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Cardiac arrhythmia is a class of serious heart diseases that threatens many people. Current arrhythmias diagnostic techniques seem to be partially efficient due to the application limitations either in time or in space. The paper presents a real-time continuous arrhythmias detection system (RECAD) platform based on the wireless sensor network technology. This system provides long-term real-time surveillance...
A method for automatic detection of sleep apnea using pulse photoplethysmography signal (PPG) is proposed. This method is based on a detection of decreases on PPG amplitude fluctuations. The proposed detector is composed of three stages: pre-processing, envelope detection, based on root mean square series or Hilbert transform, and decision algorithm based on an adaptive threshold. The detector has...
Frequent arousals during sleep degrade the quality of sleep and result in sleep fragmentation. Visual inspection of physiological signals to detect the arousal events is inconvenient and time-consuming work. The purpose of this study was to develop an automatic algorithm to detect the arousal events. We proposed the automatic method to detect arousals based on time-frequency analysis and the support...
In this paper, we propose a measuring device implementation to measure ECG, 50 KHz BIA for getting BIA/respiration, and 10~50 Hz GSR for measuring electrical characteristics of skin. To this end, BIA signal is separated by line filter and high impedance element and the interference between signals could be minimized by switching in time domain to separate ECG and GSR signals having the similar frequency...
This paper describes a three-stage system for the detection of neonatal seizures. The first stage detects 5-s seizure segments using signal processing and pattern recognition techniques. In the second stage, the seizure segments overlapping with artifactual segments are marked for post-processing using rules. Rules add intelligence to the spatio-temporal clustering in the third stage, by incorporating...
A novel approach is proposed to deal with the problem of detecting the single trial ERP using a modified RBF neural network, rational Gaussian network. The Gaussian RBF is normalized to obtain optimal behavior of noise suppression even at low SNR. The performance of the proposed scheme is also evaluated with both MSE and the tracking ability. Several experimental results with real ERP signals provide...
To assess retinal changes in diabetic eyes at early stage of retinopathy, retinal responses were examined using multifocal ERG. Seven healthy subjects, 16 diabetics with no apparent retinopathy (NDR) and 9 diabetics who had background diabetic retinopathy (BDR) underwent multifocal ERG testing. The first slice of the second order kernel (K21) were extracted from multifocal ERG record and summed. Three...
Current alarm strategies for physiological monitoring depend on predetermined thresholds without consideration for the heterogeneity between patients or intraoperative variations. To improve upon this situation, we developed an adaptive change point detection scheme to automatically notify the clinician when a change of clinical significance has occurred in the respiratory variables. We modeled end-tidal...
The quality of our life is tied to the quality of our sleep. People with sleep deficits may experience impaired performance, irritability, lack of concentration, and daytime drowsiness. Increased mobility in bed can be a sign of disrupted sleep. Therefore, body movements in bed represent an important behavioral aspect of sleep. In this paper, we propose a method for detection and classification of...
Decoding of kinematic variables from neuronal spike trains is important for neuroprosthetic devices. The spike trains from single units must be extracted from extracellular neural signals and thus spike detection and sorting procedure is essential. Since the spike detection and sorting procedure may yield considerable errors, decoding algorithm should be robust against spike train errors. Here we...
Sleep apnea syndrome (SAS) is a very common sleep disorder disease. Reliable detection of apnea is very crucial for subsequent treatment. In this article, a novel method based on artificial neural network is proposed for such purpose. With its time-invariant property the time delay neural network (TDNN) is adopted in this system to employ the temporal trend of apnea event. As airflow and SaO take...
This paper presents the upgrading of biomedical engineering laboratory training at the Department of Medical Instrumentation Technology of the Technological Educational Institution of Athens (TEI-A), taking place in the framework of the "Upgrading of Undergraduate Curricula of TEI-A" project. The educational material of selected specialized laboratory sectors is totally renewed, and new...
A method of multilead ECG character points detection is introduced in this study. The method includes two main sections: the detection of single lead character points and determination of global character points. The method of single lead character points detection is similar to the traditional ones that use the first differential signal of ECG. While some special modification is adopted. The multilead...
Mismatch negativity (MMN) is an EEG voltage fluctuation caused by the brain's automatic reaction to unexpected changes in a repetitive stimulation. In an experiment we studied 68 infants of which 2/3 were born preterm. Due to noise of large amplitude, the MMN is difficult to detect in a single infant's EEG. Therefore grand average, which is a average of many subjects EEG recordings, is sometimes used...
The new method for automatic sleep stages detection in neonatal EEG was developed. The procedure is based on processing of time profiles computed by adaptive segmentation and subsequent classification of signal graphoelements. The time profiles, functions of the class membership in the course of time, reflect the dynamic EEG structure and may be used for indication of changes in the neonatal sleep...
The purpose of this study is to strengthen feature of MU discharge for classification of motor unit action potentials (MUAPs) into each MUAP train by means of the combination between expansion matching filter and independent component analysis (ICA). From our results, it is found that, when a MUAP waveform is used as a template, expansion coefficients give higher responses at the time points when...
It is critically important for certain occupational groups to remain highly alert throughout their working day. For safety reasons, it would be useful to automatically detect lapses in performance using EEG/EOG. Automating the detection process could be simplified considerably if we could mimic human experts. Surprisingly, it is unclear to what extent human EEG raters are able to detect lapses. Consequently,...
A novel active surface Laplacian electroencephalogram (LEEG) sensor for the real-time mu rhythms detection has been developed in our study. Analog LEEG signals with high signal to noise ratio obtained directly by using the active sensor can reduce the duration and quantum error of digital signal processing and computation for the quick and precise control of brain-computer interface (BCI) systems...
The recording of EEG signals during fMRI scanning is now technically feasible and safe. However, artifacts relating to pulsatile blood flow (the ballistocardiogram) may still be prominently present in EEG data recorded in the MRI magnet. The application of independent component analysis (ICA) in order to reduce these artifacts off-line was investigated in three different types of EEG, one normal visually...
Neocortical ECoG studies have unveiled the presence of active states spatial patterns of amplitude modulation- in the beta-gamma ranges in the presence of conditioned stimuli that resemble cinematographic frames. These sequences of active frames emerge with abrupt phase resettings, followed by resynchronization and stabilization over channels, and magnified intensity. An online pattern recognizer...
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