Evaluating the Window Size's Role in Automatic EEG Epilepsy Detection.

Electroencephalography is one of the most commonly used methods for extracting information about the brain's condition and can be used for diagnosing epilepsy. The EEG signal's wave shape contains vital information about the brain's state, which can be challenging to analyse and interpret by a human observer. Moreover, the characteristic waveforms of epilepsy (sharp waves, spikes) can occur randomly through time.

Neutrophil anti-neutrophil cytoplasmic autoantibody proteins: bactericidal increasing protein, lactoferrin, cathepsin, and elastase as serological markers of inflammatory bowel and other diseases.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract comprising Crohn's disease and ulcerative colitis. Although the pathogenesis of the disease is not clearly defined yet, environmental, genetic and other factors contribute to the onset of the disease. Apart from the clinical and histopathological findings, several serological biomarkers are also employed to detect IBD.

PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease.

In this paper, we describe the PERFORM system for the continuous remote monitoring and management of Parkinson's disease (PD) patients. The PERFORM system is an intelligent closed-loop system that seamlessly integrates a wide range of wearable sensors constantly monitoring several motor signals of the PD patients. Data acquired are pre-processed by advanced knowledge processing methods, integrated by fusion algorithms to allow health professionals to remotely monitor the overall status of the patients, adjust medication schedules and personalize treatment.

Modeling and simulation of speed selection on left ventricular assist devices.

The control problem for LVADs is to set pump speed such that cardiac output and pressure perfusion are within acceptable physiological ranges. However, current technology of LVADs cannot provide for a closed-loop control scheme that can make adjustments based on the patient's level of activity. In this context, the SensorART Speed Selection Module (SSM) integrates various hardware and software components in order to improve the quality of the patients' treatment and the workflow of the specialists.

Adverse event prediction in patients with left ventricular assist devices.

This work presents the Treatment Tool, which is a component of the Specialist's Decision Support Framework (SDSS) of the SensorART platform. The SensorART platform focuses on the management of heart failure (HF) patients, which are treated with implantable, left ventricular assist devices (LVADs). SDSS supports the specialists on various decisions regarding patients with LVADs including decisions on the best treatment strategy, suggestion of the most appropriate candidates for LVAD weaning, configuration of the pump speed settings, while also provides data analysis tools for new knowledge extraction.

Automated knowledge-based fuzzy models generation for weaning of patients receiving ventricular assist device (VAD) therapy.

The SensorART project focus on the management of heart failure (HF) patients which are treated with implantable ventricular assist devices (VADs). This work presents the way that crisp models are transformed into fuzzy in the weaning module, which is one of the core modules of the specialist's decision support system (DSS) in SensorART. The weaning module is a DSS that supports the medical expert on the weaning and remove VAD from the patient decision.

Knowledge Editor and execution engine development for optimal ventricular assist device weaning.

In this work, the weaning module of the SensorART specialist decision support system (SDSS) is presented. SensorART focuses on the treatment of patients suffering from end-stage heart failure (HF). The use of a ventricular assist device (VAD) is the main treatment for HF patients.

An intelligent Decision Support System for the treatment of patients receiving ventricular assist device (VAD) support.

The scope of this paper is to present the Specialist's Decision Support System (SDSS), part of the overall Decision Support Framework that is developed under the SensorART platform. The SensorART platform focuses on the management and remote treatment of patients suffering from end-stage heart failure. The SDSS assists specialists on designing the best treatment plan for their patients before and after VAD implantation, analyzing patients' data, extracting new knowledge, and making informative decisions.

Detection of fetal heart rate through 3-D phase space analysis from multivariate abdominal recordings.

A novel three-stage methodology for the detection of fetal heart rate (fHR) from multivariate abdominal ECG recordings is introduced. In the first stage, the maternal R-peaks and fiducial points (maternal QRS onset and offset) are detected, using band-pass filtering and phase space analysis. The maternal fiducial points are used to eliminate the maternal QRS complexes from the abdominal ECG recordings.

An automated methodology for fetal heart rate extraction from the abdominal electrocardiogram.

This paper introduces an automated methodology for the extraction of fetal heart rate from cutaneous potential abdominal electrocardiogram (abdECG) recordings. A three-stage methodology is proposed. Having the initial recording, which consists of a small number of abdECG leads in the first stage, the maternal R-peaks and fiducial points (QRS onset and offset) are detected using time-frequency (t-f) analysis and medical knowledge.

Maternal and fetal heart rate extraction from abdominal recordings using multi-scale principal components analysis.

A three-stage methodology for the extraction of maternal and fetal heart rate using abdominal ECG leads, is presented. In the first stage, the maternal R-peaks and fiducial points (maternal QRS onset and offset) are detected, using multiscale principal components analysis (MSPCA) and the Smoothed Nonlinear Energy Operator (SNEO). Maternal fiducial points are used to eliminate the maternal QRS complexes from the abdominal ECG recordings.