Spike pattern recognition by supervised classification in low dimensional embedding space

© The Author(s) 2016. This article is published with open access at Springerlink.com under the terms of the Creative Commons Attribution License 4.0, (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Epileptiform discharges in interictal electroencephalography (EEG) form the mainstay of epilepsy diagnosis and localization of seizure onset. Visual analysis is rater-dependent and time consuming, especially for long-term recordings, while computerized methods can provide efficiency in reviewing long EEG recordings. This paper presents a machine learning approach for automated detection of epileptiform discharges (spikes). The proposed method first detects spike patterns by calculating similarity to a coarse shape model of a spike waveform and then refines the results by identifying subtle differences between actual spikes and false detections. Pattern classification is performed using support vector machines in a low dimensional space on which the original waveforms are embedded by locality preserving projections. The automatic detection results are compared to experts’ manual annotations (101 spikes) on a whole-night sleep EEG recording. The high sensitivity (97 %) and the low false positive rate (0.1 min−1), calculated by intra-patient cross-validation, highlight the potential of the method for automated interictal EEG assessment.Peer reviewedFinal Published versio

Echocardiography practice, training and accreditation in the intensive care: document for the World Interactive Network Focused on Critical Ultrasound (WINFOCUS)

Echocardiography is increasingly used in the management of the critically ill patient as a non-invasive diagnostic and monitoring tool. Whilst in few countries specialized national training schemes for intensive care unit (ICU) echocardiography have been developed, specific guidelines for ICU physicians wishing to incorporate echocardiography into their clinical practice are lacking. Further, existing echocardiography accreditation does not reflect the requirements of the ICU practitioner. The WINFOCUS (World Interactive Network Focused On Critical UltraSound) ECHO-ICU Group drew up a document aimed at providing guidance to individual physicians, trainers and the relevant societies of the requirements for the development of skills in echocardiography in the ICU setting. The document is based on recommendations published by the Royal College of Radiologists, British Society of Echocardiography, European Association of Echocardiography and American Society of Echocardiography, together with international input from established practitioners of ICU echocardiography. The recommendations contained in this document are concerned with theoretical basis of ultrasonography, the practical aspects of building an ICU-based echocardiography service as well as the key components of standard adult TTE and TEE studies to be performed on the ICU. Specific issues regarding echocardiography in different ICU clinical scenarios are then described

Phosphate removal and recovery from water using nanocomposite of immobilized magnetite nanoparticles on cationic polymer

Peer Reviewe