, C Fonseca, F Vaz, J Haueisen, P Fiedler, D Strohmeier, A Hunold, S Griebel, R Muhle, M Schreiber, P Pedrosa, B Vasconcelos, C Fonseca, F Vaz, J Haueisen, P Pedrosa, F Vaz, P Fiedler, B Vasconcelos, J Haueisen, M Schreiber, R Muhle, C Fonseca, S Griebel, D Strohmeier, A Hunold
Electrode and cap concepts for continuous and ubiquitous monitoring of brain activity will open up new fields of application and contribute to increased use of electroencephalography (EEG) in clinical routine, neurosciences, brain-computer-interfacing and out-of-the-lab monitoring. However, mobile and unobtrusive applications are currently hindered by the lack of applicable convenient and reliable electrode and cap systems. We propose a novel modular electrode concept based on a flexible polymer substrate, coated with electrically conductive metallic films...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227696/oscillatory-brain-activity-changes-by-anodal-tdcs-an-ecog-study-on-anesthetized-beagles
#9
Sehyeon Jang, Donghyeon Kim, Junkil Been, Hohyun Cho, Sung Chan Jun, Sehyeon Jang, Donghyeon Kim, Junkil Been, Hohyun Cho, Sung Chan Jun, Donghyeon Kim, Junkil Been, Sung Chan Jun, Hohyun Cho, Sehyeon Jang
Measuring neuronal activity of transcranial direct current stimulation (tDCS) is essential for investigating tDCS in stimuli or after stimuli effects. The aim of this study was to investigate the oscillatory changes from anodal tDCS using electrocorticography (ECoG) on beagles. We applied 2 mA anodal tDCS and monitored the ECoG signals (32 channels, 512 Hz sampling rate) for 15 minutes in three anesthetized beagles. Then, we compared the power changes before, during, and after tDCS in six different bands (delta, theta, alpha, beta, low-gamma, and mid-gamma bands)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227634/design-and-validation-of-a-wearable-drl-less-eeg-using-a-novel-fully-reconfigurable-architecture
#10
Ruhi Mahajan, Bashir I Morshed, Gavin M Bidelman, Ruhi Mahajan, Bashir I Morshed, Gavin M Bidelman, Bashir I Morshed, Ruhi Mahajan, Gavin M Bidelman
The conventional EEG system consists of a driven-right-leg (DRL) circuit, which prohibits modularization of the system. We propose a Lego-like connectable fully reconfigurable architecture of wearable EEG that can be easily customized and deployed at naturalistic settings for collecting neurological data. We have designed a novel Analog Front End (AFE) that eliminates the need for DRL while maintaining a comparable signal quality of EEG. We have prototyped this AFE for a single channel EEG, referred to as Smart Sensing Node (SSN), that senses brain signals and sends it to a Command Control Node (CCN) via an I(2)C bus...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227552/research-on-eeg-features-of-attended-unattended-vigilance
#11
Chang Sun, Runge Chen, Miao Tian, Xingwei An, Hongzhi Qi, Minpeng Xu, Xuemin Wang, Dong Ming, Peng Zhou, Chang Sun, Runge Chen, Miao Tian, Xingwei An, Hongzhi Qi, Minpeng Xu, Xuemin Wang, Dong Ming, Peng Zhou, Miao Tian, Minpeng Xu, Hongzhi Qi, Runge Chen, Dong Ming, Chang Sun, Xingwei An, Peng Zhou, Xuemin Wang
Vigilance refers to the brain alertness to objective things, including the concentration of attention and the capability to response emergencies. It is of great importance to study vigilance monitoring to avoid accidents caused by decrease of vigilance. In this study, traditional Mackworth Clock Test (MCT) was modified to induce decline of attended and unattended vigilance. We analyzed EEG features in different levels of attended vigilance and assessed unattended vigilance by amplitude of mismatch negative (MMN) which can be evoked by audio odd ball stimulations...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227548/driver-drowsiness-detection-using-the-in-ear-eeg
#12
Taeho Hwang, Miyoung Kim, Seunghyeok Hong, Kwang Suk Park, Taeho Hwang, Miyoung Kim, Seunghyeok Hong, Kwang Suk Park, Kwang Suk Park, Seunghyeok Hong, Miyoung Kim, Taeho Hwang
Driver drowsiness monitoring is one of the most demanded technologies for active prevention of severe road accidents. Electroencephalogram (EEG) and several peripheral signals have been suggested for the drowsiness monitoring. However, each type of signal has partial limitations in terms of either convenience or accuracy. Recent emerged concept of in-ear EEG raises expectations due to reduced obtrusiveness. It is yet unclear whether the in-ear EEG is effective enough for drowsiness detection in comparison with on-scalp EEG or peripheral signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227092/eeg-based-single-trial-detection-of-errors-from-multiple-error-related-brain-activity
#13
Guofa Shou, Lei Ding, Guofa Shou, Lei Ding, Guofa Shou, Lei Ding
A key ability of the human brain is to monitor erroneous events and adjust behaviors accordingly. Electrophysiological and neuroimaging studies have demonstrated different brain activities related to errors. Meanwhile, the recognition of error-related brain activity as one aspect of performance monitoring has been reported for potential applications in clinical neuroscience and brain-machine interface, where single-trial analysis and classification would provide novel insights on dynamic brain responses to errors...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226669/seizure-detection-using-dynamic-warping-for-patients-with-intellectual-disability
#14
Lei Wang, Johan B A M Arends, Xi Long, Yan Wu, Pierre J M Cluitmans, Lei Wang, Johan B A M Arends, Xi Long, Yan Wu, Pierre J M Cluitmans, Yan Wu, Johan B A M Arends, Lei Wang, Pierre J M Cluitmans, Xi Long
Electroencephalography (EEG) is paramount for both retrospective analysis and real-time monitoring of epileptic seizures. Studies have shown that EEG-based seizure detection is very difficult for a specific epileptic population with intellectual disability due to the cerebral development disorders. In this work, a seizure detection method based on dynamic warping (DW) is proposed for patients with intellectual disability. It uses an EEG template of an individual subject's dominant seizure type, to extract the morphological features from EEG signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226660/identifying-stereotypic-evolving-micro-scale-seizures-sems-in-the-hypoxic-ischemic-eeg-of-the-pre-term-fetal-sheep-with-a-wavelet-type-ii-fuzzy-classifier
#15
Hamid Abbasi, Laura Bennet, Alistair J Gunn, Charles P Unsworth, Hamid Abbasi, Laura Bennet, Alistair J Gunn, Charles P Unsworth, Charles P Unsworth, Laura Bennet, Hamid Abbasi, Alistair J Gunn
Perinatal hypoxic-ischemic encephalopathy (HIE) around the time of birth due to lack of oxygen can lead to debilitating neurological conditions such as epilepsy and cerebral palsy. Experimental data have shown that brain injury evolves over time, but during the first 6-8 hours after HIE the brain has recovered oxidative metabolism in a latent phase, and brain injury is reversible. Treatments such as therapeutic cerebral hypothermia (brain cooling) are effective when started during the latent phase, and continued for several days...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226644/examining-the-effect-of-mgso4-on-sharp-wave-transient-activity-in-the-hypoxic-ischemic-fetal-sheep-model
#16
Meherzad J Lakadia, Hamid Abbasi, Alistair J Gunn, Charles P Unsworth, Laura Bennet, Meherzad J Lakadia, Hamid Abbasi, Alistair J Gunn, Charles P Unsworth, Laura Bennet, Laura Bennet, Hamid Abbasi, Alistair J Gunn, Meherzad J Lakadia, Charles P Unsworth
Hypoxic-ischemic encephalopathy (HIE) due to lack of oxygen is a debilitating disorder experienced by a significant number of preterm infants during birth. Studies show that the brain undergoes different phases of injury following hypoxic insult, but the first 6-8 hours (known as a latent phase) are the key to treatment efficacy. Cerebral hypothermia is one known treatment, and for it to be effective it must be started during the latent phase and continued for several days. In order to determine the effectiveness of treatment it is important to pinpoint the time of insult...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226626/detection-of-steering-direction-using-eeg-recordings-based-on-sample-entropy-and-time-frequency-analysis
#17
P Caldero-Bardaji, X Longfei, S Jaschke, J Reermann, K G Mideska, G Schmidt, G Deuschl, M Muthuraman, P Caldero-Bardaji, X Longfei, S Jaschke, J Reermann, K G Mideska, G Schmidt, G Deuschl, M Muthuraman, J Reermann, X Longfei, P Caldero-Bardaji, G Deuschl, K G Mideska, S Jaschke, G Schmidt, M Muthuraman
Monitoring driver's intentions beforehand is an ambitious aim, which will bring a huge impact on the society by preventing traffic accidents. Hence, in this preliminary study we recorded high resolution electroencephalography (EEG) from 5 subjects while driving a car under real conditions along with an accelerometer which detects the onset of steering. Two sensor-level analyses, sample entropy and time-frequency analysis, have been implemented to observe the dynamics before the onset of steering. Thus, in order to classify the steering direction we applied a machine learning algorithm consisting of: dimensionality reduction and classification using principal-component-analysis (PCA) and support-vector-machine (SVM), respectively...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226618/eeg-based-driver-fatigue-detection-using-hybrid-deep-generic-model
#18
Phyo Phyo San, Sai Ho Ling, Rifai Chai, Yvonne Tran, Ashley Craig, Hung Nguyen, Phyo Phyo San, Sai Ho Ling, Rifai Chai, Yvonne Tran, Ashley Craig, Hung Nguyen, Ashley Craig, Sai Ho Ling, Hung Nguyen, Phyo Phyo San, Yvonne Tran, Rifai Chai
Classification of electroencephalography (EEG)-based application is one of the important process for biomedical engineering. Driver fatigue is a major case of traffic accidents worldwide and considered as a significant problem in recent decades. In this paper, a hybrid deep generic model (DGM)-based support vector machine is proposed for accurate detection of driver fatigue. Traditionally, a probabilistic DGM with deep architecture is quite good at learning invariant features, but it is not always optimal for classification due to its trainable parameters are in the middle layer...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226617/application-of-cross-correlated-delay-shift-rule-in-spiking-neural-networks-for-interictal-spike-detection
#19
Lilin Guo, Zhenzhong Wang, Mercedes Cabrerizo, Malek Adjouadi, Lilin Guo, Zhenzhong Wang, Mercedes Cabrerizo, Malek Adjouadi, Mercedes Cabrerizo, Lilin Guo, Zhenzhong Wang, Malek Adjouadi
This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classify spike patterns. The objective of this study was to evaluate the feasibility of using the CCDS rule to automate the detection of interictal spikes in electroencephalogram (EEG) data on patients with epilepsy. Encoding is the initial yet essential step for spiking neurons to process EEG patterns. A new encoding method is utilized to convert the EEG signal into spike patterns...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28222340/a-comparative-retrospective-exploration-of-the-profiles-of-patients-in-south-africa-diagnosed-with-epileptic-and-psychogenic-non-epileptic-seizures
#20
David G Anderson, Maria Damianova, Skye Hanekom, Marilyn Lucas
Psychogenic non-epileptic seizures (PNES) have a high prevalence globally but the accurate diagnosis of this condition still remains a challenge. This is particularly the case in countries where there is scarce expertise and insufficient affordable medical facilities to which patients have access. The rate of PNES diagnosis in epilepsy units is typically within the range of 20 to 30%. In the context of developing countries, this rate tends to be higher and increases demand on the existing scarce health care capacities...
February 18, 2017: Epilepsy & Behavior: E&B
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