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 51,768 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

In this paper, a novel P300-based concealed information test (CIT) method was proposed to improve the efficiency of differentiating deception and truth-telling. Thirty subjects including the guilty and innocent performed the paradigm based on three types of stimuli. In order to reduce the influence from the occasional variability of cognitive states on the CIT, several single-trials from Pz in probe stimuli within each subject were first averaged. Then the three groups of features were extracted from these averaged single-trials. Finally, two classes of feature samples were used to train a support vector machine (SVM) classifier. Meanwhile, the optimal number of averaged Pz waveforms and some other parameter values in the classifiers were determined by the cross validation procedures. Results show that if choosing accuracy of 90% as a detecting standard of P3 component to classify a subject's status (guilty or innocent), our method can achieve individual diagnostic rate of 100%. The individual diagnostic rate of our method was higher than the results of the other related reports. The presented method improves efficiency of CIT, and is more practical, lower fatigue and less countermeasure behavior in comparison with previous report methods, which could extend the laboratory study to the practical application.
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PMID:Denoised P300 and machine learning-based concealed information test method. 2112 96

Although relating to very different concepts, sleepiness and fatigue are often confounded. However, both fatigue-associated conditions such as the chronic fatigue syndrome (CFS) and sleepiness-associated conditions such as the sleep apnea-hypopnea syndrome (SAHS) are associated with cognitive impairment with impaired attention, concentration and memory performances. Fifteen pure CFS patients, without primary sleep disorders or clinically relevant sleepiness, were compared to 15 untreated SAHS patients, without clinically relevant fatigue, and to 16 healthy controls of similar age. The auditory verbal learning test (AVLT), digit span, digit symbol and finger tapping test (FTT) were used as cognitive and behavioural measures. In addition we assessed daytime EEG spectral power and P300 evoked potentials. With exception for the digit span, all tests showed lower performances in patient groups. Recall on the AVLT did not differ between the two patient groups, but the digit and symbol spans showed more severe impairment in SAHS patients. Psychomotor performance on the FTT presented with slower hit rates in SAHS than in CFS. EEG theta power was highest in CFS patients. P300 latencies and amplitudes did not differ between groups. Fatigue- and sleepiness-associated conditions can both present with significant and objective impairment of cognitive functioning and behavioural motor performance. In our sample cognitive impairment and psychomotor performance were worse when associated to sleepiness in SAHS than with fatigue in CFS.
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PMID:Cognitive impairment in fatigue and sleepiness associated conditions. 2119 50

Mental fatigue is a contributing factor to some serious transportation crashes. In this study, we measured mental fatigue in drivers using electroencephalogram (EEG) and electrocardiograph (ECG). Together, thirteen healthy subjects performed a continuous simulated driving task for 90 min with simultaneous ECG and multi-channel EEG recording of each subject. Several important physiological parameters were investigated using preprocessed ECG and EEG signals. The results show that the EEG alpha and beta, the relative power, the amplitude of P300 wave of event-related potential (ERP), the approximated entropy of the ECG, and the lower and upper bands of power of heart rate variability (HRV) are significantly different before and after finishing the driving task (p<0.05). These metrics are possible indices for measuring simulated driving mental fatigue.
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PMID:Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator. 2226 88

The common assumption in EEG-neurofeedback is one of functional specificity of the trained spectral bands, though it has been posited that only a nonspecific generalised learning process may be engaged. Earlier we reported differential effects on attention in healthy participants measured with continuous performance tests and the P300, following training of the sensory-motor rhythm band (SMR, 12-15 Hz) compared with the adjacent beta1 (15-18 hz) band. Here previously unreported results are presented with phenomenological data from an activation checklist in support of the putative calming effect of SMR neurofeedback. While within sessions both protocols induced tiredness, this was paralleled by an increase in calmness only following SMR training. The differential effect on mood was theoretically consistent and extends evidence of cognitive functional specificity with neurofeedback to affective processes.
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PMID:Differential effects on mood of 12-15 (SMR) and 15-18 (beta1) Hz neurofeedback. 2335 78

Vanadium-containing products are manufactured and widely used in the modern industry. Yet the neurobehavioral toxicity due to occupational exposure to vanadium remained elusive. This cross-sectional study was designed to examine the neurotoxic effects of occupational vanadium exposure. A total of 463 vanadium-exposed workers (exposed group) and 251 non-exposed workers (control group) were recruited from a Steel and Iron Group in Sichuan, China. A WHO-recommended neurobehavioral core test battery (NCTB) and event-related auditory evoked potentials test (P300) were used to assess the neurobehavioral functions of all study subjects. A general linear model was used to compare outcome scores between the two groups while controlling for possible confounders. The exposed group showed a statistically significant neurobehavioral alteration more than the control group in the NCTB tests. The exposed workers also exhibited an increased anger-hostility, depression-dejection and fatigue-inertia on the profile of mood states (p<0.05). Performances in the simple reaction time, digit span, benton visual retention and pursuit aiming were also poorer among exposed workers as compared to unexposed control workers (p<0.05). Some of these poor performances in tests were also significantly related to workers' exposure duration. P300 latencies were longer in the exposed group than in the control (p<0.05). Longer mean reaction times and more counting errors were also found in the exposed workers (p<0.05). Given the findings of our study and the limitations of neurobehavioral workplace testing, we found evidence of altered neurobehavioral outcomes by occupational exposure to vanadium.
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PMID:Vanadium exposure-induced neurobehavioral alterations among Chinese workers. 2492 99

Many professions place significant mental and/or physical strain on their workers. Some professionals (such as firefighters, soldiers, and pilots) have an inherent responsibility for the safety of others. Making sure that workers in these remain fit for duty is an important health/safety concern for the workers and those they serve. This paper explores the viability of using EEG as a non-invasive, cost efficient method for assessing fatigue, sleep deprivation, physical exertion and stress. Specifically, P300 evoked potentials are generated in response to certain stimuli. Variations in the response characteristics (magnitude, shape, and peak shift) are explored in relation to sleep deprivation, caffeine usage, and physical exertion. Preliminary data suggests that there are quantifiable changes to the P300 response that may be attributed to fatigue.
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PMID:Changes in behavior of evoked potentials in the brain as a possible indicator of fatigue in people. 2411 Dec 1

The study aimed at revealing electrophysiological indicators of mental workload and fatigue during prolonged usage of a P300 brain-computer interface (BCI). Mental workload was experimentally manipulated with dichotic listening tasks. Medium and high workload conditions alternated. Behavioral measures confirmed that the manipulation of mental workload was successful. Reduced P300 amplitude was found for the high workload condition. Along with lower performance and an increase in the subjective level of fatigue, an increase of power in the alpha band was found for the last as compared to the first run of both conditions. The study confirms that a combination of signals derived from the time and frequency domain of the electroencephalogram is promising for the online detection of workload and fatigue. It also demonstrates that satisfactory accuracies can be achieved by healthy participants with the P300 speller, despite constant distraction and when pursuing the task for a long time.
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PMID:Effects of mental workload and fatigue on the P300, alpha and theta band power during operation of an ERP (P300) brain-computer interface. 2508 78

A single-trial extraction of a visual evoked potential (VEP) signal based on the partial least-squares (PLS) regression method has been proposed in this paper. This paper has focused on the extraction and estimation of the latencies of P100, P200, P300, N75, and N135 in the artificial electroencephalograph (EEG) signal. The real EEG signal obtained from the hospital was only concentrated on the P100. The performance of the PLS has been evaluated mainly on the basis of latency error rate of the peaks for the artificial EEG signal, and the mean peak detection and standard deviation for the real EEG signal. The simulation results show that the proposed PLS algorithm is capable of reconstructing the EEG signal into its desired shape of the ideal VEP. For P100, the proposed PLS algorithm is able to provide comparable results to the generalized eigenvalue decomposition (GEVD) algorithm, which alters (prewhitens) the EEG input signal using the prestimulation EEG signal. It has also shown better performance for later peaks (P200 and P300). The PLS outperformed not only in positive peaks but also in N75. In P100, the PLS was comparable with the GEVD although N135 was better estimated by GEVD. The proposed PLS algorithm is comparable to GEVD given that PLS does not alter the EEG input signal. The PLS algorithm gives the best estimate to multitrial ensemble averaging. This research offers benefits such as avoiding patient's fatigue during VEP test measurement in the hospital, in BCI applications and in EEG-fMRI integration.
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PMID:Single-Trial Visual Evoked Potential Extraction Using Partial Least-Squares-Based Approach. 2537 49

Brain-computer interface (BCI) performance has achieved continued improvement over recent decades, and sensorimotor rhythm-based BCIs that use motor function have been popular subjects of investigation. However, it remains problematic to introduce them to the public market because of their low reliability. As an alternative resolution to this issue, visual-based BCIs that use P300 or steady-state visually evoked potentials (SSVEPs) seem promising; however, the inherent visual fatigue that occurs with these BCIs may be unavoidable. For these reasons, steady-state somatosensory evoked potential (SSSEP) BCIs, which are based on tactile selective attention, have gained increasing attention recently. These may reduce the fatigue induced by visual attention and overcome the low reliability of motor activity. In this literature survey, recent findings on SSSEP and its methodological uses in BCI are reviewed. Further, existing limitations of SSSEP BCI and potential future directions for the technique are discussed.
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PMID:Steady-State Somatosensory Evoked Potential for Brain-Computer Interface-Present and Future. 2683 11

The goal of this study is to investigate the influence of mental fatigue on the event related potential P300 features (maximum pick, minimum amplitude, latency and period) during virtual wheelchair navigation. For this purpose, an experimental environment was set up based on customizable environmental parameters (luminosity, number of obstacles and obstacles velocities). A correlation study between P300 and fatigue ratings was conducted. Finally, the best correlated features supplied three classification algorithms which are MLP (Multi Layer Perceptron), Linear Discriminate Analysis and Support Vector Machine. The results showed that the maximum feature over visual and temporal regions as well as period feature over frontal, fronto-central and visual regions were correlated with mental fatigue levels. In the other hand, minimum amplitude and latency features didn't show any correlation. Among classification techniques, MLP showed the best performance although the differences between classification techniques are minimal. Those findings can help us in order to design suitable mental fatigue based wheelchair control.
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PMID:When mental fatigue maybe characterized by Event Related Potential (P300) during virtual wheelchair navigation. 2719 88


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