A Parametric Approach to Measuring Cerebral Blood Flow Autoregulation from Spontaneous Variations in Blood Pressure

Autoregulation maintains cerebral blood flow (CBF) almost constant in the face of changes in arterial blood pressure (ABP). Tests for impairment of this process using only spontaneous fluctuations in ABP, without provoking large variations, are of great clinical interest, and a range of different approaches have previously been applied. Extending earlier work based on linear filters, we propose a simple parametric method using a first order finite impulse response filter. We evaluate the method on ABP and CBF velocity [(CBFV), from trancranial Doppler ultrasound] signals collected in 60 patients with stenosis or occlusion of the carotid arteries. Data were collected during the inspiration of ambient air, a 5% CO2/air mixture, and finally the return to ambient air. Equivalent data were collected in 15 normal subjects. The filters estimated from the data segments with constant inspiratory pCO2 showed the expected high-pass characteristic, which was reduced during hypercapnia and also in patients. Highly significant correlation between the filter parameters and cerebrovascular reactivity (percent increase in CBFV per unit change in end-tidal pCO2) gives further evidence that the filters reflect autoregulation. The method allows simple parametrization of the dynamic autoregulatory responses in CBFV, and the analysis of short (1 min) data segments. © 2001 Biomedical Engineering Society. PAC01: 8719Uv, 4762+q, 4380Qf     

Brain mapping analysis in patients with hepatic encephalopathy

Summary Topographical analysis of cerebral electrical activity was performed in 44 patients with hepatic encephalopathy. These patients were classified in 5 groups according to clinical criteria. Eight healthy subjects were used as a control group. All were studied in an awake, eyes closed, condition and some [Control Group (CG), Group 0 (G0), Group 1 (G1) and Group 2 (G2)] also in an awake, eyes open, condition. The awake, eyes closed, maps showed marked differences in the power spectral density (PSD) of the different bands, when comparing normal subjects with patients with several degrees of hepatic encephalopathy. These differences were related to the degree of clinical involvement, mainly in the alpha and delta PSD bands. The combination of a decreased alpha PSD, increased delta PSD, and decreased mean dominant frequency (MDF) allowed a clear discrimination between the different clinical groups. The differences observed between awake, eyes closed, and awake, eyes open, conditions were especially helpful to discriminate between CG subjects and G0, G1 and G2 patients.     

Effect of isometric and isokinetic muscle training on static strength and dynamic power

Summary This study investigated whether isokinetic strength training might induce changes in static and dynamic power already achieved as a result of isometric strength training. The subjects were twelve males. The isometric strength and dynamic power of elbow flexors were tested by means of an electric dynamometer and fly-wheel every two weeks. During the first 8 weeks all subjects trained the elbow flexors isometrically at four different positions of elbow joints. This training produced 27–36% gains in isometric strength and 34–46% in power. Thereafter the subjects were divided into two groups: the FG group who trained isokinetically at a fast velocity of 157·s^–1, and the SG group at slow velocity of 73·s^–1. After 6 weeks of training, the FG group produced a significant gain in power with light equivalent masses and the SG group did so with heavy equivalent masses. Neither group showed change in isometric strength.     

Detection of ophthalmic arterial doppler signals with Behcet disease using multilayer perceptron neural network

Doppler ultrasound is known as a reliable technique, which demonstrates the flow characteristics and resistance of ophthalmic arteries. In this study, ophthalmic arterial Doppler signals were obtained from 106 subjects, 54 of whom suffered from ocular Behcet disease while the rest were healthy subjects. Multilayer perceptron neural network (MLPNN) employing delta-bar-delta training algorithm was used to detect the presence of ocular Behcet disease. Spectral analysis of the ophthalmic arterial Doppler signals was performed by least squares (LS) autoregressive (AR) method for determining the MLPNN inputs. The MLPNN was trained with training set, cross validated with cross validation set and tested with testing set. All these data sets were obtained from ophthalmic arteries of healthy subjects and subjects suffering from ocular Behcet disease. Performance indicators and statistical measures were used for evaluating the MLPNN. The correct classification rate was 96.43% for healthy subjects and 93.75% for unhealthy subjects suffering from ocular Behcet disease. The classification results showed that the MLPNN employing delta-bar-delta training algorithm was effective to detect the ophthalmic arterial Doppler signals with Behcet disease.     

Aneurysm detection using one-bit correlation

Intercranial aneurysm present an especially serious clinical problem, since their rupture generally results in death or permanent brain damage. Recent work, conducted by the authors, indicated that this anomaly can be detected using spectral signature analysis. A low-cost turnkey noninvasive aneurysm-detection system is being tested for this purpose. Using polarity-coincident noise-added one-bit correlators, aneurysms have been successfully detected.     

Improvement in Doppler ultrasound human foetal heart rate records by signal correlation

An improved method for the determination of foetal heart rate from Doppler ultrasound signals is described and evaluated. It determines the most probable pulse interval from the recurrence times of multiple echoes generated by each cardiac pulse. The method, when optimised, is shown to offer an improvement over current systems, especially in reduced signal loss.     

Shear Rate Dependence of Ultrasound Backscattering from Blood Samples Characterized by Different Levels of Erythrocyte Aggregation

The objectives were (1) to determine the effect of the erythrocyte aggregation level (wide range of aggregation) and shear rate (which also affects aggregation) on the ultrasound backscattered power, and (2) to evaluate the reproducibility of the ultrasound method. Experiments were performed under steady flow (100–1250 ml/min) in a 12.7 mm diameter vertical tube. Doppler ultrasound at 10 MHz was used to measure simultaneously the velocity and the backscattered power across the tube. For each radial position, the shear rate was computed from the derivative of the velocity profile. The backscattered power decayed exponentially as a function of the shear rate, and for a given shear rate, the power increased monotonically with the level of aggregation measured by laser reflectometry. Using blood samples simulating hypo-, normal, and hyperaggregating erythrocytes, the power of the ultrasound signal varied respectively by –7.8, –13.2, and –16.1 dB as a function of the shear rate (from 0.4 to 50 s^–1). The reproducibility of the backscattered power was 5.5 dB, which is less than the variations observed as a function of the shear rate. In conclusion, ultrasound backscattering is sensitive to the level of erythrocyte aggregation. At a first glance, ultrasound seems less accurate when compared to laser reflectometry but it is suggested that this is because ultrasound backscattering may be sensitive to structural aggregate changes that are not detected by the laser method. © 2000 Biomedical Engineering Society. PAC00: 8718-h, 8719Tt, 8750Kk     

Fetal heart rate and umbilico-placental Doppler flow velocity waveforms in early pregnancies with a chromosomal abnormality and/or an increased nuchal translucency thickness

Fetal heart rate, umbilical artery pulsatility index, end-diastolicflow,nuchal translucency thickness and placental thickness were recordedin 250 women with a viable singleton pregnancy undergoing chorionicvillous sampling for fetal karyotyping at 11–14 weeksof gestation. The fetal karyotype was normal in 210 cases andabnormal in 40, including 21 with trisomy 21, 13 with trisomy18, three with triploidy, two with monosomy X and one with trisomy13. A total of 52 fetuses with a normal karyotype had a nuchaltranslucency 3 mm and were considered separately. There wasa stable and significant increase in the mean fetal heart ratein trisomy 21 pregnancies compared to controls. No significantdifference was found for the other variables between the groups.In chromosomally normal fetuses with an increased nuchal thickness,the development of fetal heart rate and compliance of the umbilico-placentalcirculation were within the normal ranges. Some fetuses withtrisomy 18 or triploidy had an increased resistance to bloodflow in the umbilical artery, which was probably due to abnormalplacental development.     

Detection and deletion of motion artifacts in electrogastrogram using feature analysis and neural networks

Electrogastrogram is a surface measurement of gastric myoelectrical activity, and electrogastrography has been an attractive method for physiological and pathophysiological studies of the stomach due to its nonivasive nature. Motion artifacts, however, ruin the electrogastrogram (EGG), and make the analysis very difficult and sometimes even impossible. They must be eliminated from EGG signals before analysis. Up to now, this can only be done by visual inspection, which is not only time-consuming but also subjective. In this study, a method using feature analysis and neural networks has been developed to realize automatic detection and elimination of the motion artifacts in EGG recordings by computer. Experiments were conducted to investigate the characteristics of different motion artifacts. Useful features were extracted, and different combinations of the features used as the input of the neural network were compared to obtain the optimal performance for the detection of motion artifacts using the artificial neural network.