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ABSTRACT: As a precursor for investigation of changes in neural activity underlying lapses of responsiveness, we set up a system to simultaneously record functional magnetic resonance imaging (fMRI), eye-video, EOG, and continuous visuomotor response inside an MRI scanner. The BOLD fMRI signal was acquired during a novel 2-D tracking task in which participants (10 males, 10 females) were cued to either briefly stop tracking and close their eyes (Stop+Close) or to briefly stop tracking (Stop) only. The onset and duration of eye-closure and stopping were identified post hoc from eye-video, EOG, and visuomotor response. fMRI data were analyzed using a general linear model (GLM) and tensorial independent component analysis (TICA). The GLM-based analysis identified predominantly increased blood oxygenation level dependent (BOLD) activity during eye-closure and stopping in multisensory areas, sensory-motor integration areas, and default-mode regions. Stopping during tracking elicited increased activity in visual processing areas, sensory-motor integration areas, and premotor areas. TICA separated the spatio-temporal pattern of activity into multiple task-related networks including the 1) occipito-medial frontal eye-movement network, 2) sensory areas, 3) left-lateralized visuomotor network, and 4) fronto-parietal visuomotor network, which were modulated differently by Stop+Close and Stop. The results demonstrate the merits of using simultaneous fMRI, behavioral, and physiological recordings to investigate the mechanisms underlying complex human behaviors in the human brain. Furthermore, knowledge of widespread modulations in brain activity due to voluntary eye-closure or stopping during a continuous visuomotor task is important for studies of the brain mechanisms underlying involuntary behaviors, such as microsleeps and attention lapses, which are often accompanied by brief eye-closure and/or response failures.
IEEE Transactions on Neural Systems and Rehabilitation Engineering 11/2010; · 3.44 Impact Factor
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ABSTRACT: Visuomotor performance and responsiveness deteriorates with time-on-task due to drowsiness and increased propensity to sleep. Frequent episodes of behavioural microsleep (BM) are also common during extended and monotonous tasks. In this study, simultaneous recording of EEG, eye-video, and continuous visuomotor response is used to investigate visuomotor performance and EEG activity during tonic drowsiness and phasic BMs. The data were collected from 20 healthy volunteers while they performed a continuous 2-D pursuit tracking task for 50 min. We identified episodes of BMs by expert visual rating of eye-video and visuomotor response using a set of pre-defined criteria. Visuomotor performance and EEG activity were correlated with and without BM events. A moderate correlation was observed between visuomotor error and theta activity in EEG at a posterior channel (Pz) before the removal of BMs. However, when BMs were removed from the data, the correlation dropped in most subjects. Furthermore, most of the large fluctuations in performance observed during the visuomotor task disappeared after the removal of BMs. This suggests that episodic behaviours such as BMs contribute substantially to fluctuations in performance and to EEG theta activity during an extended task, and that they should be taken into account when studying tonic drowsiness.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: A device capable of continuously monitoring an individual's levels of alertness in real-time is highly desirable for preventing drowsiness and microsleep related accidents. This paper presents a development of non-intrusive and light-insensitive video-based system that uses computer-vision methods to measure facial metric for identifying visible facial signs of drowsiness and behavioral microsleep. The developed system uses a remotely placed camera with a near-infrared illumination to acquire the video. The computer-vision methods are then applied to sequentially localize face, eyes, and eyelids positions to measure ratio of eye closure. The system was evaluated in frontal images of nine subjects with varying facial structures and exhibiting several ratio of eye closure and eye gaze under fully dark and ambient lighting conditions. The preliminary results showed promising results with sufficient accuracy to distinguish between fully closed, half closed, and fully open eyes.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: Lapses in responsiveness (`lapses'), particularly microsleeps and attention lapses, are complete disruptions in performance from ~0.5-15 s. They are of particular importance in the transport sector in which there is a need to maintain sustained attention for extended periods and in which lapses can lead to multiple-fatality accidents.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: Behavioural microsleeps (BMs) are brief episodes of absent responsiveness accompanied by slow-eye-closure. They frequently occur as a consequence of sleep-deprivation, an extended monotonous task, and are modulated by the circadian rhythm and sleep homeostatic pressure. In this paper, a multimodal method to investigate the neural correlates of BMs using simultaneous recording of fMRI, eye-video, VEOG, and continuous visuomotor response is presented. The data were collected from 20 healthy volunteers while they performed a continuous visuomotor tracking task inside an MRI scanner for 50 min. The BMs were identified post-hoc by expert visual rating of eye-video and visuomotor response using a set of pre-defined criteria. fMRI analysis of BMs revealed changes in haemodynamic activity in several cortical and sub-cortical regions associated with visuomotor control and arousal.
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE; 10/2009
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C.H. Yoon,
B. Bodvarsson,
S. Klim,
M. Morkebjerg,
S. Mortensen,
J. Chen,
J.R. Maclaren,
P.K. Luther,
J.M. Squire, P.J. Bones,
R.P. Millane
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ABSTRACT: An automated image analysis system for determining myosin filament azimuthal rotations, or orientations, in electron micrographs of muscle cross sections is described. The micrographs of thin sections intersect the myosin filaments which lie on a triangular lattice. The myosin filament profiles are variable and noisy, and the images exhibit a variable contrast and background. Filament positions are determined by filtering with a point spread function that incorporates the local symmetry of the lattice. Filament orientations are determined by correlation with a template that incorporates the salient filament characteristics, and the orientations are classified using a Gaussian mixture model. The precision of the technique is assessed by application to a variety of micrographs and comparison with manual classification of the orientations. The system provides a convenient, robust, and rapid means of analysing micrographs containing many filaments to study the distribution of filament orientations.
IEEE Transactions on Image Processing 05/2009; · 3.04 Impact Factor
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ABSTRACT: Fast spin echo (FSE) is a means of rapidly acquiring k-space data in magnetic resonance imaging (MRI). Unfortunately, images obtained using FSE often contain artifacts. These are caused primarily by patient motion and transversal magnetisation decay, the latter being characterised by the time constant Ti. This paper presents a study of the effect of data acquisition order on the severity of these effects.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: Bulk motion occurring during the acquisition of magnetic resonance images (MRI) remains a significant limitation in image quality. The paper presents an extension to TRELLIS, a recently developed method of detecting and correcting for bulk motion. Accurate determination of the relative orientations of overlapping strips of k-space is demonstrated. Reconstructions for both simulated and actual MRI acquisitions are presented.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: EEG spectral power has been shown to correlate with level of arousal and alertness in humans. In this paper, we assess its usefulness in the detection of behavioral microsleeps (BMs). Eight non-sleep-deprived normal subjects performed two 1-hour sessions of a continuous tracking task while EEG and facial video were recorded. BMs were identified independent of tracking performance by a human rater by viewing the video recordings. Spectral power, normalized spectral power, and power ratios in the standard EEG bands were calculated using the Burg method on 16 bipolar derivations to form an EEG feature matrix. PCA was used to reduce the dimensionality of the feature matrix and linear discriminant analysis used to form a classifier for each subject. The 8 classifiers were combined using stacked generalization to create an overall detection model and N-fold cross-validation used to determine its performance (Phi=0.30plusmn0.05, meanplusmnSE). While modest, the detection of BMs at such a high temporal resolution (1 s) has not been achieved previously other than by our group
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE; 10/2006
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ABSTRACT: It is critically important for certain occupational groups to remain highly alert throughout their working day. For safety reasons, it would be useful to automatically detect lapses in performance using EEG/EOG. Automating the detection process could be simplified considerably if we could mimic human experts. Surprisingly, it is unclear to what extent human EEG raters are able to detect lapses. Consequently, we undertook a study in which 4 expert EEG raters assessed the level of alertness of 10 air traffic controllers by observing a combination of their EEG and EOG while they performed a 10 min psychomotor vigilance task (PVT). They were specifically required to identify lapses or sleep episodes that might lead to a lapse in PVT performance. A reaction time ges 500 ms was defined as a PVT lapse. There was a total of 101 lapses (mean duration = 1.00 s). Of these, only 6 lapses were detected by one or more raters and all of these were marked as 'sleep'. Overall the human expert raters were unable to reliably identify lapses based only on EEG and EOG. This poor performance suggests an automated system would need to identify subtle features not overtly visible in the EEG
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the; 02/2006
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ABSTRACT: The fractal dimension (FD) of EEG has been shown to be of value in the detection of epileptic seizures. In this paper, we assess its usefulness in detecting behavioural microsleeps. Fifteen non-sleep-deprived normal subjects performed two 1-hour sessions of a continuous tracking task while EEG, EOG and facial video were recorded. Higuchi's algorithm was used to calculate the FD of the EEG. Video lapses were scored independently from tracking performance by a human rater. A subset of data was rated independently by three human raters observing both tracking performance and the video rating to identify behavioural microsleep events. The mean point-biserial correlation between FD and the mean human rating was -0.213 indicating modest agreement. Cross-validated detection performance of the FD was poor with a mean correlation (phi = -0.099). This suggests that, on its own, FD of the EEG is unlikely to be useful for detecting microsleeps
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the; 02/2006
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ABSTRACT: An automated image analysis system for determination of myosin filament orientations in electron micrographs of muscle cross-sections is described. Analysis of the distribution of the orientations is important in studies of muscle structure, particularly for interpretation of x-ray diffraction data. Filament positions are determined by filtering with a point spread function that incorporates the local symmetry in an image. Filament orientations are determined by correlation with a template that incorporates the salient filament characteristics and the orientations classified using a Gaussian mixture model. Application to micrographs and comparison with manual classification of orientations shows that the system is effective.
Digital Image Computing: Techniques and Applications, 2005. DICTA '05. Proceedings 2005; 01/2006
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ABSTRACT: The joint density for a particular trivariate chi-squared distribution given by the diagonal elements of a complex Wishart matrix is derived. This distribution has applications in the processing of multilook synthetic aperture radar data. The expression for the density is in the form of an infinite series that converges rapidly and is simple and fast to compute. The expression is shown to reduce to known forms for a number of special cases and is validated by simulation. The characteristic function is also derived and used to relate joint moments of the trivariate distribution to the parameters of the density function.
Journal of Multivariate Analysis 01/2006; 97(3):655-674. · 0.88 Impact Factor
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ABSTRACT: An automated image analysis system for determination of myosin filament orientations in electron micrographs of muscle cross-sections is described. Analysis of the distribution of the orientations is important in studies of muscle structure, particularly for interpretation of x-ray diffraction data. Filament positions are determined by filtering with a point spread function that incorporates the local symmetry in an image. Filament orientations are determined by correlation with a template that incorporates the salient filament characteristics and the orientations classified using a Gaussian mixture model. Application to micrographs and comparison with manual classification of orientations shows that the system is effective.
Digital Image Computing: Techniques and Applications. 12/2005;
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ABSTRACT: The fractal dimension (FD) of EEG has been shown to be of value in the detection of epileptic seizures. In this paper, we assess its usefulness in detecting behavioural microsleeps. Fifteen non-sleep-deprived normal subjects performed two 1-hour sessions of a continuous tracking task while EEG, EOG and facial video were recorded. Higuchi's algorithm was used to calculate the FD of the EEG. Video lapses were scored independently from tracking performance by a human rater. A subset of data was rated independently by three human raters observing both tracking performance and the video rating to identify behavioural microsleep events. The mean point-biserial correlation between FD and the mean human rating was -0.213 indicating modest agreement. Crossvalidated detection performance of the FD was poor with a mean correlation (.. = -0.099). This suggests that, on its own, FD of the EEG is unlikely to be useful for detecting microsleeps.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2005; 6:5742-5.
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[show abstract]
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ABSTRACT: It is critically important for certain occupational groups to remain highly alert throughout their working day. For safety reasons, it would be useful to automatically detect lapses in performance using EEG/EOG. Automating the detection process could be simplified considerably if we could mimic human experts. Surprisingly, it is unclear to what extent human EEG raters are able to detect lapses. Consequently, we undertook a study in which 4 expert EEG raters assessed the level of alertness of 10 air traffic controllers by observing a combination of their EEG and EOG while they performed a 10 min psychomotor vigilance task (PVT). They were specifically required to identify lapses or sleep episodes that might lead to a lapse in PVT performance. A reaction time .. 500 ms was defined as a PVT lapse. There was a total of 101 lapses (mean duration = 1.00 s). Of these, only 6 lapses were detected by one or more raters and all of these were marked as ;sleep'. Overall the human expert raters were unable to reliably identify lapses based only on EEG and EOG. This poor performance suggests an automated system would need to identify subtle features not overtly visible in the EEG.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2005; 6:5735-7.
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ABSTRACT: The aim of this study was to investigate the presence of apparent non-epileptiform activity arising in the same brain area as epileptiform activity in the EEG of paediatric patients with focal epilepsy. The EEG from eight patients was analyzed by an automated method which detects epochs with a single underlying source having a dipolar potential distribution. The EEG with the highlighted detections was then rated by an EEGer with respect to epileptiform activity. Although EEGer-marked events and computer detections often coincided, in five out of the eight patients a substantial number of other detections were found to arise from the same area as the marked events. The morphology of a high proportion of these other detections did not resemble typical epileptiform activity.
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE; 10/2004
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ABSTRACT: In many high-risk occupations, it is critical that a person remains alert at all times. There is much to be gained by being able to monitor a person on-line and detect lapses of consciousness (LoC) so that remedial action can be taken (e.g., a rest break) to ensure that safety is maintained. In this study, 15 normal subjects were observed on two sessions while they performed a continuous tracking task for a period of 1 hour. EEG, eye movements, tracking performance data and a video of the subject were recorded during the session. This work presents some preliminary results on the phenomenon of lapsing. Only 4 of the 15 subjects did not have a LoC at some stage. Seven subjects had LoCs more than 45 times and 4 more than 100 times during the 2 hours. The mean rate of lapsing over all subjects was 29.1 LoC/h. In contrast, lapses in performance were caused by both lapses of consciousness (30.1%) and attention (69.9%). There was no correlation found between age of subject and number of lapses of consciousness.
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE; 10/2004
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ABSTRACT: Equalizing image noise is shown to be an important step in the automatic detection of microcalcifications in digital mammography. This study extends a well established film-screen noise equalization scheme developed by Veldkamp et al. for application to full-field digital mammogram (FFDM) images. A simple noise model is determined based on the assumption that quantum noise is dominant in direct digital X-ray imaging. Estimation of the noise as a function of the gray level is improved by calculating the noise statistics using a truncated distribution method. Experimental support for the quantum noise assumption is presented for a set of step wedge phantom images. Performance of the noise equalization technique is also tested as a preprocessing stage to a microcalcification detection scheme. It is shown that the square root model based approach which FFDM allows leads to a robust estimation of the high frequency image noise. This provides better microcalcification detection performance when compared to the film-screen noise equalization method developed by Veldkamp. Substantially better results are obtained than when noise equalization is omitted. A database of 124 direct digital mammogram images containing 28 microcalcification clusters was used for evaluation of the method.
IEEE Transactions on Medical Imaging 04/2004; · 3.64 Impact Factor
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ABSTRACT: An image whose region of support is smaller than its bounding rectangle can, in principle, be reconstructed from a subset of the Nyquist samples. However, determining such a sampling set that gives a stable reconstruction is a difficult and computationally intensive problem. An algorithm is developed for determining periodic nonuniform sampling patterns that is orders of magnitude faster than existing algorithms. The speedup is achieved by using a sequential selection algorithm and heuristic metrics for the quality of sampling sets that are fast to compute, as opposed to the more rigorous linear algebraic metrics that have been used previously. Simulations show that the sampling sets determined using the new algorithm give image reconstructions that are of accuracy comparable with those determined by other slower algorithms.
Journal of the Optical Society of America A 02/2003; 20(1):67-77. · 1.56 Impact Factor
