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M Akay

Publications and source records attributed to M Akay.

18 recordsLinked to original sources
PubMed1995

Investigating the effects of opioid drugs on electrocortical activity using wavelet transform.

Fetal electrocortical activity (ECoG) is characterized by two distinct patterns: HVSA (high voltage, slow activity) and LVFA (low voltage, fast activity). Using the wavelet transform (WT), we recently reported that the frequency characteristics of these two ECoG patterns undergo significant maturational changes prior to birth (Akay et al. 1994a). We now report that fetal ECoG can also be significantly affected by pharmacological agents. In this paper, we compared the effects of two opioid drugs (morphine and [D-Pen2, D-Pen5]-enkephalin, DPDPE) on fetal ECoG, using the chronically instrumented fetal lamb model. Morphine was infused intravenously (i.v.) at 2.5 mg/h, while DPDPE was infused into the lateral cerebroventricle (i.c.v.) at 30 micrograms/h. The ECoG was analyzed using WT. We performed multi-resolution decomposition for four sets of parameters D2j where -1 < j < -4. The four series WTs represent the detail signal bandwidths: (1) 16-32 Hz, (2) 8-16 Hz, (3) 4-8 Hz, (4) 2-4 Hz. The data were subjected to statistical analysis using the Kolmogorov-Smirnov (KS) test. Both morphine and DPDPE resulted in a significant increase in power in the first wavelet band, while power was reduced in the second, third and fourth wavelet bands. In addition, both drugs resulted in a disruption of the normal cyclic pattern between the two ECoG patterns. There was a difference in the time course of action between morphine and DPDPE. This is the first occasion in which continuous ECoG has been subjected to rigorous statistical analysis. The results suggest that the WT-KS method is most suitable for quantitating changes in the ECoG induced by pharmacological agents.

Animals↗
PubMed1995

An estimation of fatigue life for a carbon fibre/poly ether ether ketone hip joint prosthesis.

A fracture mechanics approach was applied to estimate the life of a prosthesis injection moulded from short carbon fibre reinforced poly ether ether ketone. Flexural modulus and strength, fracture toughness, fatigue endurance limit, fatigue crack growth rate and threshold stress intensity factor were determined. The dimensions of the test pieces were selected to yield fibre orientation and fibre length distributions similar to those obtained in the prosthesis. Stress levels generated in the prosthesis under different activities were estimated by conducting three-dimensional finite element analysis. It was shown by a fracture mechanics approach that a fatigue failure due to the propagation of an embedded elliptical slit, under these stresses, would be unlikely for a crack length smaller than 1.85 mm. However, the cement would fail under the same conditions, irrespective of the type of the prosthesis employed.

Benzophenones↗
PubMed1994

Time-frequency analysis of the electrocortical activity during maturation using wavelet transform.

In this study, we introduce the wavelet transform (WT) as a method for characterizing the maturational changes in electrocortical activity in 24 fetal lambs ranging from 110-144 days gestation (term 145 days). The WT, based on multiresolution signal decomposition, is free of assumptions regarding the characteristics of the signal. The approximation of the electrocortical activity at resolutions varying from 2j+1 to 2j can be extracted by decomposing the signal on a wavelet orthonormal basis of L2(R). We performed multiresolution decomposition for four sets of parameters D2j, where -1 < j < -4. The four series WT represent the detail signal band-widths: (1) 16-32 Hz, (2) 8-16 Hz, (3) 4-8 Hz, (4) 2-4 Hz. The data were divided into three groups according to gestational age: 110-122 days (early), 123-135 days (middle), and 136-144 days (late). In the early group, the power was highest in the fourth signal bandwidth, with relatively low power in the other bands. Increase in gestational age was characterized by increased power in all four bandwidths. Comparison of the cumulative distribution function of the power in the four wavelet bands confirmed the presence of two statistically different patterns in all three age groups. These two patterns correspond to the visually identified patterns of HVSA (high-voltage slow activity) and LVFA (low-voltage fast activity). The earliest development change occurred in HVSA, with progressive increase in power in the 2-8 Hz band. Later changes occurred in LVFA, with a significant increase in power in the 16-32 Hz band.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1994

Investigating the effects of vasodilator drugs on the turbulent sound caused by femoral artery stenosis using short-term Fourier and wavelet transform methods.

In this study, the effects of vasodilator drugs on the turbulent sound generation mechanisms during femoral artery stenoses were investigated using the wavelet analysis of the turbulent sounds to characterize these sounds before and after the injection of vasodilator drugs. Results showed that the injection of drugs drastically improved the diagnostic performance of the turbulent sounds in detecting stenoses by increasing the signal-to-noise ratio of the sounds. Results also suggested that the sound above 250 Hz was drastically increased in response to the injection of the vasodilator drug for the partially occluded cases. The turbulence sounds caused by partially occluded femoral arteries are directly related to the slope of baseline of blood flow and to the velocity of the flow. For the 0% occlusion case, initially, sounds were produced with the injection of drugs. However, the sounds totally disappeared when the slope of average blood flow was zero. These results show that the diagnostic performance of diastolic heart sounds associated with occluded arteries can be improved by using vasodilator drugs, which increase the acoustic energy in the first and second wavelet bandwidths due to the turbulence. The short-term Fourier transform (STFT) method was also applied to the same data base. Results using the STFT showed somewhat similar power distributions in that the acoustical power above 250 Hz was increased after the injection of drugs for the occluded cases. However, the WT method provided better time-frequency resolution than the STFT method, showing details of the change in the frequency characteristics with respect to time after the injection of drug.

Animals↗
PubMed1993

Mechanoelectrical feedback in cardiac myocytes from stretch-activated ion channels.

Stretch-activated ion channels (SAC's) in cardiac myocytes from neonatal rats were studied in cell-attached patches. Stretch of membrane patches by suction in the recording pipette caused the triggering of action potentials that were recorded as action currents (AC's). The significance of a temporal correlation between SAC open probability and AC's was tested using the Kolmogorov-Smirnov and Poisson distributions. It was shown that the 50-ms epoch immediately preceding the action current had unique kinetics and represented a peak in SAC open probability (p < 0.001). Thus it appears that current from a small number of SAC's injects sufficient charge (0.2 pC during 50 ms) to trigger action potentials in myocytes. These data strengthen the hypothesis that passive mechanical stretch of myocardium can be arrhythmogenic.

Action Potentials↗
PubMed1992

Noninvasive diagnosis of coronary artery disease using a neural network algorithm.

This study examines the utility of neural networks for detecting coronary artery disease noninvasively by using the clinical examination variables and extracting useful information from the diastolic heart sounds associated with coronary occlusions. It has been widely reported that coronary stenoses produce sounds due to the turbulent blood flow in these vessels. These complex and highly attenuated signals taken from recordings made in both soundproof and noisy rooms were detected and analyzed to provide feature set based on the poles and power spectral density function (PSD) of the Autoregressive (AR) method after Adaptive Line Enhancement (ALE) method. In addition, some physical examination variables such as sex, age, body weight, smoking condition, diastolic pressure, systolic pressure and derivation from them were included in the feature vector. This feature vector was used as the input pattern to the neural network. The analysis was studied on one hundred recordings (63 abnormal, 37 normals). The network correctly identified 84% of the subjects with coronary artery disease and 89% of the normal subjects.

Algorithms↗
PubMed1992

Noninvasive acoustical detection of coronary artery disease using the adaptive line enhancer method.

Previous studies have indicated that heart sounds may contain information which is useful in the detection of occluded coronary arteries. Specifically, previous work based on analysing heart sounds recorded during the diastolic portion of the cardiac cycle, when blood flow through the coronary arteries is maximum, has shown that additional frequency components are present in patients with coronary artery disease. To further explore the application of advanced signal processing techniques to the noninvasive detection of coronary artery disease, a new signal-processing approach is presented using adaptive line enhancing (ALE) and spectral estimation of diastolic heart sounds taken from recordings made at the patient's bedside. This approach comprises two cascaded processes. In the first the ALE method is used to enhance the diastolic heart sounds and eliminate background noise. In the second process, either autoregressive (AR) or autoregressive moving average (ARMA) spectral methods are used to estimate the model parameters. Model parameters (the power spectral density (PSD) functions and the poles of the AR or ARMA method) were used to diagnose patients as diseased or normal. Results showed that normal and abnormal recordings were correctly identified in 39 of 43 cases using the new method. These results also confirm that high-frequency energy above 400 Hz is associated with coronary stenosis.

Coronary Disease↗
PubMed1992

Heart rate variability as an index of autonomic imbalance in patients with recent myocardial infarction.

Autonomic nervous activities are estimated in three groups of patients: Group A consists of patients who had experienced myocardial infarction (MI) within 2-6 weeks before the tests; Group B consists of patients who had MI more than one year previously; Group C consists of matched controls, free of cardiac disease. Autonomic activity is estimated using postural effects on heart rate variability (HRV): a sympathetic activity index is defined as HRV power within a low frequency band (0.04-0.12 Hz) in the tilt position and a parasympathetic activity index is defined as HRV power in a high frequency band (0.18-0.28 Hz) in the supine position. Results show that, relative to controls, Group A patients have reduced parasympathetic activity index (5 + 3 against 13 + 8, normalised units; p < 0.05) and an increased ratio of sympathetic to parasympathetic activity (17 + 17 against 4 + 2; p < 0.05). Group B is not significantly different from Group A or C. The period of 2-6 weeks post-MI thus appears to be characterised by depressed parasympathetic nervous activity which can be measured using HRV analysis.

Aged↗
PubMed1992

Application of adaptive filters to noninvasive acoustical detection of coronary occlusions before and after angioplasty.

Previous studies have indicated that coronary stenoses produce sounds due to the turbulent blood flow in these vessels [1]-[10]. Measurement of these signals forms the basis of our noninvasive approach to the detection of coronary artery disease. It is during diastole that coronary blood flow is maximum and the sounds associated with turbulent blood flow through partially occluded coronary arteries would be loudest [1]-[10]. Isolated diastolic heart sounds taken from recordings made at the patient's bedside were modeled using the autoregressive (AR) and autoregressive moving average (ARMA) methods [4], [7] after adaptive line enhancement (ALE). Decisions were made in a blind fashion without prior knowledge of whether a given recording was made before or after angioplasty. Resulting model frequency spectra showed greater high-frequency components (between 400 and 800 Hz) in preangioplasty patients, and a consistent shift in amplitude of the second pole pairs of the AR and ARMA methods with surgery. Blind assessment, based on frequency spectra and poles, correctly classified the diastolic recordings in 18 of 20 cases. These results provide strong evidence supporting our hypothesis that coronary stenoses produce detectable sounds during diastole [1]-[10].

Angioplasty, Balloon, Coronary↗
PubMed1991

Application of the ARMA method to acoustic detection of coronary artery disease.

To further explore the application of advanced signal processing techniques to the noninvasive detection of coronary artery disease, 30 patients (10 angioplasty and 20 normal or abnormal) were tested using autoregressive moving average (ARMA) modelling of the diastolic heart sound data. It is during diastole that coronary blood flow is maximum and sounds associated with turbulent blood flow through partially occluded coronary arteries would be loudest. Model parameters (the power spectral density (PSD) functions and the poles of the ARMA method) were used to separate the normal patients from the abnormal patients in the normal/abnormal study, or to decide whether the recordings were made before or after angioplasty in the angioplasty study. The decisions were made 'blind', without knowledge of the actual disease states of the patients for the normal/abnormal study and without prior knowledge of whether a given recording was made before or after angioplasty for the angioplasty study. Results from the angioplasty and the normal/abnormal studies showed that pre- and post-angioplasty records were correctly distinguished in 8 out of 10 cases, and normal and abnormal records were correctly distinguished in 17 of 20 cases. These results also confirmed that high frequency energy above 400 Hz is probably associated with coronary stenosis.

Aged↗
PubMed1990

Detection of coronary occlusions using autoregressive modeling of diastolic heart sounds.

Previous studies have indicated that diastolic heart sounds may contain information useful in the detection of occluded coronary arteries. In this study, recordings of diastolic heart sound segments were modeled by autoregressive (AR) methods including the adaptive recursive least-square lattice (RLSL) and the gradient lattice predictor (GAL). Application of the Akaike criterion demonstrated that between 5 and 15 AR coefficients are required to completely describe a diastolic segment. The reflection coefficients, prediction coefficients, zeros of the polynomial of the inverse filter, and the AR spectrum were determined over a number (N = 20-30) of diastolic segments. Preliminary results indicate that the averaged AR spectrum and the zeros of the inverse filter polynomial can be used to distinguish between normal patients and those with coronary artery disease.

Algorithms↗
PubMed1990

Noninvasive detection of coronary stenoses before and after angioplasty using eigenvector methods.

Previous studies done by our group suggest that partially occluded coronary arteries may generate sounds due to turbulent blood flow. To support these previous findings the frequency spectra of diastolic heart sounds are compared before and after angioplastic surgery. Since the low-level sounds associated with partially occluded coronary arteries are contaminated with considerable background noise, traditional FFT analysis may not produce accurate frequency spectra. Indeed, in a previous study using the same data, no significant differences were found in the diastolic heart sounds before and after angioplastic surgery. In this study, three eigenvector methods (Pisarenko, MUSIC, and Minimum-Norm) have been selected to generate the frequency spectra because of their higher resolution, particularly in the presence of noise. Although the Pisarenko method produced spurious zeros and could not be used, the other two methods produced spectra showing, in most cases, a marked decrease in high-frequency spectral components following angioplasty.

Algorithms↗
PubMedDate not supplied

Localized spatial discrimination of epicardial conduction paths after linear transformation of variant information.

We present a method for the localized statistical discrimination of class populations based on the Karhunen-Loève and Fukunaga-Koontz transforms. These transforms provide features that model the variance of a sample distribution. The spatial series of a 196 channel epicardial electrogram recording from an arrythmogenic postinfarct canine were analyzed. For each type of rhythm studied, Karhunen-Loève and Fukunaga-Koontz expansions were computed from five training sets of spatial data, corresponding to five locations across the surface of the heart. Nonparametric statistical tests were then used for discriminant analysis to compare properties representative of the distribution from each proposed class. In a comparison of properties from sinus rhythm to those of two ventricular tachycardias, several spatial regions exhibited statistically significantly different propagation characteristics. These areas were observed by visual inspection of electrogram activation maps to be characterized by conductive gradients, which differed in magnitude and direction from one rhythm to another. The regions in which the propagation characteristics are of greatest difference in each tachycardia were centered upon sites of conduction block, manifested by reentrant circuit rhythms. Therefore, the importance of the technique for the localization of specific electrophysiologic events is demonstrated. This study extends previous work of our group on biosignal pattern recognition to encompass localized spatial data.

Analysis of Variance↗
PubMedDate not supplied

Dynamics of the sounds caused by partially occluded femoral arteries in dogs.

Previous studies have indicated that partially occluded arteries produce sounds due to turbulence. If these sounds from the coronary arteries could be detected externally, they would provide a simple approach to the detection of coronary artery disease. To confirm the hypothesis that coronary stenosis produces detectable acoustic correlates, sounds caused by a controlled occlusion of the femoral artery of dogs were detected and analyzed using both the fast Fourier transform (FFT) and the autoregressive (AR) methods. The femoral artery was chosen, since its size and flow approximate those of coronary arteries in humans. The poles of the AR spectra and the power ratios of different sections of the FFT and AR spectra were used to differentiate the degree of the stenosis. The results showed that high frequency acoustical power between 200 and 800 Hz is associated with the turbulence produced by the partially occluded femoral arteries of the dogs. Using the AR method, high acoustic power above 200 Hz increased when the degree of the occlusions increased. The poles and power ratios of the AR spectra differed according to the degree of stenosis. However, the high frequency acoustical power above 200 Hz did not increase above the 85% occlusion.

Animals↗
PubMedDate not supplied

Wavelets in biomedical engineering.

Wavelets analysis methods have been widely used in the signal processing of biomedical signals. These methods represent the temporal characteristics of a signal by its spectral components in the frequency domain. In this way, important features of the signal can be extracted in order to understand or model the physiological system. This paper reviews the widely used orthogonal wavelet transform method in the biomedical applications.

Algorithms↗
PubMedDate not supplied

Investigating the relationship between fetus EEG, respiratory, and blood pressure signals during maturation using wavelet transform.

In this study, we introduce the fast wavelet transform as a method for characterizing maturational changes in electrocortical activity, respiratory activity, and blood pressure in fetal lambs in early (110-122 days), mid (123-135 days), and late (136-144 days) third trimester (term 145 days). Each recording was 2 hr in duration. Wavelet decomposition was performed for six sets of parameters D2j where 1 < or = j < or = 6. The six series wavelet transforms represent the following signal frequency bands: 1. 16-32 Hz; 2. 8-16 Hz; 3. 4-8 Hz; 4. 2-4 Hz; 5. 1-2 Hz; 6. 0.5-1 Hz. In the early group, power in the electrocephalogram (EEG) was highest in the fourth wavelet band, with relatively low power in the other bands. Increase in gestational age was characterized by increased power in all four wavelet bands. Power in the first wavelet band was significantly increased during low-voltage fast activity (LVFA) in the late group. The respiratory and blood pressure signals showed common frequency components with respect to time and were coincident with the LVFA EEG signal. Respiratory activity was only observed during some of the LVFA periods and was completely absent during high-voltage slow activity (HVSA) EEG. The respiratory signal showed dominant power in the fourth wavelet band, and less power in the third and fifth band. The blood pressure signal was also characterized by dominant power in the fourth wavelet band. This power was significantly increased during periods of respiratory activity. These results suggest a strong relationship between fetal EEG, blood pressure, and breathing movements.

Animals↗