9 research outputs found

    Exploring temporal information in neonatal seizures using a dynamic time warping based SVM kernel

    Get PDF
    Seizure events in newborns change in frequency, morphology, and propagation. This contextual information is explored at the classifier level in the proposed patient-independent neonatal seizure detection system. The system is based on the combination of a static and a sequential SVM classifier. A Gaussian dynamic time warping based kernel is used in the sequential classifier. The system is validated on a large dataset of EEG recordings from 17 neonates. The obtained results show an increase in the detection rate at very low false detections per hour, particularly achieving a 12% improvement in the detection of short seizure events over the static RBF kernel based system

    Evaluation of different signal processing methods in time and frequency domain for brain-computer interface applications

    Get PDF
    Brain-computer interface (BCI) has been widely introduced in many medical applications. One of the main challenges in BCI is to run the signal processing algorithms in real-time which is challenging and usually comes with high processing unit costs. BCIs based on motor imagery task are introduced for severe neurological diseases especially locked-in patients. A common concept is to detect one’s movement intention and use it to control external devices such as wheelchair or rehabilitation devices. In real-time BCI, running the signal processing algorithms might not always be possible due to the complexity of the algorithms. Moreover, the speed of the affordable computational units is not usually enough for those applications. This study evaluated a range of feature extraction methods which are commonly used for such realtime BCI applications. Electroencephalogram (EEG) and Electrooculogram (EOG) data available through IEEE Brain Initiative repository was used to investigate the performance of different feature extraction methods including template matching, statistical moments, selective bandpower, and fast Fourier transform (FFT) power spectrum. The support vector machine (SVM) was used for classification. The result indicates that there is not a significant difference when utilizing different feature extraction methods in terms of movement prediction although there is a vast difference in the computational time needed to extract these features. The results suggest that computational time could be considered as the primary parameter when choosing the feature extraction methods as there is no significant difference between the results when different features extraction methods are used

    Dynamic classifiers for neonatal brain monitoring

    Get PDF
    Brain injury due to lack of oxygen or impaired blood flow around the time of birth, may cause long term neurological dysfunction or death in severe cases. The treatments need to be initiated as soon as possible and tailored according to the nature of the injury to achieve best outcomes. The Electroencephalogram (EEG) currently provides the best insight into neurological activities. However, its interpretation presents formidable challenge for the neurophsiologists. Moreover, such expertise is not widely available particularly around the clock in a typical busy Neonatal Intensive Care Unit (NICU). Therefore, an automated computerized system for detecting and grading the severity of brain injuries could be of great help for medical staff to diagnose and then initiate on-time treatments. In this study, automated systems for detection of neonatal seizures and grading the severity of Hypoxic-Ischemic Encephalopathy (HIE) using EEG and Heart Rate (HR) signals are presented. It is well known that there is a lot of contextual and temporal information present in the EEG and HR signals if examined at longer time scale. The systems developed in the past, exploited this information either at very early stage of the system without any intelligent block or at very later stage where presence of such information is much reduced. This work has particularly focused on the development of a system that can incorporate the contextual information at the middle (classifier) level. This is achieved by using dynamic classifiers that are able to process the sequences of feature vectors rather than only one feature vector at a time

    Comparison of resting state functional networks in HIV infected and uninfected children at age 9 years

    Get PDF
    Over 2.5 million children are infected with HIV, the majority of whom reside in Sub-Saharan Africa. Treatment coverage is steadily gaining momentum, reducing mortality and morbidity. Yet little is known about brain development in HIV-infected (HIV+) children who are on highly-active antiretroviral therapy (ART), with viral load suppression from a young age. Here, we use resting state fMRI (rs-fMRI) to examine the impact of HIV and ART on the development of functional networks in 9-year-old vertically HIV-infected children compared to age-matched controls of similar socioeconomic status. We present analyses for a sample of 40 HIV+ (9.2 ± 0.20 years; 16 males) children from the Children with HIV Early Antiretroviral (CHER) clinical trial (Cotton et al. 2013; Violari et al. 2008) and 24 uninfected (12 exposed; 12 males; 9.6 ± 0.52 years) controls from an interlinking vaccine trial (Madhi et al. 2010). Scans were performed at the Cape Universities Body Imaging Centre (CUBIC) in Cape Town, South Africa. We investigated HIV-related differences in within- and between-network functional connectivity (FC) using independent component analysis(ICA) and seed-based correlation analysis (SCA). For SCA, seeds were placed in the structural core, in regions implicated in HIV-related between-group differences at age 7 years, and in regions associated with neuropsychological domains impaired in our cohort. In addition, we evaluated associations of past and present immune health measures with within-network connectivity using ICA. We found no HIV-related intra-network FC differences within any ICA-generated RSNs at age 9 years, perhaps as a result of within-network connectivity not being sufficiently robust at this age. We found a positive association of CD4%, both current and in infancy, with functional integration of left lobule 7 into the cerebellum network at age 9 years. Long-term impact of early immune health supports recently-revised policies of commencing ART immediately in HIV+ neonates. ii Compared to uninfected children, HIV+ children had increased FC to several seeds. Firstly, to seeds associated with the planning and visual perception neuropsychological domains. Secondly, to structural core seeds in the extrastriate visual cortex (of the medial visual network) and the right angular gyrus (of the temporoparietal network). Finally, to left paracentral (somatosensory network) and right precuneus (posterior DMN) seeds previously revealing between-group differences at age 7 years. The connections with greater FC in HIV+ children may variously indicate functional recruitment of additional brain capacity, immature excess of short-range connections, and/or immature excess of between-network connections. In conclusion, despite early ART and early virologic suppression, HIV+ children demonstrate instances of abnormal FC at age 9 years. Disruption to visual cortex is marked, consistent with indications from neuropsychological testing that visual perception is disrupted. The profile of HIV- and/or ART-related effects on FC differs considerably between the two ages of 7 and 9 years, but both show characteristics of immature functional organisation compared with age-matched controls

    Life Sciences Program Tasks and Bibliography

    Get PDF
    This document includes information on all peer reviewed projects funded by the Office of Life and Microgravity Sciences and Applications, Life Sciences Division during fiscal year 1995. Additionally, this inaugural edition of the Task Book includes information for FY 1994 programs. This document will be published annually and made available to scientists in the space life sciences field both as a hard copy and as an interactive Internet web pag
    corecore