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https://www.readbyqxmd.com/read/28326009/improving-eeg-based-driver-fatigue-classification-using-sparse-deep-belief-networks
#1
Rifai Chai, Sai Ho Ling, Phyo Phyo San, Ganesh R Naik, Tuan N Nguyen, Yvonne Tran, Ashley Craig, Hung T Nguyen
This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28321563/do-patients-with-m%C3%A3-ni%C3%A3-re-s-disease-have-attacks-of-syncope
#2
Ilmari Pyykkö, Vinaya Manchaiah, Jing Zou, Hilla Levo, Erna Kentala
The aim of the present study was to evaluate the prevalence and associated factors for syncope among patients with Ménière's disease (MD). An attack of syncope was defined as a sudden and transient loss of consciousness, which subsides spontaneously and without a localizing neurological deficit. The study used an across-sectional survey design. Information from a database consisting of 961 individuals was collected from the Finnish Ménière Association. The data contained case histories, general health-related quality of life (HRQoL), and impact measurements of the complaints...
March 20, 2017: Journal of Neurology
https://www.readbyqxmd.com/read/28277403/methylphenidate-enhances-grip-force-and-alters-brain-connectivity
#3
Michael King, Laurie H Rauch, Samantha J Brooks, Dan J Stein, Kai Lutz
INTRODUCTION: A central fatigue theory proposes that force output during fatiguing exercise is limited to maintain homeostasis. The self-awareness of the body's homeostatic state is known as interoception. Brain regions thought to play a role in interoception, such as the insular and orbital frontal cortex, have been proposed as sites for the upstream regulation of fatiguing exercise. Methylphenidate (MPH) can improve force output during exercise and may alter central processes during fatiguing exercise...
March 8, 2017: Medicine and Science in Sports and Exercise
https://www.readbyqxmd.com/read/28269312/classification-of-eeg-based-mental-fatigue-using-principal-component-analysis-and-bayesian-neural-network
#4
Rifai Chai, Yvonne Tran, Ganesh R Naik, Tuan N Nguyen, Sai Ho Ling, Ashley Craig, Hung T Nguyen
This paper presents an electroencephalography (EEG) based-classification of between pre- and post-mental load tasks for mental fatigue detection from 65 healthy participants. During the data collection, eye closed and eye open tasks were collected before and after conducting the mental load tasks. For the computational intelligence, the system uses the combination of principal component analysis (PCA) as the dimension reduction method of the original 26 channels of EEG data, power spectral density (PSD) as feature extractor and Bayesian neural network (BNN) as classifier...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28267750/changes-in-brain-activation-in-breast-cancer-patients-depend-on-cognitive-domain-and-treatment-type
#5
Sanne Menning, Michiel B de Ruiter, Dick J Veltman, Willem Boogerd, Hester S A Oldenburg, Liesbeth Reneman, Sanne B Schagen
BACKGROUND: Cognitive problems in breast cancer patients are common after systemic treatment, particularly chemotherapy. An increasing number of fMRI studies show altered brain activation in breast cancer patients after treatment, suggestive of neurotoxicity. Previous prospective fMRI studies administered a single cognitive task. The current study employed two task paradigms to evaluate whether treatment-induced changes depend on the probed cognitive domain. METHODS: Participants were breast cancer patients scheduled to receive systemic treatment (anthracycline-based chemotherapy +/- endocrine treatment, n = 28), or no systemic treatment (n = 24) and no-cancer controls (n = 31)...
2017: PloS One
https://www.readbyqxmd.com/read/28261110/the-neuroinflammatory-etiopathology-of-myalgic-encephalomyelitis-chronic-fatigue-syndrome-me-cfs
#6
Julian A G Glassford
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating multi-systemic chronic illness of unknown etiology, classified as a neurological disorder by the World Health Organization (WHO). The symptomatology of the condition appears to emanate from a variety of sources of chronic neurological disturbance and associated distortions, and chronicity, in noxious sensory signaling and neuroimmune activation. This article incorporates a summary review and discussion of biomedical research considered relevant to this essential conception perspective...
2017: Frontiers in Physiology
https://www.readbyqxmd.com/read/28257928/the-effects-of-a-mid-task-break-on-the-brain-connectome-in-healthy-participants-a-resting-state-functional-mri-study
#7
Yu Sun, Julian Lim, Zhongxiang Dai, KianFoong Wong, Fumihiko Taya, Yu Chen, Junhua Li, Nitish Thakor, Anastasios Bezerianos
Although rest breaks are commonly administered as a countermeasure to reduce mental fatigue and boost cognitive performance, the effects of taking a break on behavior are not consistent. Moreover, our understanding of the underlying neural mechanisms of rest breaks and how they modulate mental fatigue is still rudimentary. In this study, we investigated the effects of receiving a rest break on the topological properties of brain connectivity networks via a two-session experimental paradigm, in which one session comprised four successive blocks of a mentally demanding visual selective attention task (No-rest session), whereas the other contained a rest break between the second and third task blocks (Rest session)...
February 28, 2017: NeuroImage
https://www.readbyqxmd.com/read/28242828/unilateral-fatiguing-exercise-and-its-effect-on-ipsilateral-and-contralateral-resting-mechanomyographic-mean-frequency-between-aerobic-populations
#8
Nathan P Wages, Travis W Beck, Xin Ye, Joshua C Carr
The purpose of this investigation was to establish a better understanding of contralateral training and its effects between homologous muscles following unilateral fatiguing aerobic exercise during variable resting postural positions, and to determine if any observable disparities could be attributed to the differences between the training ages of the participants. Furthermore, we hypothesized that we would observe a contralateral cross-over effect for both groups, with the novice trained group having the higher mechanomyographic mean frequency values in both limbs, across all resting postural positions...
February 2017: Physiological Reports
https://www.readbyqxmd.com/read/28241776/the-effectiveness-of-robot-assisted-gait-training-versus-conventional-therapy-on-mobility-in-severely-disabled-progressive-multiple-sclerosis-patients-ragtime-study-protocol-for-a-randomized-controlled-trial
#9
Sofia Straudi, Fabio Manfredini, Nicola Lamberti, Paolo Zamboni, Francesco Bernardi, Giovanna Marchetti, Paolo Pinton, Massimo Bonora, Paola Secchiero, Veronica Tisato, Stefano Volpato, Nino Basaglia
BACKGROUND: Gait and mobility impairments affect the quality of life (QoL) of patients with progressive multiple sclerosis (MS). Robot-assisted gait training (RAGT) is an effective rehabilitative treatment but evidence of its superiority compared to other options is lacking. Furthermore, the response to rehabilitation is multidimensional, person-specific and possibly involves functional reorganization processes. The aims of this study are: (1) to test the effectiveness on gait speed, mobility, balance, fatigue and QoL of RAGT compared to conventional therapy (CT) in progressive MS and (2) to explore changes of clinical and circulating biomarkers of neural plasticity...
February 27, 2017: Trials
https://www.readbyqxmd.com/read/28240392/abnormal-task-driven-neural-oscillations-in-multiple-sclerosis-a-visuomotor-meg-study
#10
Eleanor L Barratt, Prejaas K Tewarie, Margareta A Clarke, Emma L Hall, Penny A Gowland, Peter G Morris, Susan T Francis, Nikos Evangelou, Matthew J Brookes
Multiple sclerosis (MS) is a debilitating disease commonly attributed to degradation of white matter myelin. Symptoms include fatigue, as well as problems associated with vision and movement. Although areas of demyelination in white matter are observed routinely in patients undergoing MRI scans, such measures are often a poor predictor of disease severity. For this reason, it is instructive to measure associated changes in brain function. Widespread white-matter demyelination may lead to delays of propagation of neuronal activity, and with its excellent temporal resolution, magnetoencephalography can be used to probe such delays in controlled conditions (e...
February 27, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28227550/classification-of-eeg-based-mental-fatigue-using-principal-component-analysis-and-bayesian-neural-network
#11
Rifai Chai, Yvonne Tran, Ganesh R Naik, Tuan N Nguyen, Sai Ho Ling, Ashley Craig, Hung T Nguyen, Rifai Chai, Yvonne Tran, Ganesh R Naik, Tuan N Nguyen, Sai Ho Ling, Ashley Craig, Hung T Nguyen, Ashley Craig, Tuan N Nguyen, Sai Ho Ling, Hung T Nguyen, Yvonne Tran, Ganesh R Naik, Rifai Chai
This paper presents an electroencephalography (EEG) based-classification of between pre- and post-mental load tasks for mental fatigue detection from 65 healthy participants. During the data collection, eye closed and eye open tasks were collected before and after conducting the mental load tasks. For the computational intelligence, the system uses the combination of principal component analysis (PCA) as the dimension reduction method of the original 26 channels of EEG data, power spectral density (PSD) as feature extractor and Bayesian neural network (BNN) as classifier...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28219032/analysis-of-the-semg-force-relationship-using-hd-semg-technique-and-data-fusion-a-simulation-study
#12
Mariam Al Harrach, Vincent Carriou, Sofiane Boudaoud, Jeremy Laforet, Frederic Marin
The relationship between the surface Electromyogram (sEMG) signal and the force of an individual muscle is still ambiguous due to the complexity of experimental evaluation. However, understanding this relationship should be useful for the assessment of neuromuscular system in healthy and pathological contexts. In this study, we present a global investigation of the factors governing the shape of this relationship. Accordingly, we conducted a focused sensitivity analysis of the sEMG/force relationship form with respect to neural, functional and physiological parameters variation...
February 16, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28217081/blinker-automated-extraction-of-ocular-indices-from-eeg-enabling-large-scale-analysis
#13
Kelly Kleifges, Nima Bigdely-Shamlo, Scott E Kerick, Kay A Robbins
Electroencephalography (EEG) offers a platform for studying the relationships between behavioral measures, such as blink rate and duration, with neural correlates of fatigue and attention, such as theta and alpha band power. Further, the existence of EEG studies covering a variety of subjects and tasks provides opportunities for the community to better characterize variability of these measures across tasks and subjects. We have implemented an automated pipeline (BLINKER) for extracting ocular indices such as blink rate, blink duration, and blink velocity-amplitude ratios from EEG channels, EOG channels, and/or independent components (ICs)...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28216087/neural-consequences-of-post-exertion-malaise-in-myalgic-encephalomyelitis-chronic-fatigue-syndrome
#14
Dane B Cook, Alan R Light, Kathleen C Light, Gordon Broderick, Morgan R Shields, Ryan J Dougherty, Jacob D Meyer, Stephanie VanRiper, Aaron J Stegner, Laura D Ellingson, Suzanne D Vernon
Post exertion malaise is one of the most debilitating aspects of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, yet the neurobiological consequences are largely unexplored. The objective of the study was to determine the neural consequences of acute exercise using functional brain imaging. Fifteen female Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients and 15 healthy female controls completed 30min of submaximal exercise (70% of peak heart rate) on a cycle ergometer. Symptom assessments (e.g...
February 17, 2017: Brain, Behavior, and Immunity
https://www.readbyqxmd.com/read/28207899/human-cortical-neural-correlates-of-visual-fatigue-during-binocular-depth-perception-an-fnirs-study
#15
Tingting Cai, Huilin Zhu, Jie Xu, Shijing Wu, Xinge Li, Sailing He
Functional near-infrared spectroscopy (fNIRS) was adopted to investigate the cortical neural correlates of visual fatigue during binocular depth perception for different disparities (from 0.1° to 1.5°). By using a slow event-related paradigm, the oxyhaemoglobin (HbO) responses to fused binocular stimuli presented by the random-dot stereogram (RDS) were recorded over the whole visual dorsal area. To extract from an HbO curve the characteristics that are correlated with subjective experiences of stereopsis and visual fatigue, we proposed a novel method to fit the time-course HbO curve with various response functions which could reflect various processes of binocular depth perception...
2017: PloS One
https://www.readbyqxmd.com/read/28186630/cascade-convolutional-neural-networks-for-automatic-detection-of-thyroid-nodules-in-ultrasound-images
#16
Jinlian Ma, Fa Wu, Tian'an Jiang, Jiang Zhu, Dexing Kong
PURPOSE: It is very important for calculation of clinical indices and diagnosis to detect thyroid nodules from ultrasound images. However, this task is a challenge mainly due to heterogeneous thyroid nodules with distinct components are similar to background in ultrasound images. In this study, we employ cascade deep convolutional neural networks (CNNs) to develop and evaluate a fully automatic detection of thyroid nodules from 2D ultrasound images. METHODS: Our cascade CNNs are a type of hybrid model, consisting of two different CNNs and a new splitting method...
February 10, 2017: Medical Physics
https://www.readbyqxmd.com/read/28161821/cortical-activity-predicts-good-variation-in-human-motor-output
#17
Sarine Babikian, Eva Kanso, Jason J Kutch
Human movement patterns have been shown to be particularly variable if many combinations of activity in different muscles all achieve the same task goal (i.e., are goal-equivalent). The nervous system appears to automatically vary its output among goal-equivalent combinations of muscle activity to minimize muscle fatigue or distribute tissue loading, but the neural mechanism of this "good" variation is unknown. Here we use a bimanual finger task, electroencephalography (EEG), and machine learning to determine if cortical signals can predict goal-equivalent variation in finger force output...
April 2017: Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale
https://www.readbyqxmd.com/read/28113875/the-reorganization-of-human-brain-networks-modulated-by-driving-mental-fatigue
#18
Chunlin Zhao, Min Zhao, Yong Yang, Junfeng Gao, Nini Rao, Pan Lin
The organization of the brain functional network is associated with mental fatigue, but little is known about the brain network topology that is modulated by the mental fatigue. In this study, we used the graph theory approach to investigate reconfiguration changes in functional networks of different electroencephalography (EEG) bands from 16 subjects performing a simulated driving task. Behavior and brain functional networks were compared between the normal and driving mental fatigue states. The scores of subjective self-reports indicated that 90 mins of simulated driving induced mental fatigue...
March 18, 2016: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28110043/is-myoelectric-activity-distributed-equally-within-the-rectus-femoris-muscle-during-loaded-squat-exercises
#19
Leonardo Mendes Leal de Souza, Desirée Barros da Fonseca, Hélio da Veiga Cabral, Liliam Fernandes de Oliveira, Taian Martins Vieira
Recent evidence suggests different regions of the rectus femoris (RF) muscle respond differently to squat exercises. Such differential adaptation may result from neural inputs distributed locally within RF, as previously reported for isometric contractions, walking and in response to fatigue. Here we therefore investigate whether myoelectric activity distributes evenly within RF during squat. Surface electromyograms (EMGs) were sampled proximally and distally from RF with arrays of electrodes, while thirteen healthy volunteers performed 10 consecutive squats with 20% and 40% of their body weight...
January 9, 2017: Journal of Electromyography and Kinesiology
https://www.readbyqxmd.com/read/28089250/pathology-of-behavior-in-pd-what-is-known-and-what-is-not
#20
REVIEW
Kaylena A Ehgoetz Martens, Simon J G Lewis
Abnormal behavior in Parkinson's disease (PD) stems from a complex orchestration of impaired neural networks that result from PD-related neurodegeneration across multiple levels. Typically, cellular and tissue abnormalities generate neurochemical changes and disrupt specific regions of the brain, in turn creating impaired neural circuits and dysfunctional global networks. The objective of this chapter is to provide an overview of the array of pathological changes that have been linked to different behavioral symptoms of PD such as depression, anxiety, apathy, fatigue, impulse control disorders, psychosis, sleep disorders and dementia...
March 15, 2017: Journal of the Neurological Sciences
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