The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a new approach to identify the respiratory phases of heart cycles from acceleration signals (i.e., seismocardiogram) recorded from the sternum, in back to front direction. The acceleration signals were recorded simultaneously with a single lead electrocardiogram (ECG), and the respiratory signal (using a chest band strain gauge) from 20 healthy subjects. Two accelerometer-derived...
In this paper we investigated the feasibility of manufacturing planar antennas on paper substrate using the screen-printing method. We designed and manufactured dipole, bowtie and patch antennas and measured their performance.
The bio-imaging techniques have widespread applications from diagnosing diseases to investigating the body tissues at the cells level. Traditionally, these techniques were used mainly in the orthopedic treatment. However, with the development of infrared cameras, ultrasound, and radio wave technology, they are used in different medical fields such as cardiovascular analysis, neurological treatment...
The significance of identifying early non-cavitated carious lesions and monitoring the lesion extent has led to increasing prospects for prevention, early diagnosis, and implementation of conservative treatments. This paper emphasizes the importance of speckle reduction and possible lesion segmentation options of optical coherence tomography (OCT) images prior to caries detection. First, a comparison...
Proton magnetic resonance spectroscopic imaging (MRSI) provides spatial information about tissue metabolite concentrations used in differentiating diseased from normal tissue. Obtaining metabolic maps with high spatial resolution requires long acquisition time where the patient has to lie still inside the magnet bore (scanner) especially if classical Chemical Shift Imaging (CSI) is used. To reduce...
Electroencephalogram (EEG) signal, the signature of brain activity, can be used to quantify for human performance evaluation. There are ongoing efforts by scientists and researchers in this area. Different traditional and novel signal processing and analysis methods have been applied to evaluate performance, mental workload, and task engagement based on EEG signals. Linear change in the indices with...
Different types of analyses of scalp and intracranial electroencephalography (EEG) recordings using linear and nonlinear time series analysis method have been done. They showed strong evidence of detectable changes in the EEG dynamics from minutes up to several hours in advance of seizure onset. The predictive performance of univariate and bivariate measures, comprising both linear and non-linear...
In this paper, we present a fuzzy rule-based system for the automatic detection of seizures in the intracranial EEG (IEEG) recordings. A total of 302.7 hours of the IEEG with 78 seizures, recorded from 21 patients aged between 10 and 47 years were used for the evaluation of the system. After preprocessing, temporal, spectral, and complexity features were extracted from the segmented IEEGs. The results...
We present a method for automatic detection of seizures in intracranial EEG recordings from patients suffering from medically intractable focal epilepsy.We designed a fuzzy rule-based seizure detection system based on knowledge obtained from experts’ reasoning. Temporal, spectral, and complexity features were extracted from IEEG segments, and spatio-temporally integrated using the fuzzy rule-based...
This paper presents a method based on fractal dimensions to characterize electroencephalogram (EEG) signals, and differentiate between healthy and epileptic EEG data sets. The estimated correlation fractal dimension is considerably lower for intracranial invasive EEG recordings as compared to non-invasive scalp recordings. The epileptic EEG is also shown to have lower correlation dimension than healthy...
A robust method of detecting determinism for short time series is proposed and applied to both healthy and epileptic EEG signals. The method provides a robust measure of determinism through characterizing the trajectories of the signal components which are obtained through singular value decomposition. Robustness of the method is shown by calculating proposed index of determinism at different levels...
A brain-computer interface (BCI) is a system that conveys messages and commands directly from the human brain to a computer. The BCI system described in this work is based on P300 speller BCI paradigm designed by Farwell and Donchin in 1988. It has been the most widely used and a benchmark in P300 BCI. In this paradigm, a 6x6 matrix of letters and numbers is displayed and subject focuses on a character...
Most current wireless biomedical signal transceivers use range-limiting communication. This work presents a low-cost biomedical signal transceiver that uses Bluetooth wireless technology. The design is implemented in a modular form to be adaptable to different types of biomedical signals. The signal front end obtains and processes incoming signals, which are then transmitted via a microcontroller...
This paper presents a scheme for image decomposition and reconstruction, using complex Gabor wavelets. Gabor functions have been used extensively in areas related to the human visual system due to their localization in space and bandlimited properties. However, since the standard two-sided Gabor functions are not orthogonal and lead to nearly singular Gabor matrices, they have been used in the decomposition...
A novel method is proposed here to determine whether a time series is deterministic even in the presence of noise. The method is the extension of an existing method based on smoothness analysis of the signal in state space with surrogate data testing. While classical measures fail to detect determinism when the time series is corrupted by noise, the proposed method can clearly distinguish between...
Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper...
This paper describes the implementation of a human computer interface based on eye tracking. Current commercially available systems exist, but have limited use due mainly to their large cost. The system described in this paper was designed to be a low cost and unobtrusive. The technique was video-oculography assisted by corneal reflections. An off-the shelf CCD webcam was used to capture images. The...
In this paper, the performance of five classifiers in P300 speller paradigm are compared. Theses classifiers are Linear Support Vector Machine (LSVM), Gaussian Support Vector Machine (GSVM), Neural Network (NN), Fisher Linear Discriminant (FLD), and Kernel Fisher Discriminant (KFD). In classification of P300 waves, there has been a trend to use SVM classifiers. Although they have shown a good performance,...
Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper...
In this paper, the performance of five classifiers in P300 speller paradigm are compared. Theses classifiers are Linear Support Vector Machine (LSVM), Gaussian Support Vector Machine (GSVM), Neural Network (NN), Fisher Linear Discriminant (FLD), and Kernel Fisher Discriminant (KFD). In classification of P300 waves, there has been a trend to use SVM classifiers. Although they have shown a good performance,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.