Performance metrics for characterization of a seizure detection algorithm for offline and online use

Purpose: To select appropriate previously reported performance metrics to evaluate a new seizure detection algorithm for offline and online analysis, and thus quantify any performance variation between these metrics. Methods: Traditional offline algorithms mark out any EEG section (epoch) of a seizure (event), so that neurologists only analyze the detected and adjacent sections. Thus, offline algorithms could be evaluated using number of correctly detected events, or event-based sensitivity (SEVENT), and epoch-based specificity (percentage of incorrectly detected background epochs). In contrast, online seizure detection (especially, data selection) algorithms select for transmission only the detected EEG sections and hence need to detect the entire duration of a seizure. Thus, online algorithms could be evaluated using percentage of correctly detected seizure duration, or epoch-based sensitivity (SEPOCH), and epoch-based specificity. Here, a new seizure detection algorithm is evaluated using the selected performance metrics for epoch duration ranging from 1s to 60s. Results: For 1s epochs, the area under the event-based sensitivity-specificity curve was 0.95 whilst SEPOCH achieves 0.81. This difference is not surprising, as intuitively, detecting any epoch within a seizure is easier than detecting every epoch - especially as seizures evolve over time. For longer epochs of 30s or 60s, SEVENT falls to 0.84 and 0.82 respectively and SEPOCH reduces to 0.76. Here, decreased SEVENT shows that fewer seizures are detected, possibly due to easy-to-detect short seizure sections being masked by surrounding EEG. However, detecting one long epoch constitutes a larger percentage of a seizure than a shorter one and thus SEPOCH does not decrease proportionately. Conclusions: Traditional offline and online seizure detection algorithms require different metrics to effectively evaluate their performance for their respective applications. Using such metrics, it has been shown that a decrease in performance may be expected when an offline seizure detection algorithm (especially with short epoch duration) is used for online analysis.Accepted versio

Optimal features for online seizure detection

This study identifies characteristic features in scalp EEG that simultaneously give the best discrimination between epileptic seizures and background EEG in minimally pre-processed scalp data; and have minimal computational complexity to be suitable for online, real-time analysis. The discriminative performance of 65 previously reported features has been evaluated in terms of sensitivity, specificity, area under the sensitivity-specificity curve (AUC), and relative computational complexity, on 47 seizures (split in 2,698 2 s sections) in over 172 h of scalp EEG from 24 adults. The best performing features are line length and relative power in the 12.5-25 Hz band. Relative power has a better seizure detection performance (AUC = 0.83; line length AUC = 0.77), but is calculated after the discrete wavelet transform and is thus more computationally complex. Hence, relative power achieves the best performance for offline detection, whilst line length would be preferable for online low complexity detection. These results, from the largest systematic study of seizure detection features, aid future researchers in selecting an optimal set of features when designing algorithms for both standard offline detection and new online low computational complexity detectors. © International Federation for Medical and Biological Engineering 2012

An introduction to future truly wearable medical devices--from application to ASIC.

Accepted versio

Charge dependence of neoclassical and turbulent transport of light impurities on MAST

Carbon and nitrogen impurity transport coefficients are determined from gas puff experiments carried out during repeat L-mode discharges on the Mega-Amp Spherical Tokamak (MAST) and compared against a previous analysis of helium impurity transport on MAST. The impurity density profiles are measured on the low-field side of the plasma, therefore this paper focuses on light impurities where the impact of poloidal asymmetries on impurity transport is predicted to be negligible. A weak screening of carbon and nitrogen is found in the plasma core, whereas the helium density profile is peaked over the entire plasma radius.Comment: 17 pages, 7 figure

Validation of gyrokinetic modelling of light impurity transport including rotation in ASDEX Upgrade

Upgraded spectroscopic hardware and an improved impurity concentration calculation allow accurate determination of boron density in the ASDEX Upgrade tokamak. A database of boron measurements is compared to quasilinear and nonlinear gyrokinetic simulations including Coriolis and centrifugal rotational effects over a range of H-mode plasma regimes. The peaking of the measured boron profiles shows a strong anti-correlation with the plasma rotation gradient, via a relationship explained and reproduced by the theory. It is demonstrated that the rotodiffusive impurity flux driven by the rotation gradient is required for the modelling to reproduce the hollow boron profiles at higher rotation gradients. The nonlinear simulations validate the quasilinear approach, and, with the addition of perpendicular flow shear, demonstrate that each symmetry breaking mechanism that causes momentum transport also couples to rotodiffusion. At lower rotation gradients, the parallel compressive convection is required to match the most peaked boron profiles. The sensitivities of both datasets to possible errors is investigated, and quantitative agreement is found within the estimated uncertainties. The approach used can be considered a template for mitigating uncertainty in quantitative comparisons between simulation and experiment.Comment: 19 pages, 11 figures, accepted in Nuclear Fusio

The linear tearing instability in three dimensional, toroidal gyrokinetic simulations

Linear gyro-kinetic simulations of the classical tearing mode in three-dimensional toroidal geometry were performed using the global gyro kinetic turbulence code, GKW . The results were benchmarked against a cylindrical ideal MHD and analytical theory calculations. The stability, growth rate and frequency of the mode were investigated by varying the current profile, collisionality and the pressure gradients. Both collision-less and semi-collisional tearing modes were found with a smooth transition between the two. A residual, finite, rotation frequency of the mode even in the absense of a pressure gradient is observed which is attributed to toroidal finite Larmor-radius effects. When a pressure gradient is present at low collisionality, the mode rotates at the expected electron diamagnetic frequency. However the island rotation reverses direction at high collisionality. The growth rate is found to follow a $\eta^{1/7}$ scaling with collisional resistivity in the semi-collisional regime, closely following the semi-collisional scaling found by Fitzpatrick. The stability of the mode closely follows the stability using resistive MHD theory, however a modification due to toroidal coupling and pressure effects is seen

Discriminating between best performing features for seizure detection and data selection

Seizure detection algorithms have been developed to solve specific problems, such as seizure onset detection, occurrence detection, termination detection and data selection. It is thus inherent that each type of seizure detection algorithm would detect a different EEG characteristic (feature). However most feature comparison studies do not specify the seizure detection problem for which their respective features have been evaluated. This paper shows that the best features/algorithm bases are not the same for all types of algorithms but depend on the type of seizure detection algorithm wanted. To demonstrate this, 65 features previously evaluated for online seizure data selection are re-evaluated here for seizure occurrence detection, using performance metrics pertinent to each seizure detection type whilst keeping the testing methodology the same. The results show that the best performing features/algorithm bases for data selection and occurrence detection algorithms are different and that it is more challenging to achieve high detection accuracy for the former seizure detection type. This paper also provides a comprehensive evaluation of the performance of 65 features for seizure occurrence detection to aid future researchers in choosing the best performing feature(s) to improve seizure detection accuracy. © 2013 IEEE

Severe pneumonia due to Parachlamydia acanthamoebae following intranasal inoculation: a mice model.

Parachlamydia acanthamoebae is an obligate intracellular bacterium naturally infecting free-living amoebae. The role of this bacterium as an agent of pneumonia is suggested by sero-epidemiological studies and molecular surveys. Furthermore, P. acanthamoebae may escape macrophages microbicidal effectors. Recently, we demonstrated that intratracheal inoculation of P. acanthamoebae induced pneumonia in 100% of infected mice. However, the intratracheal route of infection is not the natural way of infection and we therefore developed an intranasal murine model. Mice inoculated with P. acanthamoebae by intranasal inoculation lost 18% of their weight up to 8 days post-inoculation. All mice presented histological signs of pneumonia at day 2, 4, 7, and 10 post-inoculation, whereas no control mice harboured signs of pneumonia. A 5-fold increase in bacterial load was observed from day 0 to day 4 post-inoculation. Lungs of inoculated mice were positive by Parachlamydia-specific immunohistochemistry 4 days post-inoculation, and P. acanthamoebae were localized within macrophages. Thus, we demonstrated that P. acanthamoebae induce a severe pneumonia in mice. This animal model (i) further supports the role of P. acanthamoebae as an agent of pneumonia, confirming the third Koch postulate, and (ii) identified alveolar macrophages as one of the initial cells where P. acanthamoebae is localized following infection

Retaining young Catholics in the church: assessing the importance of parental example

Drawing on data from a survey conducted among 9,810 young people in England, Scotland, and Wales, this study examines parental and peer influence on church attendance among 2146 13- to 15-year-old students who identified themselves as Catholics. The data suggested that young Catholics who practise their Catholic identity by attending church do so largely because their parents are Catholic churchgoers. Moreover, young Catholic churchgoers are most likely to keep going if both mother and father are Catholic churchgoers. Among this age group of young Catholics both peer support and attending a church school are also significant, but account for little additional variance after taking parental church-going into account. The implication from these findings for a Catholic Church strategy for ministry among children and young people within England, Scotland and Wales is that it may be wise to invest in the education and formation of Catholic parents