Electric organ discharge variability of Mormyridae (Teleostei: Osteoglossomorpha) in the Upper Volta system

The electric organ discharges (EODs) of five mormyrid species ( Marcusenius senegalensis , Brevimyrus niger , Petrocephalus bovei , Pollimyrus isidori , Hippopotamyrus pictus ) from different sampling sites from the Upper Volta system in West Africa were investigated. EOD waveforms were recorded at high sampling rates in order to compare signal waveform parameters of the different species from different locations. Except for H. pictus , EODs within a species differed significantly from one another in some parameters and waveform variability at least between some sampling sites. In addition, each species showed a continuous spectrum of waveform variations, all or only parts of which were found at certain localities. Although there was variability and sometimes similarities between species, the EOD waveforms were species specific. Knowing their variation spectrum, they can be used for species determination and are probably used for species recognition by the mormyrids. Similarities or differences in EOD waveform expression within a species were not related to geographical distance. By contrast, we suggest that biotic environmental factors at a given location influence the expression of EOD waveforms. These factors affect absolute measurements such as EOD duration and fast Fourier transformation peak frequency as well as the amount of variation for certain waveform parameters across species in a similar manner for a given site. Although EOD waveform might be important for the establishment of reproductive barriers between species, our results suggest that differences in waveforms may not necessarily reflect different species or speciation processes in progress.  © 2008 The Linnean Society of London, Biological Journal of the Linnean Society , 2008, 94 , 61–80.     

High-resolution alignment of action potential waveforms using cubic spline interpolation

A cubic spline interpolation technique is applied to the problem of aligning action potential waveforms. Interpolation is an attractive alternative to sampling at many times the Nyquist rate in order to reduce errors caused by asynchronous sampling of rapidly changing waveforms. Alignment is achieved by locating the peak of the interpolated waveform, which can be found by solving a quadratic equation. The waveform is then reconstructed for comparison with existing templates. The technique was tested using simulated noisy, randomly arriving waveforms, the interpolated signal and alignment time errors being computed as functions of the signal/noise ratio. The spline technique is superior in accuracy to sampling at eight-times the Nyquist rate and is comparable to a Fourier-transform-based interpolation algorithm. It is computationally efficient, requiring approximately five multiplications per sample point. The interpolation concept is extended to the principal component technique for separation of action potential waveforms. The energy function is interpolated and used to align the waveforms, after which the interpolated coefficients can be used for high speed classification. The technique shows an improvement in both alignment error and effective signal/noise ratio in comparison with sampling or interpolation to a voltage peak.     

Pulse charge and not waveform affects M-wave properties during progressive motor unit activation

The aim of this study was to investigate changes in experimentally recorded M-waves with progressive motor unit (MU) activation induced by transcutaneous electrical stimulation with different pulse waveforms. In 10 subjects, surface electromyographic signals were detected with a linear electrode array during electrically elicited contractions of the biceps brachii muscle. Three different monophasic waveforms of 304-μs duration were applied to the stimulation electrode on the main muscle motor point: triangular, square, and sinusoidal. For each waveform, increasing stimulation current intensities were applied in 10 s (frequency: 20 Hz). It was found that: (a) the degree of MU activation, as indicated by M-wave average rectified value, was a function of the injected charge and not of the stimulation waveform, and (b) MUs tended to be recruited in order of increasing conduction velocity with increasing charge of transcutaneous stimulation. Moreover, the subjects reported lower discomfort during the contractions elicited by the triangular waveform with respect to the others. Since subject tolerance to the stimulation protocol must be considered as important as MU recruitment in determining the effectiveness of neuromuscular electrical stimulation (NMES), we suggest that both charge and waveform of the stimulation pulses should be considered relevant parameters for optimizing NMES protocols.     

Electrical penetration graphs from Cicadulina mbila on maize, the fine structure of its stylet pathways and consequences for virus transmission efficiency

Five distinct electrical penetration graph waveforms characterising the feeding behaviour of the leafhopper Cicadulina mbila Naudé (Homoptera: Cicadellidae) on maize (Zea mays L.) were obtained using a DC based system. The waveforms were distinguished by spectral features and by statistical analysis of their median voltages, durations and time to first waveform recording. By changing the polarity of the system voltage and the level of the input resistor it was shown that the waveforms are mainly determined by the electromotive force (emf) component. Based on the correlation between waveforms and the fine structure of the stylet pathways observed by transmission electron microscopy, insect's activities have been associated with five waveforms: stylet pathway formation (waveform 1), active ingestion (waveform 2), putative stylet work (waveform 3), salivation (waveform 4) and passive ingestion (waveform 5). Like waveform E1 and E2 of aphids, waveforms 4 and 5 of C. mbila correspond to feeding activities in sieve tubes. However, unlike aphids which probe briefly in non-vascular cells, waveform 2 corresponds to active ingestion in cells, where the cell content is partially ingested and hence the organelles' integrity severely affected. These observations suggest that this specific feeding feature, typical of leafhoppers, determines their ability to acquire geminivirus virions located in the plant cell nucleus.     

Blind identification of the aortic pressure waveform from multiple peripheral artery pressure waveforms

We have developed a new technique to estimate the clinically relevant aortic pressure waveform from multiple, less invasively measured peripheral artery pressure waveforms. The technique is based on multichannel blind system identification in which two or more measured outputs (peripheral artery pressure waveforms) of a single-input, multi-output system (arterial tree) are mathematically analyzed so as to reconstruct the common unobserved input (aortic pressure waveform) to within an arbitrary scale factor. The technique then invokes Poiseuille's law to calibrate the reconstructed waveform to absolute pressure. Consequently, in contrast to previous related efforts, the technique does not utilize a generalized transfer function or any training data and is therefore entirely patient and time specific. To demonstrate proof of concept, we have evaluated the technique with respect to four swine in which peripheral artery pressure waveforms from the femoral and radial arteries and a reference aortic pressure waveform from the descending thoracic aorta were simultaneously measured during diverse hemodynamic interventions. We report that the technique reliably estimated the entire aortic pressure waveform with an overall root mean squared error (RMSE) of 4.6 mmHg. For comparison, the average overall RMSE between the peripheral artery pressure and reference aortic pressure waveforms was 8.6 mmHg. Thus the technique reduced the RMSE by 47%. As a result, the technique also provided similar improvements in the estimation of systolic pressure, pulse pressure, and the ejection interval. With further successful testing, the technique may ultimately be employed for more precise monitoring and titration of therapy in, for example, critically ill and hypertension patients.     

Determination of the average shape of flagellar bends: a gradient curvature model

Data obtained by manual digitization of photographs of flagellar bending waves have been analyzed by determining size parameters for the bends by least-squares fitting of a model waveform. These parameters were then used to normalize the data so that the average shape of the bends could be determined. Best fits were obtained with a model waveform derived from the constant curvature waveforms used previously but with provision for a linear change in curvature across the central region of the bend-the gradient curvature model (GCM). The central regions of the GCM bending waves are separated by transition regions with length determined by a parameter called the truncation factor (FT). Fitting the GCM to sine-generated bending waves give optimal fit when FT = 0.34. Fitting the GCM to four different samples of flagellar bending waves gave best fits with values of FT ranging from 0.17 for ATP-reactivated Lytechinus spermatozoa beating at approximately 10 Hz to 0.32 for live spermatozoa of Arbacia. The difference between the Arbacia waveforms and a sine-generated waveform is therefore very small, but a sine-generated waveform lacks the degree of freedom represented by FT that is required to fit other waveforms optimally. The residual differences between the waveform data and optimal GCM waveforms were averaged and found to be small. In most cases, the curvature in the central region of the optimal GCM decreased in magnitude towards the tip of the flagellum; however, this slope was highly variable and sometimes positive. Significant variations in both this slope and FT were found in individual bends as they propagated along a flagellum.     

视觉诱发电位波形的自动判别分析及其临床应用

计算诱发电位波形第一至第六次谐波的幅度和相位,把这12个参数作为判别分析的自变量.用32只正常眼、31只弱视眼和30只球后视神经炎患眼的诱发电位波形数据建立判别分析系统,再用另外32只正常眼、35只弱视眼和30只球后视神经炎患眼的诱发电位波形数据检验该判别分析系统的判别效果.     

Energy Efficient Neural Stimulation: Coupling Circuit Design and Membrane Biophysics

The delivery of therapeutic levels of electrical current to neural tissue is a well-established treatment for numerous indications such as Parkinson’s disease and chronic pain. While the neuromodulation medical device industry has experienced steady clinical growth over the last two decades, much of the core technology underlying implanted pulse generators remain unchanged. In this study we propose some new methods for achieving increased energy-efficiency during neural stimulation. The first method exploits the biophysical features of excitable tissue through the use of a centered-triangular stimulation waveform. Neural activation with this waveform is achieved with a statistically significant reduction in energy compared to traditional rectangular waveforms. The second method demonstrates energy savings that could be achieved by advanced circuitry design. We show that the traditional practice of using a fixed compliance voltage for constant-current stimulation results in substantial energy loss. A portion of this energy can be recuperated by adjusting the compliance voltage to real-time requirements. Lastly, we demonstrate the potential impact of axon fiber diameter on defining the energy-optimal pulse-width for stimulation. When designing implantable pulse generators for energy efficiency, we propose that the future combination of a variable compliance system, a centered-triangular stimulus waveform, and an axon diameter specific stimulation pulse-width has great potential to reduce energy consumption and prolong battery life in neuromodulation devices.     

Estimation of changes in instantaneous aortic blood flow by the analysis of arterial blood pressure

The purpose of this study was to introduce and validate a new algorithm to estimate instantaneous aortic blood flow (ABF) by mathematical analysis of arterial blood pressure (ABP) waveforms. The algorithm is based on an autoregressive with exogenous input (ARX) model. We applied this algorithm to diastolic ABP waveforms to estimate the autoregressive model coefficients by requiring the estimated diastolic flow to be zero. The algorithm incorporating the coefficients was then applied to the entire ABP signal to estimate ABF. The algorithm was applied to six Yorkshire swine data sets over a wide range of physiological conditions for validation. Quantitative measures of waveform shape (standard deviation, skewness, and kurtosis), as well as stroke volume and cardiac output from the estimated ABF, were computed. Values of these measures were compared with those obtained from ABF waveforms recorded using a Transonic aortic flow probe placed around the aortic root. The estimation errors were compared with those obtained using a windkessel model. The ARX model algorithm achieved significantly lower errors in the waveform measures, stroke volume, and cardiac output than those obtained using the windkessel model (P < 0.05).     

ML—2型心电导联转换仪的研制及其实践效果

目的：市售SYD－4228生理学学生实验系统没有配置心电图导联电缆及导联选择装置,不能进行观察心电图的实验,为此研制本心电导联转换仪。方法：设计并制作兼容网络与导联输入电缆,组装成新型的转换仪。结果：本转换仪配合SYD系统在高血钾实验中使用,满足了SYD系统进行心电图实验的需要。结论：本转换仪既适用于SYD系统,也适用于各型心电图机,可以同步对比观察不同导联的心电图。     

Parameter estimation in cardiac ionic models

We examine the problem of parameter estimation in mathematical models of excitable cell cardiac electrical activity using the well-known Beeler–Reuter (1977) ionic equations for the ventricular action potential. The estimation problem can be regarded as equivalent to the accurate reconstruction of ionic current kinetics and amplitudes in an excitable cell model, given only action potential experimental data. We show that in the Beeler–Reuter case, all ionic currents may be reasonably reconstructed using an experimental design consisting of action potential recordings perturbed by pseudo-random injection currents.

The Beeler–Reuter model was parameterised into 63 parameters completely defining all membrane current amplitudes and kinetics. Total membrane current was fitted to model-generated experimental data using a ‘data-clamp’ protocol. The experimental data consisted of a default action-potential waveform and an optional series of perturbed waveforms generated by current injections. Local parameter identifiability was ascertained from the reciprocal condition value (1/λ) of the Hessian at the known solution. When fitting to a single action potential waveform, the model was found to be over-determined, having a 1/λ value of 3.6e−14. This value improved slightly to 1.4e−10 when an additional 2 perturbed waveforms were included in the fitting process, suggesting that the additional data did not overly improve the identifiability problem. The additional data, however, did allow the accurate reconstruction of all ionic currents. This indicates that by appropriate experimental design, it may be possible to infer the properties of underlying membrane currents from observation of transmembrane potential waveforms perturbed by pseudo-random currents.     

Wavelet transform as a potential tool for ECG analysis and compression

The recently introduced wavelet transform is a member of the class of time-frequency representations which include the Gabor short-time Fourier transform and Wigner-Ville distribution. Such techniques are of significance because of their ability to display the spectral content of a signal as time elapses. The value of the wavelet transform as a signal analysis tool has been demonstrated by its successful application to the study of turbulence and processing of speech and music. Since, in common with these subjects, both the time and frequency content of physiological signals are often of interest (the ECG being an obvious example), the wavelet transform represents a particularly relevant means of analysis. Following a brief introduction to the wavelet transform and its implementation, this paper describes a preliminary investigation into its application to the study of both ECG and heart rate variability data. In addition, the wavelet transform can be used to perform multiresolution signal decomposition. Since this process can be considered as a sub-band coding technique, it offers the opportunity for data compression, which can be implemented using efficient pyramidal algorithms. Results of the compression and reconstruction of ECG data are given which suggest that the wavelet transform is well suited to this task.     

Waveform tuning of electroreceptor cells in the weakly electric fish, Gnathonemus petersii

Electroreceptive afferents from A- and B-electroreceptor cells of mormyromasts and Knollenorgans were tested for their sensitivity to different stimulus waveforms in the weakly electric fish Gnathonemus petersii. Both A- and B-mormyromast cells had their lowest sensitivity to a waveform similar to the self-generated electric organ discharge (EOD) (around 0° phase-shift). Highest sensitivities, i.e. lowest response thresholds, in both A- and B-cells were measured at phase shifts of +135°. Thus, both cell types were inversely waveform tuned. The sensitivity of B-cells increased sharply with increasing waveform distortions. Their tuning curves had a sharp minimum of sensitivity at +7° phase shift. A-cells had a much broader waveform tuning with a plateau level of low sensitivity from +24° to −15°. Across a 360° cycle of phase-shifts, the range of thresholds was 16 dB for individual B-cells and 4.5 dB for individual A-cells. Knollenorgan afferents were tuned to 0° phase-shifted EODs and had a dynamic range of 12 dB. Lowest sensitivities were measured at a phase shift of +165°. Experiments with computer-generated stimuli revealed that the strong sensitivity of mormyromast B-cells of EOD waveform distortions cannot be attributed to any of the seven waveform parameters tested. In addition, EOD stimuli must have the correct duration for B-cells to respond to waveform distortions. Thus, waveform tuning appears to be based on the specific combination of several waveform parameters that occur only with natural EODs. Accepted: 28 April 1997     

Empirical Mode Decomposition and Wavelet Transform Based ECG Data Compression Scheme

ObjectiveIn health-care systems, compression is an essential tool to solve the storage and transmission problems. In this regard, this paper reports a new electrocardiogram (ECG) data compression scheme which employs sifting function based empirical mode decomposition (EMD) and discrete wavelet transform.MethodEMD based on sifting function is utilized to get the first intrinsic mode function (IMF). After EMD, the first IMF and four significant sifting functions are combined together. This combination is free from many irrelevant components of the signal. Discrete wavelet transform (DWT) with mother wavelet ‘bior4.4’ is applied to this combination. The transform coefficients obtained after DWT are passed through dead-zone quantization. It discards small transform coefficients lying around zero. Further, integer conversion of coefficients and run-length encoding are utilized to achieve a compressed form of ECG data.ResultsCompression performance of the proposed scheme is evaluated using 48 ECG records of the MIT-BIH arrhythmia database. In the comparison of compression results, it is observed that the proposed method exhibits better performance than many recent ECG compressors. A mean opinion score test is also conducted to evaluate the true quality of the reconstructed ECG signals.ConclusionThe proposed scheme offers better compression performance with preserving the key features of the signal very well.     

Wavelet Domain Radiofrequency Pulse Design Applied to Magnetic Resonance Imaging

A new method for designing radiofrequency (RF) pulses with numerical optimization in the wavelet domain is presented. Numerical optimization may yield solutions that might otherwise have not been discovered with analytic techniques alone. Further, processing in the wavelet domain reduces the number of unknowns through compression properties inherent in wavelet transforms, providing a more tractable optimization problem. This algorithm is demonstrated with simultaneous multi-slice (SMS) spin echo refocusing pulses because reduced peak RF power is necessary for SMS diffusion imaging with high acceleration factors. An iterative, nonlinear, constrained numerical minimization algorithm was developed to generate an optimized RF pulse waveform. Wavelet domain coefficients were modulated while iteratively running a Bloch equation simulator to generate the intermediate slice profile of the net magnetization. The algorithm minimizes the L2-norm of the slice profile with additional terms to penalize rejection band ripple and maximize the net transverse magnetization across each slice. Simulations and human brain imaging were used to demonstrate a new RF pulse design that yields an optimized slice profile and reduced peak energy deposition when applied to a multiband single-shot echo planar diffusion acquisition. This method may be used to optimize factors such as magnitude and phase spectral profiles and peak RF pulse power for multiband simultaneous multi-slice (SMS) acquisitions. Wavelet-based RF pulse optimization provides a useful design method to achieve a pulse waveform with beneficial amplitude reduction while preserving appropriate magnetization response for magnetic resonance imaging.     

Ischemia episode detection in ECG using kernel density estimation, support vector machine and feature selection

ABSTRACT: BACKGROUND: Myocardial ischemia can be developed into more serious diseases. Early Detection of the ischemic syndrome inelectrocardiogram (ECG) more accurately and automatically can prevent it from developing into a catastrophicdisease. To this end, we propose a new method, which employs wavelets and simple feature selection. METHODS: For training and testing, the European ST-T database is used, which is comprised of 367 ischemic ST episodes in90 records. We first remove baseline wandering, and detect time positions of QRS complexes by a method basedon the discrete wavelet transform. Next, for each heart beat, we extract three features which can be used fordifferentiating ST episodes from normal: 1) the area between QRS offset and T-peak points, 2) the normalizedand signed sum from QRS offset to effective zero voltage point, and 3) the slope from QRS onset to offset point.We average the feature values for successive five beats to reduce effects of outliers. Finally we apply classifiersto those features. RESULTS: We evaluated the algorithm by kernel density estimation (KDE) and support vector machine (SVM) methods.Sensitivity and specificity for KDE were 0.939 and 0.912, respectively. The KDE classifier detects 349 ischemicST episodes out of total 367 ST episodes. Sensitivity and specificity of SVM were 0.941 and 0.923, respectively.The SVM classifier detects 355 ischemic ST episodes. CONCLUSIONS: We proposed a new method for detecting ischemia in ECG. It contains signal processing techniques of removingbaseline wandering and detecting time positions of QRS complexes by discrete wavelet transform, and featureextraction from morphology of ECG waveforms explicitly. It was shown that the number of selected featureswere sufficient to discriminate ischemic ST episodes from the normal ones. We also showed how the proposedKDE classifier can automatically select kernel bandwidths, meaning that the algorithm does not require anynumerical values of the parameters to be supplied in advance. In the case of the SVM classifier, one has to selecta single parameter.     

On-line analysis of neuromuscular bioelectric potentials

A computer system is presented which provides for on-line data capture and analysis of evoked end-plate potentials and action potentials, and on-line data capture with off-line analysis of spontaneously occurring miniature end-plate potentials at the end-plate region of the neuromuscular junction. Sampling of evoked waveforms begins after an adjustable delay following the stimulus. Spontaneously occurring waveforms are captured by 'freezing' the contents of a circular buffer. The software provides MENU selectable support functions including storage and retrieval of data and calculated parameters, analog and digital display of waveforms, data calibration and gain modification, data editing, file management, and hardcopy output. Calculated parameters of the waveform are optionally placed in a data base file by the analysis programs. The data base may be used for editing, arithmetic operations, and subsetting of variables as well as statistical analysis and plotting of any selected variables.     

ECG Data Compression Using Modified Run Length Encoding of Wavelet Coefficients for Holter Monitoring

ObjectiveIn cardiac patient-care, compression of long-term ECG data is essential to minimize the data storage requirement and transmission cost. Hence, this paper presents a novel electrocardiogram data compression technique which utilizes modified run-length encoding of wavelet coefficients.MethodFirst, wavelet transform is applied to the ECG data which decomposes it and packs maximum energy to less number of transform coefficients. The wavelet transform coefficients are quantized using dead-zone quantization. It discards small valued coefficients lying in the dead-zone interval while other coefficients are kept at the formulated quantized output interval. Among all the quantized coefficients, an average value is assigned to those coefficients for which energy packing efficiency is less than 99.99%. The obtained coefficients are encoded using modified run-length coding. It offers higher compression ratio than conventional run-length coding without any loss of information.ResultsCompression performance of the proposed technique is evaluated using different ECG records taken from the MIT-BIH arrhythmia database. The average compression performance in terms of compression ratio, percent root mean square difference, normalized percent mean square difference, and signal to noise ratio are 17.18, 3.92, 6.36, and 28.27 dB respectively for 48 ECG records.ConclusionThe compression results obtained by the proposed technique is better than techniques recently introduced by others. The proposed technique can be utilized for compression of ECG records of Holter monitoring.