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Biomedical subjects

M Akay

Publications and source records attributed to M Akay.

At least 19 recordsLinked to original sources

Investigating the effect of maternal alcohol intake on human fetal breathing rate using adaptive time-frequency analysis methods.

In this study, the matching pursuit (MP) method which is a modified version of the wavelet transform (WT) method was proposed to examine the effects of alcohol on human fetal breathing rates in both time and frequency domains. The matching pursuit method was chosen since the classical Fourier transform may not represent signals which have stationary characteristics and wavelet transform may not represent signals whose Fourier transforms have a narrow frequency support. Our results show that the horizontal structured atoms representing the sinusoidal activity at all frequency ranges disappeared and the vertical structured atoms representing the discontinuous spike type activity increased. In addition, the circular structured atoms at the high frequency range shifted to the low frequencies after the alcohol intake. The results also suggested that the matching pursuit is most suitable for analyzing the fetal breathing rate signals with and without alcohol intake.

Algorithms

Numerical and experimental stress analysis of a polymeric composite hip joint prosthesis.

A comparative stress analysis of a polymeric composite hip joint replacement was performed. A prototype short carbon-fiber reinforced PEEK (CF/PEEK) prosthesis was manufactured by injection molding. Finite element (FE) analysis was conducted on intact femurs and femurs fitted with the CF/ PEEK and the titanium prostheses under various loading conditions. FE models were validated by experimental strain gauge measurements by using synthetic femurs. There was a good agreement between the two methods except in the hoop strain of the femur in the calcar region because of the assumption of the isotropic material properties. The stem stresses were lower for the CF/PEEK prosthesis than for the titanium prosthesis. The maximum stress was in the spigot of the CF/PEEK prosthesis, but in the middle third of the stem of the titanium prosthesis. Stress generated in the cement was almost equal for both prostheses although more load was transferred, via cement, to the femur with the CF/ PEEK prosthesis because the load transfer took place over a larger area. An out-of-plane component of the joint load causes higher prosthesis and cement stresses.

Benzophenones

The effects of morphine on the relationship between fetal EEG, breathing and blood pressure signals using fast wavelet transform.

In this study, we introduce the fast wavelet transform (WT) as a method for investigating the effects of morphine on the electroencephalogram (EEG), respiratory activity and blood pressure in fetal lambs. Morphine was infused intravenously at 25 mg/h. The EEG, respiratory activity and blood pressure signals were analyzed using WT. We performed wavelet decomposition for five sets of parameters D2j where -1 < j < -5. The five series WTs represent the detail signal bandwidths: 1, 16-32 Hz; 2, 8-16 Hz; 3, 4-8 Hz; 4, 2-4 Hz; 5, 1-2 Hz. Before injection of the high-dose morphine, power in the EEG was high in all six frequency bandwidths. The respiratory and blood pressure signals showed common frequency components with respect to time and were coincident with the low-voltage fast activity (LVFA) EEG signal. Respiratory activity was observed during only 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 bands. 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. There was a strong relationship between fetal EEG, blood pressure and breathing movements. However, the injection of high-dose morphine resulted in a disruption of the normal cyclic pattern between the two EEG states and a significant increase in power in the first wavelet band. In addition, the high-dose drug resulted in a significant increase in the power of respiratory signal in the fourth and fifth wavelet bands, while power was reduced in the third wavelet band. Breathing activity was also continuous after the drug. The high-dose morphine also caused a temporary power shift from the third wavelet band to the fourth wavelet band for the 30-min period after injection of drug. Finally, high-dose morphine completely destroyed the correlation between EEG, breathing and blood pressure signals.

Animals

Evaluation of the tracking potential of a noninvasive estimator of cardiac output.

A robust, automatic measurement system for calculating cardiac output noninvasively has recently been developed. The proposed method relies on fast Fourier transform (FFT) analysis of pulses measured externally at the carotid and femoral pressure points. A transfer function of the aorta is computed from these (calibrated) pressure measurements, and a tapered model of the aorta is parametrically adapted so that its transfer function matches that derived experimentally. Incorporated in the system are a custom routine for digitally filtering pressure data and a simplex optimization algorithm for identification of aortic parameters essential to the calculation of impedance and aortic flow. Once flow has been reconstructed in the time domain it is averaged to a stroke volume and multiplied by the heart rate to yield cardiac output. Flow measurements are computed over several pulses and compared against the standard, invasive procedure of thermodilution. Preliminary results for a dynamic investigation of the method indicate a strong potential for tracking changes in cardiac output over time, thus advocating its use in monitoring hemodynamically unstable patients.

Algorithms

Autoregressive spectral analysis of phrenic neurogram during eupnea and gasping.

During hypoxic gasping, the phrenic neurogram (PN) has a steeper rate of rise, an augmented amplitude, and a shorter duration than is seen during eupnea. Because hypoxia reduces neuronal activity, we hypothesized that gasping would be characterized in the frequency domain by enhanced low-frequency power compared with eupnea. Autoregressive (AR) spectral analysis of the PN in chloralose-anesthetized, vagotomized, peripherally chemodenervated cats was performed during eupnea and hypoxic gasping. During eupnea, significant spectral peaks were seen at 41 +/- 2 and 93 +/- 2 (SE) Hz. In all cats, the 41-Hz spectral peak disappeared during hypoxic gasping and was replaced by a high-power, low-frequency peak at 26 +/- 1 Hz. No consistent change in the frequency or power of the high-frequency spectral peak was seen during gasping. To determine whether changes in the AR spectrum of the PN during gasping result from augmented respiratory output, we compared the AR spectra of the PN during gasping, hypercapnia (end-tidal CO2 fraction = 0.09), and carotid sinus nerve stimulation. Unlike during gasping, there was no shift in power toward lower frequencies during hypercapnia and carotid sinus nerve stimulation. We conclude that the spectral characteristics of gasping, loss of the medium-frequency peak and the appearance of low-frequency (< 30-Hz) power, are unique to this respiratory pattern.

Animals

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

Prediction of the location and time of spontaneous termination of reentrant ventricular tachycardia for radiofrequency catheter ablation therapy.

Ventricular tachycardia caused by reentrant excitation can lead to cardiac arrest and sudden death. Drug treatment and surgical procedures have been used with limited effectiveness. Catheter ablation methods are more promising because they are less invasive than surgery. Although ablation has come to be highly effective in the treatment of supraventricular tachycardias, the overall success rate remains low for ventricular tachycardias, which may be due in part to an inaccurate localization of the reentrant pathway. The authors hypothesize that a site in the myocardium exists that is critical for the maintenance or reentry and that when ablated, will result in permanent cessation of the tachycardia. The authors also hypothesize that this is the same site where the reentrant impulse blocks during spontaneous termination of tachycardia. A series of experiments has been designed to determine if there are specific properties of extracellular electrograms recorded from reentrant circuits that would enable the circuits to be identified without activation maps and, more specifically, allow the site of block causing spontaneous termination to be localized. For quantitative analysis of electrograms, a paradigm is developed to characterize electrogram morphology using a canine infarct model. Changes in morphology (shape, size, and location of signal deflections) can be considered (1) motions of a coordinate system and/or (2) conformational changes of shape. To a first approximation, stationarity over short time segments is assumed so that the motions and conformations can be parameterized. These parameters were extracted for 50 cardiac cycles during an episode of nonsustained ventricular tachycardia, in which 196-bipolar electrode pairs were positioned in an array format across the epicardial surface of the heart. The results of these studies of changes in electrogram morphology suggest that during cycles 5 to 49 of ventricular tachycardia, in many electrograms near the circuit, the cycle length increases linearly, the amplitude increases, and the duration of activation decreases. During cycles 50 to 54, the cycle length increases much more markedly, the amplitude decreases, and the duration of activation increases. These observations suggest that cycle lengthening may be an important property of some spontaneous terminations, and moreover that other morphologic characteristics are affected differently at different stages of cycle lengthening. Further, all motion parameters tended to oscillate from cycle to cycle in either an alternans pattern or longer oscillation. The variations in morphology were typically only a few percent from cycle to cycle. Such variability would not be evident using only ruler-and-caliper measurements made by hand because of the lack of precision and the sheer volume of data. It is expected that this approach for characterization of electrogram morphology will be extremely useful clinically to (1) increase speed and accuracy of ablation site selection and (2) reduce multichannel electrogram recording complexity during ablation site selection.

Algorithms

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

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

Pattern recognition and interpretation of electromyogram data from cat jaw muscle.

This study investigates the effect of emotional behavior on the masseteric muscle EMG response patterns. Two experimental protocols are utilized: (1) does not elicit emotional behavior (stick chewing) and (2) elicits emotional behavior (hypothalamic stimulation). The Karhunen-Loève transform is used to compute features which exactly represent the correlated patterns of mean-zero observations, with data compression and noise immunity. Using nonparametric tests, it is found that the populations of biting and hissing features are significantly different (p < 0.05), with increased statistical significance as the size of the training set is increased. No statistically significant difference is seen in a test of the two biting populations.

Animals

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

Application of adaptive FTF/FAEST zero tracking filters to noninvasive characterization of the sound pattern caused by coronary artery stenosis before and after angioplasty.

This article presents a new signal processing application that can be used for acoustical detection of coronary artery disease before and after angioplasty. The adaptive Autoregressive (AR) method based on the FTF/FAEST (Fast transversal filters/Fast a posteriori error sequential techniques) is used to track acoustical behavior associated with coronary occlusions. Using the amplitude trajectory of the second pole pair of this method, 9 out of 10 angioplasty patients were correctly identified using a blind protocol without prior knowledge of whether a given recording was made before and after angioplasty. These results were obtained from signals located between 200 and 300 msec after the end of the second heart sound during the diastolic period.

Algorithms

Acoustical detection of coronary occlusions using neural networks.

A nonlinear neural network classifier was applied to noninvasive acoustic detection of coronary artery disease; the classifier included a feature vector, derived from diastolic heart sounds, and a multi-layered network trained by the backpropagation. The feature vector is based on the linear prediction coefficients of the autoregressive method after an adaptive line enhancement method was used as the input pattern to the neural network. One hundred and twelve recordings (70 abnormal, 42 normal) were studied and the network was trained on a randomly chosen set of six abnormal and six normal patients. It was tested on a database consisting of 100 recordings to which it had not been exposed. The network correctly identified 50 of the 64 patients with coronary artery disease and 32 of the 36 patients without any coronary artery occlusions. These results showed that this neural network is capable of distinguishing normal patients from abnormal patients. In addition, the diagnostic capability of this approach is much better than any other available noninvasive approach.

Coronary Disease

Noninvasive acoustical detection of coronary artery disease: a comparative study of signal processing methods.

Previous studies have indicated heart sounds may contain information useful in the detection of occluded coronary arteries. During diastole, coronary blood flow is maximum, and the sounds associated with turbulent blood flow through partially occluded coronary arteries should be detectable. In order to detect such sounds, recordings of diastolic heart sound segments were analyzed by using four signal processing techniques; the Fast Fourier Transform (FFT), the Autoregressive (AR), the Autoregressive Moving Average (ARMA), and the Minimum-Norm (Eigen-vector) methods. To further enhance the diastolic heart sounds and reduce background noise, an Adaptive filter was used as a preprocessor. The power ratios of the FFT method and the poles of the AR, ARMA, and Eigen-vector methods were used to diagnose patients as diseased or normal arteries using a blind protocol without prior knowledge of the actual disease states of the patients to guard against human bias. Results showed that normal and abnormal records were correctly distinguished in 56 of 80 cases using the Fast Fourier Transform (FFT), in 63 of 80 cases using the AR, in 62 of 80 cases using the ARMA method, and in 67 of 80 cases using the Eigenvector method. Among all four methods, the Eigenvector methods showed the best diagnostic performance when compared with the FFT, AR, and ARMA methods. These results confirm that high frequency acoustic energy between 300 and 800 Hz is associated with coronary stenosis.

Coronary Disease

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

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

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