Automatic Identification of Epileptic Seizures from EEG Signals using Sparse Representation-based Classification

Identifying seizure activities in non-stationary electroencephalography (EEG) is a challenging task, since it is time-consuming, burdensome, and dependent on expensive human resources and subject to error and bias. A computerized seizure identification scheme can eradicate the above problems, assist clinicians and benefit epilepsy research. So far, several attempts were made to develop automatic systems to help neurophysiologists accurately identify epileptic seizures. In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. The proposed method is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. Furthermore, the proposed method does not require additional preprocessing and extraction of features which is common in the existing methods. The proposed method reached the sensitivity, specificity and accuracy of 100% in 8 out of 9 scenarios. It is also robust to the measurement noise of level as much as 0 dB. Compared to state-of-the-art algorithms and other common methods, the proposed method outperformed them in terms of sensitivity, specificity and accuracy. Moreover, it includes the most comprehensive scenarios for epileptic seizure detection, including different combinations of 2 to 5 class scenarios. The proposed automatic identification of epileptic seizures method can reduce the burden on medical professionals in analyzing large data through visual inspection as well as in deprived societies suffering from a shortage of functional magnetic resonance imaging (fMRI) equipment and specialized physician

Axial resistance of CFA piles in Dublin boulder clay

This paper describes the results of static compression and tension load tests performed on three-instrumented large diameter Continuous Flight Auger piles installed in Dublin boulder clay. The piles developed very high shaft resistance and, in contrast to piles driven into boulder clay which exhibit friction fatigue, the shaft distribution was uniform along the pile shaft. This resulted in the normalised average shear resistance being mobilised by a bored pile exceeding that of a pile driven in similar ground conditions. In contrast the base resistance of the test piles were significantly lower than a pile driven in similar ground conditions.Not applicableUCD Urban Institute Irelandti,ab,sp.kpw25/8/1