Biomedical subjects

Sadik Kara

Publications and source records attributed to Sadik Kara.

16 recordsLinked to original sources

PubMed2006

Classification of macular and optic nerve disease by principal component analysis.

In this study, pattern electroretinography (PERG) signals were obtained by electrophysiological testing devices from 70 subjects. The group consisted of optic nerve and macular diseases subjects. Characterization and interpretation of the physiological PERG signal was done by principal component analysis (PCA). While the first principal component of data matrix acquired from optic nerve patients represents 67.24% of total variance, the first principal component of the macular patients data matrix represents 76.81% of total variance. The basic differences between the two patient groups were obtained with first principal component, obviously. In addition, the graphic of second principal component vs. first principal component of optic nerve and macular subjects was analyzed. The two patient groups were separated clearly from each other without any hesitation. This research developed an auxiliary system for the interpretation of the PERG signals. The stated results show that the use of PCA of physiological waveforms is presented as a powerful method likely to be incorporated in future medical signal processing.

Adult↗

PubMed2006

Low-cost compact ECG with graphic LCD and phonocardiogram system design.

Till today, many different ECG devices are made in developing countries. In this study, low cost, small size, portable LCD screen ECG device, and phonocardiograph were designed. With designed system, heart sounds that take synchronously with ECG signal are heard as sensitive. Improved system consist three units; Unit 1, ECG circuit, filter and amplifier structure. Unit 2, heart sound acquisition circuit. Unit 3, microcontroller, graphic LCD and ECG signal sending unit to computer. Our system can be used easily in different departments of the hospital, health institution and clinics, village clinic and also in houses because of its small size structure and other benefits. In this way, it is possible that to see ECG signal and hear heart sounds as synchronously and sensitively. In conclusion, heart sounds are heard on the part of both doctor and patient because sounds are given to environment with a tiny speaker. Thus, the patient knows and hears heart sounds him/herself and is acquainted by doctor about healthy condition.

Electrocardiography↗

PubMed2006

Detection of gastric dysrhythmia using WT and ANN in diabetic gastroparesis patients.

Gastric myoelectrical activity can be measured by a noninvasive technique called electrogastrography where surface electrodes are placed on the epigastric area of the abdomen. The electrogastrogram (EGG) signal is by nature a nonstationary signal in terms of its frequency, amplitude and wave shape. Unlike the other methods discrete wavelet analysis (DWT) was designed for nonstationary signals. For automatic assessment of EGG, we used artificial neural networks (ANNs) that have been widely employed in pattern recognition due to their great potential of high performance, flexibility, robust fault tolerance, cost-effective functionality and capability for real-time applications. So we developed a new method for classification of EGG based on DWT and ANN.

Adolescent↗

PubMed2006

Utilization of artificial neural networks in the diagnosis of optic nerve diseases.

This research is concentrated on the diagnosis of optic nerve disease through the analysis of pattern electroretinography (PERG) signals with the help of artificial neural network (ANN). Multilayer feed forward ANN trained with a Levenberg Marquart (LM) backpropagation algorithm was implemented. The designed classification structure has about 96.4% sensitivity, 90.4% specifity and positive prediction is calculated to be 94.2%. The end results are classified as healthy and diseased. Testing results were found to be compliant with the expected results that are derived from the physician's direct diagnosis. The end benefit would be to assist the physician to make the final decision without hesitation.

Adult↗

PubMed2006

Utilization of artificial neural networks and autoregressive modeling in diagnosing mitral valve stenosis.

This research is concentrated on the diagnosis of mitral heart valve stenosis through the analysis of Doppler Signals' AR power spectral density graphic with the help of ANN. Multilayer feedforward ANN trained with a Levenberg Marquart backpropagation algorithm was implemented in the MATLAB environment. Correct classification of 94% was achieved, whereas 4 false classifications have been observed for the test group of 68 subjects in total. The designed classification structure has about 97.3% sensitivity, 90.3% specifity and positive prediction is calculated to be 92.3%. The stated results show that the proposed method can make an effective interpretation.

Adult↗

PubMed2006

Comparison of fast Fourier transformation and autoregressive modelling as a diagnostic tool in analysis of lower extremity venous signals.

In this study, we have compared the efficacy of autoregressive modelling (ARM) and fast Fourier transformation (FFT) of Doppler signals from lower extremity veins of healthy volunteers in various physiologic situations. Compared to FFT, ARM produced smooth spectra and less spectral broadening both in sonograms and power spectra. However, faulty positioning of the peaks along the time axis in FFT-derived power spectral density curves show that FFT is not a suitable method if these graphs are to be used as a diagnostic tool. Analysis of ARM-based venous sonograms and power spectral density graphs revealed that FFT should not be used in signals with high power spectral density levels and low-frequency bandwidth within limited segments of time.

Adult↗

PubMed2006

Discontinuous doppler signals simulating respiratory misregistration: effect on autoregressive frequency spectra.

In this study, we have produced discontinuous Doppler signals of carotid artery and internal jugular vein, simulating respiratory misregistration. The aim of the study is to observe the effect of signal discontinuity and its duration on power spectral density vs. frequency graphs obtained by Autoregressive Modeling. The signals were recorded from ten male volunteers. Signal interruption was performed by moving the sampling volume in and out of the vessel bidirectionally. To estimate the effect of on-line recording time and signal discontinuity on frequency spectra, we have worked on a control data of 30s with continuous signal, and three sets of data with artificially interrupted signals of 30, 60 and 90s duration. Maximum power spectral density, area under the power spectral density, and frequency level corresponding to maximum power spectral density were calculated on frequency spectra. The frequency level corresponding to maximum power spectral density provides the most statistically stable finding in our preliminary data. The signal duration of the signal had no significant effect on the statistical stability of the frequency level.

Adult↗

PubMed2006

Detection of atherosclerosis using autoregressive modelling and principles component analysis to carotid artery Doppler signals.

The purpose of this study was to evaluate principal component analysis method to power spectral density acquired with autoregressive modeling (AR) of carotid artery Doppler signals. Carotid artery Doppler signals from patient with atherosclerosis and healthy subjects were recorded. Afterwards, power spectral densities of these signals were obtained using AR method. The basic differences between the healthy and patients were obtained with 1st principal component obviously. These results could be extrapolated to situations involving noninvasive measurement where PCA can be extremely time saving. As a result the patient and healthy groups are separated clearly from each other via an arbitrary power function y=ax with perfect accuracy resulting in a precision sensitivity and specificity of 100 percent and the use of PCA of physiological waveform is presented as a powerful method likely to be incorporated in future medical signal processing.

Adult↗

PubMed2005

Classification of carotid artery Doppler signals in the early phase of atherosclerosis using complex-valued artificial neural network.

In this study, carotid arterial Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group had an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal angiographies. Results were classified using complex-valued artificial neural network (CVANN). Principal component analysis (PCA) and fuzzy c-means clustering (FCM) algorithm were used to make a CVANN system more effective. For this aim, before classifying with CVANN, PCA method was used for feature extraction in PCA-CVANN architecture and FCM algorithm was used for data set reduction in FCM-CVANN architecture. Training and test data were selected randomly using 10-fold cross validation. PCA-CVANN and FCM-CVANN architectures classified healthy and unhealthy subjects for training and test data with about 100% correct classification rate. These results shown that PCA-CVANN and FCM-CVANN classified Doppler signals successfully.

Adult↗

PubMed2005

Training a learning vector quantization network using the pattern electroretinography signals.

In this study, the pattern electroretinography (PERG) signals derived from evoked potential across retinal cells of subjects after visual stimulation were analyzed using artificial neural network (ANN) with 172 healthy and 148 diseased subjects. ANN was employed to PERG signals to distinguish between healthy eye and diseased eye. Supervised network examined was a competitive learning vector quantization network. The designed classification structure has about 94% sensitivity, 90.32% specifity, 5.94% false negative, 9.67% false positive and correct classification is calculated to be 92%. Testing results were found to be compliant with the expected results that are derived from the physician's direct diagnosis. The end benefit would be to assist the physician to make the final decision without hesitation.

Adult↗

PubMed2005

Estimation of wavelet and short-time Fourier transform sonograms of normal and diabetic subjects' electrogastrogram.

Electrogastrography (EGG) is a noninvasive way to record gastric electrical activity of stomach muscle by placing electrodes on the abdominal skin. Our goal was to investigate the frequency of abnormalities of the EGG in real clinical diabetic gastroparesis patients using WT method and to compare performance of STFT and WT methods in the case of time-frequency resolution. The results showed that WT sonograms can be used to classify patients successfully as healthy or sick. And also, due to the fact that the WT method does not suffer from some intrinsic problems that affect the STFT method, one can see that the WT method can help improve the quality of the sonogram of the EGG signals.

Adolescent↗

PubMed2005

Imaging system for visualization and numerical analysis of cancer at stomach and skin tissues.

Digital imaging of cancerous cells is instrumental not only in determining the characteristic of the cancer but also monitoring the progress of the disease in the follow up of the patient and adapting the treatment, accordingly. Therefore, we have developed an imaging system to display and layout the characteristics of normal and cancerous cells in an automated way. Image processing techniques are performed on the digitized images of stomach and skin tissues, in order to derive the number of cells, area of an individual cell, and average area of the cells in a certain size of an image window.

Analog-Digital Conversion↗

PubMed2005

Comparison of the autoregressive modeling and fast Fourier transformation in demonstrating Doppler spectral waveform changes in the early phase of atherosclerosis.

In this study, we have performed fast Fourier transformation (FFT) and autoregressive (AR) signal processing of the Doppler signals at a nonstenotic arterial site in patients with atherosclerosis and healthy volunteers. We have not only utilized Doppler sonograms, but also facilitated the power spectral density distribution graphs using AR modeling and FFT. Our preliminary analysis show that AR modeling has a higher efficacy in demonstrating Doppler spectral waveform changes in the preclinic or silent phase of atherosclerosis. AR has especially revealed an outstanding difference in the calculation for frequency level of maximum power spectral density.

Adult↗

PubMed2004

Investigation of a new heart contractility power parameter.

First derivative of arterial blood pressure, dp/dt is known to reflect the contractility power of the heart. We hypothesize that the calculated area under each cardiac cycle of the blood pressure curve is also another practical tool in revealing the heart contractility power. Of the 84 subjects, 61 patients were found to have adequate contractility power (high dp/dt) and their mean area calculation resulted in 64.2 mmHg s with a standard deviation of 2.9 mmHg s. The remaining 23 patients have indicated poor heart contractility power (low dp/dt) and stayed in serious condition for long time. This group had mean area of 41.4 +/- 3.1 mmHg s. Patients with poor contractility power had areas below 45 mmHg s, while all area calculations for patients with high contractility power stayed over 60 mmHg s. Therefore, small area of the arterial blood pressure curves seems to be a good indicator of a poor heart contractility power and the area calculation may be an adjunct parameter to the dp/dt that has been employed for the assessment of heart contractility.

Action Potentials↗

PubMed2003

Low-cost instrumentation for the diagnosis of Hirschsprung's disease.

In Hirschsprung's disease, the internal anorectal sphincter fails to relax in response to rectal distension, which strongly indicates the absence of rectoanal inhibitory reflex (RAIR). Hirschsprung's disease is a very common case particularly encountered in the newborns in our region. Development of a manometric system targeted specifically for the diagnosis of this disease at a reasonable cost is an urgent need identified by our regional colorectal surgeons. These surgeons indicated that commercially available anorectal manometers are too expensive to acquire. Therefore, in our research we tried to develop a low-cost single balloon-transducer system, which only provides information about RAIR, and hence diagnoses the Hirschsprung's disease. The hardware part of our instrumentation is made of a latex balloon, pressure transducer, amplifier, and A/D converter circuits, which all collects the pressure readings and sends the data to the computer. The manometer system software, programmed based on Delphi, displays these readings and patient information on a computer screen. This designed system was successful enough to perform manometric recording of RAIR in the anorectal ampulla of rabbits and rats.

Anal Canal↗

PubMed2003

Sphincter muscle stimulator to be used before treating anal atresia.

Closed rectum is a very frequently encountered anomaly of the newborns in our university hospital. Before making a rectal opening, the anorectal sphincter muscle needs to be stimulated to prevent any damage to the muscle itself In this study, we have designed a stimulator that provides reasonably constant output current depending on the physiological impedance of the rectal area. The current amplitude can be set between 20 and 250 mA. Stimulation pulses are adjusted for duration of 230 micros and can be obtained at a repetition period between 1.75 and 20 ms. Fifteen patients in the Pediatric Surgery Department of Erciyes University Hospital were subjected to our stimulation tests. On average, about 140 mA was enough to stimulate the muscle when probes were applied over the skin. On the other hand, with the placement of probes beneath the skin, stimulation was obtained for pulse amplitude of 40 mA.

Anal Canal↗