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.
The goal of this paper is to present a novel approach in the automatic diagnosis of ECG abnormalities based on detection of R peaks in the phase space. The features are extracted from detected R peaks using their geometric position on the phase curve. This paper is dealing with classification problem of normal and abnormal ECG signals. The proposed system has been validated with the data from the...
Quantization of signals is required for many transmission, storage and compression applications. The original signal is quantized at the encoder side. At the decoder side, a replica of the original signal that should resemble the original signal in some sense is recovered. Present quantizers make an effort to reduce the distortion of the signal in the sense of reproduction fidelity. Consider scenarios...
This paper presents an optimizing methodology for implementing a multi-layer perceptron (MLP) neural network in a Field Programmable Gate Array (FPGA) device. In order to obtain an efficient implementation, a compromise of time and area is needed. Starting from simulation in the learning phase with fixed point operators, we have developed a methodology which allows the automatic generation of a VHDL...
The nonstationary nature of the brain signals provides a rather unstable input resulting in uncertainty and complexity in the control. Intelligent processing algorithms adapted to the task are a prerequisite for reliable BCI applications. This work presents a novel intelligent processing strategy for the realization of an effective BCI which has the capability to improved classification accuracy and...
According to the symmetric characteristics of bispectrum, a novel feature extraction scheme, which includes the summation-at-every-column feature vector, the summation-at-every-row feature vector and their combination in a triangle area, one of the 12 symmetric areas of bispectrum, is proposed. By using One-against-One (OAO) method of multi classification of Support Vector Machine (SVM), the mean...
Automatic analysis of cardiac arrhythmias is very important for diagnosis of cardiac abnormities. This paper presents a novel approach that classifies ECG signals with the combination of Wavelet transform and Decision tree classification. This approach has two aspects. In the first aspect, we utilize the wavelet transform to extract the ECG signals wavelet coefficients as the first features and utilize...
Real-time implementation of an assistive human-machine interface system based around tongue-movement ear pressure (TMEP) signals is presented, alongside results from a series of simulated control tasks. The implementation of this system into an online setting involves short-term energy calculation, detection, segmentation and subsequent signal classification, all of which had to be reformulated based...
The high order pattern discovery algorithm is applied to classify schizophrenia and health's EEG signals. Samples of 780 schizophrenia and health EEG pieces are classified. The result shows that the classification accuracy can achieve 90% in 6-order. The 6-orders are associated with frontal polar, temporal and occipital regions.
A bass line is an instrumental melody that encapsulates both rhythmic, melodic, and harmonic features and arguably contains sufficient information for accurate genre classification. In this paper a bass line based automatic music genre classification system is described. "Melodic Interval Histograms" are used as features and k-nearest neighbor classifiers are utilized and compared with SVMs...
Besides cardiovascular diseases, heart attacks are the main cause of death around the world. Pre-monitoring or pre-diagnostic helps to prevent heart attacks and strokes. ECG plays a key role in this regard. In recent studies, SVM with different kernel functions and parameter values are applied for classification on ECG data. The classification model of SVM can be improved by assigning membership values...
This paper proposes an emotional stress recognition system with EEG signals using higher order spectra (HOS). A visual induction based acquisition protocol is designed for recording the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) under two emotional stress states of participants, Calm neutral and Negatively exited. After pre-processing the signals, higher order spectra are employed to extract...
This work is an evaluation, to which degree geological information can be obtained from modern remote sensing systems like the multispectral ASTER or the hyperspectral Hyperion sensor for a volcanic region like Teide Volcano (Tenerife, Canary Islands). To account for the enhanced information content these sensors provide, hyperspectral analysis methods, incorporating for example Minimum Noise Fraction-Transformation...
The performance of assistive communication brain-computer interfaces has been studied mostly for languages with alphabetic script. The viability of using such systems for languages with other types of script, such as Chinese, which has a logographic script, is currently poorly understood. Here, a performance analysis of the P300 Speller is presented for Chinese text input. The performance of six distinct...
The detection of central apneas using an unobtrusive pressure sensor array installed in the beds of smart homes could allow comfortable diagnosis of sleep disturbances. To improve central apnea detection, two methods of improving the results of apneas classified by a previously developed method are presented: moving average windowing and window elimination. The first improved classifier sensitivity,...
Research in time-frequency distributions (TFDs) is limited in terms of their use of the available spatial domains and in their target applications. Most of the work up till now has been concentrated mainly on the t-f domain space. This work presents a detailed study about the ambiguity domain (AD), their resemblance in the t-f space and the significance of using such a representation. Further, a novel...
In this study, we analyze brain connectivity based on Granger causality computed from magnetoencephalographic (MEG) activity obtained at the resting state in eight autistic and eight normal subjects along with measures of network connectivity derived from graph theory in an attempt to understand how communication in a human brain network is affected by autism. A connectivity matrix was computed for...
To evaluate the proficiency level of an operating myoelectric hand, we proposed an evaluation index consisting of the accuracy and the reproducibility of electromyography (EMG) signal patterns. Our proposed method is not an absolute evaluation because we use bio-signals, so it is necessary to verify the correlation between the proposed index and performance evaluation to confirm the usefulness of...
Feedback error-related potentials are a promising brain process in the field of rehabilitation since they are related to human learning. Due to the fact that many therapeutic strategies rely on the presentation of feedback stimuli, potentials generated by these stimuli could be used to ameliorate the patient's progress. In this paper we propose a method that can identify, in real-time, feedback evoked...
Prosthetic hands of increasing capability and sophistication are being built, but how does the user tell the hand what to do? One method is to use the low-level electrical signals associated with forearm muscle movement, or electrogmyograms (EMGs). This paper describes an experiment in which supervised learning, or classification, was used to build a model that decides which of a set of hand gestures...
Visual evaluation of long-term EEG recordings is very difficult, time consuming and subjective process. This paper aims to present the research and development of a comprehensive scheme for computer-assisted recognition of behavioral states of sleep in newborns. In clinical practice, the ratio of behavioral states (wakefulness, quiet and active sleep) is used as an important indicator of the brain...
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.