数字信号处理在生物医学工程中的应用

数字信号处理技术一诞生就显示了强大的生命力,展现了极为广阔的应用前景.主要讨论数字信号处理技术中小波分析、人工神经网络、维格纳分布在生物医学工程中的应用,并对数字信号处理技术在生物医学工程中的应用前景进行了展望.     

Characterization of single channel currents using digital signal processing techniques based on Hidden Markov Models.

Techniques for extracting small, single channel ion currents from background noise are described and tested. It is assumed that single channel currents are generated by a first-order, finite-state, discrete-time, Markov process to which is added 'white' background noise from the recording apparatus (electrode, amplifiers, etc). Given the observations and the statistics of the background noise, the techniques described here yield a posteriori estimates of the most likely signal statistics, including the Markov model state transition probabilities, duration (open- and closed-time) probabilities, histograms, signal levels, and the most likely state sequence. Using variations of several algorithms previously developed for solving digital estimation problems, we have demonstrated that: (1) artificial, small, first-order, finite-state, Markov model signals embedded in simulated noise can be extracted with a high degree of accuracy, (2) processing can detect signals that do not conform to a first-order Markov model but the method is less accurate when the background noise is not white, and (3) the techniques can be used to extract from the baseline noise single channel currents in neuronal membranes. Some studies have been included to test the validity of assuming a first-order Markov model for biological signals. This method can be used to obtain directly from digitized data, channel characteristics such as amplitude distributions, transition matrices and open- and closed-time durations.     

The use of fluoresceinphosphatidylethanolamine (FPE) as a real-time probe for peptide-membrane interactions

The characterization of fluorescelnphosphatidylethanolamlne (FPE) as a real-time Indicator of the electrostatic nature of a membrane surface is described. The conditions appropriate for the labelling of membranes and the implementation of FPE as a tool to monitor the interactions of various peptides with model membranes are outlined. It is shown that of the membrane-active peptides studied, Naja naja kaouthla cardiotoxin and pyrularia thionin bind to certain model membranes without insertion. Whereas the leader sequence of the nuclear encoded subunit IV of mammalian cytochrome c oxidase (E.C. 1.9.3.1), known as p-25, and melittin appear to bind and then partially insert into the membrane. It seems evident also that melittin does not adopt a fully transmembrane configuration. Melittin is known to promote membrane lysis and by employing a rapid-kinetic technique it is shown that the time-course of such lysis does not appear to correlate with peptide binding, but following binding a significant proportion of melittin must become inserted into the membrane before lysis appears to commence.     

The value of asymmetric signal processing in klinokinesis

Klinokinesis is a behavioral mechanism in which an organism moves toward or away from a stimulus source by altering its frequency of change of direction without biasing its turns with respect to the stimulus field. Previous studies of a variety of organisms have demonstrated that rates of adaptation (or other information processing features) for increases and decreases in stimulus intensity are often very different from one another. In order to determine if such asymmetric signal processing could improve the efficiency of klinokinesis, computer modeling studies were performed. The model involved a simple generic version of klinokinesis in 2 dimensions with the rate of adaptation for increasing intensity varied independently of the rate for decreasing intensity. The effects of three types of noise that limit the performance of the model were tested-intensity noise, motor noise, and developmental noise. The results demonstrated that, with all three types of noise, the two adaptation rates had quite different effects on efficiency. The overall pattern of effects was different for each type of noise. In the cases of intensity noise and motor noise, the optimum combination of adaptation rates had a 3-to 5-fold higher rate for decreases in attractant than for increases, which is similar to what has previously been found with bacteria and nematodes.     

The digital processing of the images in x-ray microanalysis

Image analysis of X-ray microanalytical maps of sodium, potassium, phosphorus, chloride and calcium was carried out on the IBAS image analysis system (OPTON, FRG). In the present work, algorithms were developed for getting a new semiquantitative information from the binary images of maps: the element profile on the chosen line, the isoconcentration mapping and the multiple elemental mapping. It is possible to get as many as eight different elemental maps on the same image (with 8-bit resolution of pixel) and to extract the pixels with element overlappings.     

Behavioral analysis of Vibrio parahaemolyticus variants in high- and low-viscosity microenvironments by use of digital image processing.

Digital image analysis and light microscopy were used to study and quantify the growth and behavior of two variants and selected flagellar mutants of Vibrio parahaemolyticus in glass flow cells under high- and low-viscosity conditions. The observations showed a series of surface-associated behaviors, including attachment, microcolony formation, migration, chemotactic movements, and aggregation, indicating a substantial degree of adaptive flexibility and multicellular behavior during growth of V. parahaemolyticus at interfaces.     

Excitation signal processing times in Halobacterium halobium phototaxis.

Phototaxis responses of Halobacterium halobium were monitored with a computerized cell-tracking system coupled to an electronic shutter controlling delivery of photostimuli. Automated analysis of rates of change in direction and linear speeds provided detection of swimming reversals with 67 ms resolution, permitting measurement of distinct phases of the responses to attractant and repellent stimuli. After stimulation, there was a latency period in which the population reversal frequency was unchanged, followed by an excitation phase in which reversal frequency increased, and a slower adaptation phase in which reversal frequency returned to its prestimulus value. A step-decrease in illumination of the attractant receptor slow-cycling or sensory rhodopsin (SR) (lambda max, 587 nm) was interpreted by the cells as an unfavorable stimulus and, after a minimum latency of 0.70 +/- 0.14 s, induced swimming reversals with the peak response occurring 1.34 +/- 0.07 s after onset of the stimulus. Two distinct repellent responses in the near UV/blue were observed. One was a reversal response to 400 nm light, which was dependent on orange-red background illumination as expected for the photointermediate repellent form of SR (lambda max, 373 nm). The minimum latency of this response was approximately the same as that of the SR attractant system. The second was a reversal response with shorter minimum latency (0.40 +/- 0.07 s) to light of longer wavelength (450 nm) than absorbed by the known SR repellent form. This result confirms recent findings of an additional repellent photosystem in this spectral range. Further, the longer wavelength repellent response is independent of orange-red background illumination, indicating that the photoreceptor mediating this response is not a photointermediate of SR.     

The role of independent component analysis in the signal processing of ECG recordings.

Independent component analysis (ICA) is an emerging technique for multidimensional signal processing. In recent years, these techniques have been proposed for solving a large number of biomedical applications. This work reviews current knowledge on ICA in electrocardiographic (ECG) analysis. The benefits that ICA can bring to clinical practice are illustrated with four relevant clinical applications: foetal ECG extraction from maternal ECG recordings, analysis of atrial fibrillation, ECG denoising and removal of pacemaker artefacts.     

Structural characterization of a ribonuclease III processing signal.

The structure of a ribonuclease III processing signal from bacteriophage T7 was examined by NMR spectroscopy, optical melting, and chemical and enzymatic modification. A 41 nucleotide variant of the T7 R1.1 processing signal has two Watson-Crick base-paired helices separated by an internal loop, consistent with its predicted secondary structure. The internal loop is neither rigidly structured nor completely exposed to solvent, and seems to be helical. The secondary structure of R1.1 RNA is largely insensitive to the monovalent cation concentration, which suggests that the monovalent cation sensitivity of secondary site cleavage by RNase III is not due to a low salt-induced RNA conformational change. However, spectroscopic data show that Mg2+ affects the conformation of the internal loop, suggesting a divalent cation binding site(s) within this region. The Mg(2+)-dependence of RNase III processing of some substrates may reflect not only a requirement for a divalent cation as a catalytic cofactor, but also a requirement for a local RNA conformation which is divalent cation-stabilized.     

The use of hydrolysis and hairpin probes in real-time PCR

In this review we discuss the limitations of traditional PCR methods and introduce real-time PCR, a fluorescence-based detection system, as a method that overcomes these limitations. We describe the technologies involved in real-time PCR including the design of hydrolysis and hairpin probes and the practical applications of such systems.     

Multivariate classification of animal communication signals: A simulation-based comparison of alternative signal processing procedures using electric fishes

Evolutionary studies of communication can benefit from classification procedures that allow individual animals to be assigned to groups (e.g. species) on the basis of high-dimension data representing their signals. Prior to classification, signals are usually transformed by a signal processing procedure into structural features. Applications of these signal processing procedures to animal communication have been largely restricted to the manual or semi-automated identification of landmark features from graphical representations of signals. Nonetheless, theory predicts that automated time-frequency-based digital signal processing (DSP) procedures can represent signals more efficiently (using fewer features) than can landmark procedures or frequency-based DSP – allowing more accurate classification. Moreover, DSP procedures are objective in that they require little previous knowledge of signal diversity, and are relatively free from potentially ungrounded assumptions of cross-taxon homology. Using a model data set of electric organ discharge waveforms from five sympatric species of the electric fish Gymnotus, we adopted an exhaustive simulation approach to investigate the classificatory performance of different signal processing procedures. We considered a landmark procedure, a frequency-based DSP procedure (the fast Fourier transform), and two kinds of time-frequency-based DSP procedures (a short-time Fourier transform, and several implementations of the discrete wavelet transform -DWT). The features derived from each of these signal processing procedures were then subjected to dimension reduction procedures to separate those features which permit the most effective discrimination among groups of signalers. We considered four alternative dimension reduction methods. Finally, each combination of reduced data was submitted to classification by linear discriminant analysis. Our results support theoretical predictions that time-frequency DSP procedures (especially DWT) permit more efficient discrimination of groups. The performance of signal processing was found to depend largely upon the dimension reduction procedure employed, and upon the number of resulting features. Because the best combinations of procedures are dataset-dependent and difficult to predict, we conclude that simulations of the kind described here, or at least simplified versions of them, should be routinely executed before classification of animal signals - especially unfamiliar ones.     

Techniques of EMG signal analysis: detection, processing, classification and applications (Correction)

This paper was originally published in Biological Procedures Online (BPO) on March 23, 2006. It was brought to the attention of the journal and authors that reference 74 was incorrect. The original citation for reference 74, “Stanford V. Biosignals offer potential for direct interfaces and health monitoring. Pervasive Computing, IEEE 2004; 3(1):99–103.” should read “Costanza E, Inverso SA, Allen R. ‘Toward Subtle Intimate Interfaces for Mobile Devices Using an EMG Controller’ in Proc CHI2005, April 2005, Portland, OR, USA.”