Higher-Order Spectral Analysis Combined with a Convolution Neural Network for Atrial Fibrillation Detection-Preliminary Study.

The global burden of atrial fibrillation (AFIB) is constantly increasing, and its early detection is still a challenge for public health and motivates researchers to improve methods for automatic AFIB prediction and management. This work proposes higher-order spectra analysis, especially the bispectrum of electrocardiogram (ECG) signals combined with the convolution neural network (CNN) for AFIB detection. Like other biomedical signals, ECG is non-stationary, non-linear, and non-Gaussian in nature, so the spectra of higher-order cumulants, in this case, bispectra, preserve valuable features.

Semi-Quantitative Method of Assessing the Thrombogenicity of Biomaterials Intended for Long-Term Blood Contact.

Biomaterials used in cardiosurgical implants and artificial valves that have long-term contact with blood pose a great challenge for researchers due to the induction of thrombogenicity. So far, the assessment of the thrombogenicity of biomaterials has been performed with the use of highly subjective descriptive methods, which has made it impossible to compare the results of various experiments. The aim of this paper was to present a new semi-quantitative method of thrombogenicity assessment based on scanning electron microscope (SEM) images of an adhered biological material deposited on the surfaces of prepared samples.

The Assessment of the Condition of Knee Joint Surfaces with Acoustic Emission Analysis.

The knee joint, being the largest joint in the human body, is responsible for a great percentage of leg movements. The diagnosis of the state of knee joints is usually based on X-ray scan, ultrasound imaging, computerized tomography (CT), magnetic resonance imaging (MRI), or arthroscopy. In this study, we aimed to create an inexpensive, portable device for recording the sound produced by the knee joint, and a dedicated application for its analysis.

Gastric slow wave rhythm identification using new approach based on noise-assisted multivariate empirical mode decomposition and Hilbert-Huang transform.

Background: Electrogastrography (EGG) is the method of cutaneous recording of the myoelectrical activity of the stomach. A multi-channel signal is recorded non-invasively by means of electrodes placed outside the epigastric area. The normal electrical rhythm of the stomach (slow wave) may become significantly disturbed due to disorders of gastrointestinal tract.

EGG DWPack: System for Multi-Channel Electrogastrographic Signals Recording and Analysis.

Electrogastrography (EGG) is a non-invasive examination method for investigating the myolectrical activity of a stomach. Nowadays, abdominal surface electrogastrography is the one of methods of stomach examination that is used for diagnosing patients with chronic intractable nausea, vomiting and gastroparesis. The electrogastrographic signals are recorded by using cutaneous electrodes placed on the stomach surface.

Empirical Mode Decomposition for slow wave extraction from electrogastrographical signals.

The aim of this study was to investigate the effectiveness of Empirical Mode Decomposition (EMD) for slow wave extraction from multichannel electrogastrographical signal (EGG) the cutaneous recording of gastric myoelectrical activity. From the pacemaker region of stomach both spontaneous depolarization and repolarization occur generating the myoelectrical waves that are called the gastric pacesetter potentials, or slow waves. The 3 cycles per minute (3pcm) (0.

The Use of Continuous Wavelet Transform Based on the Fast Fourier Transform in the Analysis of Multi-channel Electrogastrography Recordings.

This paper presents the analysis of multi-channel electrogastrographic (EGG) signals using the continuous wavelet transform based on the fast Fourier transform (CWTFT). The EGG analysis was based on the determination of the several signal parameters such as dominant frequency (DF), dominant power (DP) and index of normogastria (NI). The use of continuous wavelet transform (CWT) allows for better visible localization of the frequency components in the analyzed signals, than commonly used short-time Fourier transform (STFT).

The extraction of the new components from electrogastrogram (EGG), using both adaptive filtering and electrocardiographic (ECG) derived respiration signal.

Electrogastrographic examination (EGG) is a noninvasive method for an investigation of a stomach slow wave propagation. The typical range of frequency for EGG signal is from 0.015 to 0.

[Laparoscopy or laparotomy in the treatment of ovarian teratomas?].

Background: Mature cystic teratomas (dermoid cyst), are the most common germ cell tumours of the ovary in women of reproductive age. They are usually asymptomatic until they reach considerable size. Frequently, ultrasonography is diagnostic.