76 resultados para Electroencephalography (EEG)


Relevância:

10.00% 10.00%

Publicador:

Resumo:

Key points • The clinical aims of MR spectroscopy (MRS) in seizure disorders are to help identify, localize and characterize epileptogenic foci. • Lateralizing MRS abnormalities in temporal lobe epilepsy (TLE) may be used clinically in combination with structural and T2 MRI measurements together with other techniques such as EEG, PET and SPECT. • Characteristic metabolite abnormalities are decreased N-acetylaspartate (NAA) with increased choline (Cho) and myoinositol (mI) (short-echo time). • Contralateral metabolite abnormalities are frequently seen in TLE, but are of uncertain significance. • In extra-temporal epilepsy, metabolite abnormalities may be seen where MR imaging (MRI) is normal; but may not be sufficiently localized to be useful clinically. • MRS may help to characterize epileptogenic lesions visible on MRI (aggressive vs. indolent neoplastic, dysplasia). • Spectral editing techniques are required to evaluate specific epilepsy-relevant metabolites (e.g. -aminobutyric acid (GABA)), which may be useful in drug development and evaluation. • MRS with phosphorus (31P) and other nuclei probe metabolism of epilepsy, but are less useful clinically. • There is potential for assessing the of drug mode of action and efficacy through 13C carbon metabolite measurements, while changes in sodium homeostasis resulting from seizure activity may be detected with 23Na MRS.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Drivers' ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. Highway design reduces the driving task mainly to a lane-keeping manoeuvre. Such a task is monotonous, providing little stimulation and this contributes to crashes due to inattention. Research has shown that driver's hypovigilance can be assessed with EEG measurements and that driving performance is impaired during prolonged monotonous driving tasks. This paper aims to show that two dimensions of monotony - namely road design and road side variability - decrease vigilance and impair driving performance. This is the first study correlating hypovigilance and driver performance in varied monotonous conditions, particularly on a short time scale (a few seconds). We induced vigilance decrement as assessed with an EEG during a monotonous driving simulator experiment. Road monotony was varied through both road design and road side variability. The driver's decrease in vigilance occurred due to both road design and road scenery monotony and almost independently of the driver's sensation seeking level. Such impairment was also correlated to observable measurements from the driver, the car and the environment. During periods of hypovigilance, the driving performance impairment affected lane positioning, time to lane crossing, blink frequency, heart rate variability and non-specific electrodermal response rates. This work lays the foundation for the development of an in-vehicle device preventing hypovigilance crashes on monotonous roads.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Acute exercise has been shown to exhibit different effects on human sensorimotor behavior; however, the causes and mechanisms of the responses are often not clear. The primary aim of the present study was to determine the effects of incremental running until exhaustion on sensorimotor performance and adaptation in a tracking task. Subjects were randomly assigned to a running group (RG), a tracking group (TG), or a running followed by tracking group (RTG), with 10 subjects assigned to each group. Treadmill running velocity was initially set at 2.0 m s− 1, increasing by 0.5 m s− 1 every 5 min until exhaustion. Tracking consisted of 35 episodes (each 40 s) where the subjects' task was to track a visual target on a computer screen while the visual feedback was veridical (performance) or left-right reversed (adaptation). Resting electroencephalographic (EEG) activity was recorded before and after each experimental condition (running, tracking, rest). Tracking performance and the final amount of adaptation did not differ between groups. However, task adaptation was significantly faster in RTG compared to TG. In addition, increased alpha and beta power were observed following tracking in TG but not RTG although exhaustive running failed to induce significant changes in these frequency bands. Our results suggest that exhaustive running can facilitate adaptation processes in a manual tracking task. Attenuated cortical activation following tracking in the exercise condition was interpreted to indicate cortical efficiency and exercise-induced facilitation of selective central processes during actual task demands.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Earlier research found evidence for electro-cortical race bias towards black target faces in white American participants irrespective of the task relevance of race. The present study investigated whether an implicit race bias generalizes across cultural contexts and racial in- and out-groups. An Australian sample of 56 Chinese and Caucasian males and females completed four oddball tasks that required sex judgements for pictures of male and female Chinese and Caucasian posers. The nature of the background (across task) and of the deviant stimuli (within task) was fully counterbalanced. Event-related potentials (ERPs) to deviant stimuli recorded from three midline sites were quantified in terms of mean amplitude for four components: N1, P2, N2 and a late positive complex (LPC; 350–700 ms). Deviants that differed from the backgrounds in sex or race elicited enhanced LPC activity. These differences were not modulated by participant race or sex. The current results replicate earlier reports of effects of poser race relative to background race on the LPC component of the ERP waveform. In addition, they indicate that an implicit race bias occurs regardless of participant's or poser's race and is not confined to a particular cultural context.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

The present study used ERPs to compare processing of fear-relevant (FR) animals (snakes and spiders) and non-fear-relevant (NFR) animals similar in appearance (worms and beetles). EEG was recorded from 18 undergraduate participants (10 females) as they completed two animal-viewing tasks that required simple categorization decisions. Participants were divided on a post hoc basis into low snake/spider fear and high snake/spider fear groups. Overall, FR animals were rated higher on fear and elicited a larger LPC. However, individual differences qualified these effects. Participants in the low fear group showed clear differentiation between FR and NFR animals on subjective ratings of fear and LPC modulation. In contrast, participants in the high fear group did not show such differentiation between FR and NFR animals. These findings suggest that the salience of feared-FR animals may generalize on both a behavioural and electro-cortical level to other animals of similar appearance but of a non-harmful nature.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Summary:  Objective: We performed spike triggered functional MRI (fMRI) in a 12 year old girl with Benign Epilepsy with Centro-temporal Spikes (BECTS) and left-sided spikes. Our aim was to demonstrate the cerebral origin of her interictal spikes. Methods: EEG was recorded within the 3 Tesla MRI. Whole brain fMRI images were acquired, beginning 2–3 seconds after spikes. Baseline fMRI images were acquired when there were no spikes for 20 seconds. Image sets were compared with the Student's t-test. Results: Ten spike and 20 baseline brain volumes were analysed. Focal activiation was seen in the inferior left sensorimotor cortex near the face area. The anterior cingulate was more active during baseline than spikes. Conclusions: Left sided epileptiform activity in this patient with BECTS is associated with fMRI activation in the left face region of the somatosensory cortex, which would be consistent with the facial sensorimotor involvement in BECT seizures. The presence of BOLD signal change in other regions raises the possibility that the scalp recorded field of this patient with BECTs may reflect electrical change in more than one brain region.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Decline of alertness constitutes a normal physiological phenomenon but could be aggravated when drivers operate in monotonous environments, even in rested individuals. Driving performance is impaired and this increases crash risk due to inattention. This paper aims to show that road characteristics - namely road design (road geometry) and road side variability (signage and buildings) – influence subjective assessment of alertness by drivers. This study used a driving simulator to investigate the drivers’ ability to subjectively detect periods of time when their alertness is importantly reduced by varying road geometry and road environment. Driver’s EEG activity is recorded as a reference to evaluate objectively driver's alertness and is compared to self-reported alertness by participants. Twenty-five participants drove on four different scenarios (varying road design and road environment monotony) for forty minutes. It was observed that participants were significantly more accurate in their assessment before the driving task as compared to after (90% versus 60%). Errors in assessment were largely underestimations of their real alertness rather than over-estimations. The ability to detect low alertness as assessed with an EEG was highly dependent on the road monotony. Scenarios with low roadside variability resulted in high overestimation of the real alertness, which was not observed on monotonous road design. The findings have consequences for road safety and suggest that countermeasures to lapses of alertness cannot rely solely on self-assessment from drivers and road design should reduce environments with low variability.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Background: Sleepiness is a direct contributor to a substantial proportion of fatal and severe road cashes. A number of technological solutions designed to detect sleepiness have been developed, but self-awareness of increasing sleepiness remains a critical component in on-road strategies for mitigating this risk. In order to take appropriate action when sleepy, drivers’ perceptions of their level of sleepiness must be accurate. Aims: This study aimed to assess capacity to accurately identify sleepiness and self-regulate driving cessation during a validated driving simulator task. Participants: Participants comprised 26 young adult drivers (20-28 years). The drivers had open licenses but no other exclusion criteria where used. Methods: Participants woke at 5am, and took part in a laboratory-based hazard perception driving simulation, either at mid-morning or mid-afternoon. Established physiological measures (including EEG) and subjective measures (sleepiness ratings) previously found sensitive to changes in sleepiness levels were utilised. Participants were instructed to ‘drive’ until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 39 minutes (±18 minutes). Almost all (23/26) of the participants then achieved sleep during the nap opportunity. These data suggest that the participants’ perceptions of sleepiness were specific. However, EEG data from a number of participants suggested very high levels of sleepiness prior to driving cessation, suggesting poor sensitivity. Conclusions: Participants reported high levels of sleepiness while driving after very moderate sleep restriction. They were able to identify increasing sleepiness during the test period, could decide to cease driving and in most cases were sufficiently sleepy to achieve sleep during the daytime session. However, the levels of sleepiness achieved prior to driving cessation suggest poor accuracy in self-perception and regulation. This presents practical issues for the implementation of fatigue and sleep-related strategies to improve driver safety.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Introduction: Sleepiness contributes to a substantial proportion of fatal and severe road crashes. Efforts to reduce the incidence of sleep-related crashes have largely focussed on driver education to promote self-regulation of driving behaviour. However, effective self-regulation requires accurate self-perception of sleepiness. The aim of this study was to assess capacity to accurately identify sleepiness, and self-regulate driving cessation, during a validated driving simulator task. Methods: Participants comprised 26 young adult drivers (20-28 years) who had open licenses. No other exclusion criteria where used. Participants were partially sleep deprived (05:00 wake up) and completed a laboratory-based hazard perception driving simulation, counterbalanced to either at mid-morning or mid-afternoon. Established physiological measures (i.e., EEG, EOG) and subjective measures (Karolinska Sleepiness Scale), previously found sensitive to changes in sleepiness levels, were utilised. Participants were instructed to ‘drive’ on the simulator until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 36.1 minutes (±17.7 minutes). Subjective sleepiness increased significantly from the beginning (KSS=6.6±0.7) to the end (KSS=8.2±0.5) of the driving period. No significant differences were found for EEG spectral power measures of sleepiness (i.e., theta or alpha spectral power) from the start of the driving task to the point of cessation of driving. During the nap opportunity, 88% of the participants (23/26) were able to reach sleep onset with an average latency of 9.9 minutes (±7.5 minutes). The average nap duration was 15.1 minutes (±8.1 minutes). Sleep architecture during the nap was predominately comprised of Stages I and II (combined 92%). Discussion: Participants reported high levels of sleepiness during daytime driving after very moderate sleep restriction. They were able to report increasing sleepiness during the test period despite no observed change in standard physiological indices of sleepiness. This increased subjective sleepiness had behavioural validity as the participants had high ‘napability’ at the point of driving cessation, with most achieving some degree of subsequent sleep. This study suggests that the nature of a safety instruction (i.e. how to view sleepiness) can be a determinant of driver behaviour.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Objectives To examine the effects on monotonous driving of normal sleep versus one night of sleep restriction in continuous positive airway pressure (CPAP) treated obstructive sleep apnoea (OSA) patients compared with age matched healthy controls. Methods Nineteen CPAP treated compliant male OSA patients (OSA-treated patients (OPs)), aged 50–75 years, and 20 healthy age-matched controls underwent both a normal night’s sleep and sleep restriction to 5 h (OPs remained on CPAP) in a counterbalanced design. All participants completed a 2 h afternoon monotonous drive in a realistic car simulator. Driving was monitored for sleepiness-related minor and major lane deviations, with ‘safe’ driving time being total time driven prior to first major lane deviation. EEGs were recorded continuously, and subjective sleepiness ratings were taken at regular intervals throughout the drive. Results After a normal night’s sleep, OPs and controls did not differ in terms of driving performance or in their ability to assess the levels of their own sleepiness, with both groups driving ‘safely’ for approximately 90 min. However, after sleep restriction, OPs had a significantly shorter (65 min) safe driving time and had to apply more compensatory effort to maintain their alertness compared with controls. They also underestimated the enhanced sleepiness. Nevertheless, apart from this caveat, there were generally close associations between subjective sleepiness, likelihood of a major lane deviation and EEG changes indicative of sleepiness. Conclusions With a normal night’s sleep, effectively treated older men with OSA drive as safely as healthy men of the same age. However, after restricted sleep, driving impairment is worse than that of controls. This suggests that, although successful CPAP treatment can alleviate potential detrimental effects of OSA on monotonous driving following normal sleep, these patients remain more vulnerable to sleep restriction.