Conventional Signal Processing Techniques Research Articles

A new method for pulse oximetry possessing inherent insensitivity to artifact.

A new method for pulse oximetry is presented that possesses an inherent insensitivity to corruption by motion artifact, a primary limitation in the practical accuracy and clinical applicability of current technology. Artifact corruption of the underlying photoplethysmographic signals is reduced in real time, using an electronic processing methodology that is based upon inversion of a physical artifact model. This fundamental approach has the potential to provide uninterrupted output and superior accuracy under conditions of sustained subject motion, therefore, widening the clinical scope of this useful measurement. A new calibration technique for oxygen saturation is developed for use with these processed signals, which is shown to be a generalization of the classical interpretation. The detailed theoretical and practical issues of implementation are then explored, highlighting important engineering simplifications implicit in this new approach. A quantitative investigation of the degree of insensitivity to artifact is also undertaken, with the aid of a custom electronic system and commercial pulse oximeter probes, which is compared and contrasted with the performance of a conventional implementation. It is demonstrated that this new methodology results in a reduced sensitivity to common classes of motion artifact, while retaining the generality to be combined with conventional signal processing techniques.

Corrosion Process Monitoring Using Wavelet Analysis

The objective of this paper is to explore the use of wavelet transform methods in the characterization and identification of intensity and type of localized corrosion using electrochemical noise (in this case, fluctuations in potential). A series of experiments were conducted using two identical stainless steel electrodes inserted into known corrosive media. The fluctuations in corrosion potential (electrochemical noise) generated from these electrodes were monitored periodically (about every hour) over a few days. These fluctuations were stored in blocks of 1024 data points (collected at 1 Hz). They were analyzed by using conventional signal processing techniques in the time and frequency domains as well as by using wavelet techniques in the time-frequency phase plane. The results were compared with microscopic visual examination of the corroded surface to correlate the electrochemical noise signal with the type and extent of corrosion. The results show that wavelet transforms hold promise in decoding this noise pattern. A method to compute the corrosion intensity from the phase plane data is proposed and is in qualitative agreement with the experimental results.

Optical BEAMTAP beam-forming and jammer-nulling system for broadband phased-array antennas

We present an approach to receive-mode broadband beam forming and jammer nulling for large adaptive antenna arrays as well as its efficient and compact optical implementation. This broadband efficient adaptive method for true-time-delay array processing (BEAMTAP) algorithm decreases the number of tapped delay lines required for processing an N-element phased-array antenna from N to only 2, producing an enormous savings in delay-line hardware (especially for large broadband arrays) while still providing the full NM degrees of freedom of a conventional N-element time-delay-and-sum beam former that requires N tapped delay lines with M taps each. This allows the system to adapt fully and optimally to an arbitrarily complex spatiotemporal signal environment that can contain broadband signals of interest, as well as interference sources and narrow-band and broadband jammers--all of which can arrive from arbitrary angles onto an arbitrarily shaped array--thus enabling a variety of applications in radar, sonar, and communication. This algorithm is an excellent match with the capabilities of radio frequency (rf) photonic systems, as it uses a coherent optically modulated fiber-optic feed network, gratings in a photorefractive crystal as adaptive weights, a traveling-wave detector for generating time delay, and an acousto-optic device to control weight adaptation. Because the number of available adaptive coefficients in a photorefractive crystal is as large as 10(9), these photonic systems can adaptively control arbitrarily large one- or two-dimensional antenna arrays that are well beyond the capabilities of conventional rf and real-time digital signal processing techniques or alternative photonic techniques.

A real-time knowledge-based system for intelligent monitoring in complex, sensor-rich environments

Abstract Real-time and on-line optimisation methods for control of large-scale systems use real-time sensor data to optimise the system's performance. The data need to be pre-processed for faults to safeguard against inappropriate control actions. Conventional real-time signal processing techniques are likely to fail because of the system's complexity and the processing speed required. A generic, real-time knowledge-based system—FLASH (FLexible AI for Signal Handling in real time)—has been developed to detect, diagnose and replace faulty sensor readings. Its effectiveness in processing signals for control in a complex, sensor-rich environment has been demonstrated in real-time environmental control of greenhouse microclimate.

Application of wavelets in Doppler ultrasound

Provides an introduction into wavelets and illustrates their application with two examples. The wavelet transform provides the analyst with a scaleable time‐frequency representation of the signal, which may uncover details not evidenced by conventional signal processing techniques. The signals used in this paper are Doppler ultrasound recordings of blood flow velocity taken from the internal carotid artery and the femoral artery. Shows how wavelets can be used as an alternative signal processing tool to the short time Fourier transform for the extraction of the time‐frequency distribution of Doppler ultrasound signals. Implements wavelet‐based adaptive filtering for the extraction of maximum blood velocity envelopes in the post processing of Doppler signals.

Bowel-sound signal enhancement using adaptive filtering.

We hypothesized that computerized analysis of gastrointestinal acoustic phenomena (GAP) may provide an accurate, rapid, safe, and inexpensive method of diagnosing a wide range of gastrointestinal conditions. Adaptive filters (AFs) and other conventional signal-processing techniques were employed for heart-sound (HS) cancellation. The objective was to remove HSs with minimum GAP distortion. After an overview of AF applications in biomedicine, we review our methods for HS removal in the laboratory and we discuss the results of the study.

Man-made target backscattering behavior: applicability of conventional radar resolution theory

Radar is not achieving its potential performance. The reasons for this are discussed. The backscattering behavior of man-made targets is much more complicated than conventionally modeled. This makes the conventional resolution theory inappropriate when man-made targets are highly resolved, with the consequence that conventional signal processing and image analysis techniques miss much of the information in the radar returns. The type of backscattering behavior we have observed with real data, and how it affects resolution performance is discussed here. It is also shown that one must analyze the complex image rather than the intensity image.

Heterodyne detection technique using stimulated Brillouin scattering and a multimode laser

We present, for the first time to our knowledge, the use of multiple axial laser modes in distributed temperature sensing based on stimulated Brillouin scattering. One axial mode stimulates a Stokes wave with a temperaturedependent Brillouin frequency shift in the 13-GHz range. Optical heterodyning of the stimulated Stokes wave with a second axial laser mode allows one to generate and evaluate a beat signal in a lower frequency range. Using diode-pumped solid-state lasers, we have reduced the Brillouin beat frequency to the 500-MHz range. Hence, low-cost detectors and conventional signal-processing techniques can be applied for the beat signal processing.

Instantaneous frequency of a transient mechanical signature and its estimation by a moving window; applicability and physical interpretation

Instantaneous frequency often indicates the occurrence of specific events which could indicate a change in the action of machinery. It is therefore useful to find a way to utilise instantaneous frequency on the characterisation of transient actions of mechanical components. This can also be based on conventional signal processing techniques such as amplitude--time domain data and Fourier analysis. In this paper, we look at the possibility of applying instantaneous frequency to analyse transient mechanical signatures. We found that instantaneous frequency is quite sensitive to signal to noise ratio and therefore to utilise this measure an improved estimator which can minimise the effect of noise on the estimation is needed. The suggested method is a moving window in the time domain, which essentially averages out the noise effect for the prescribed window length. The proposed method reduces the noise effect on the instantaneous frequency estimation but is not satisfactory for signals which have quite low signal to noise ratios. To deal with this, we proposed an 'instantaneous frequency histogram' which shows the number of occurrences of instantaneous frequency and can thus be used to grade the meaningful instantaneous frequency components. The non-linear characteristics of the instantaneous frequency which produce the additional component of the signal which in general has frequencies which differ from the original signals is discussed in terms of its applicability and limitations for mechanical signature analysis.

The application of artificial neural networks to non-intrusive multi-phase metering

Transducers monitoring multi-phase flow in pipelines produce complex signals containing a wealth of information. Whilst this information is difficult to assimilate, it does contain intrinsically the characteristics of of the natural flow. However, conventional signal processing techniques find such complex signals difficult to analyse due to the high level of understanding of the signal required to implement the processing algorithms.

Spectral analysis of randomly distributed scatterers for ultrasonic grain size estimation

Since the average grain size is an important parameter in material characterization, the non-destructive evaluation of the microstructure in polycrystalline materials using ultrasonic backscattered echoes has significant practical implications. However, the complexity of the ultrasonic backscattered signal, which consists of interrering multiple echoes with random positions and amplitudes, makes accurate grain size evaluation difficult with conventional signal processing techniques. This Paper introduces an alternative approach which examines the spectrum of an ensemble of randomly distributed scatterers with known distribution to establish a relationship between the spectral and temporal statistical properties of the scatterers. Theoretical derivations based on a one-dimensional point scattered model show that the average grain size can be extracted from the power spectrum of the backscattered echoes. Using a non-linear least-squares technique, the theoretical grain power spectrum is curve-fitted to the sample grain power spectrum to estimate the mean and standard deviation of the grain size. Computer simulations based on this technique show that the average grain size can be extracted from the power spectrum of the backscattered echoes, indicating the potential feasibility of this technique for material characterization.

Wave-vector-frequency spectral estimation: A review of conventional signal processing techniques

Signal processing techniques for estimating wave-vector-frequency spectra of space-time fields from measured data parallel those developed by electrical engineers for estimating frequency spectra from measured samples of temporal fields. This paper reviews a conventional technique for estimating the wave-vector-frequency spectrum from samples of a space-time field measured through an array of sensors. The mean value of this specral estimate can be related to the true spectrum of the space-time field and the wave-vector and frequency responses associated with the various components of the signal processing. This relationship permits, under certain conditions, the quality of the spectral estimate to be assessed. The dependence of the quality of the spectral estimate on the various components of the signal processing is discussed.

ON TIMING THE VSP FIRST ARRIVAL*

AbstractThe advent of signal energy on a VSP or check‐shot trace may be defined as the first break. An accurate pick of this first break would be possible in the absence of noise. However, real data traces are inevitably corrupted by noise and this leads to difficulty in identifying a break because the signal‐to‐noise ratio is low in its neighbourhood.Under such conditions, an obvious alternative is to pick “troughs” where the local signal‐to‐noise ratio is likely to be much higher. Although trough picking is an effective way to minimize the noise problem, it is sensitive to signal properties (such as absorption and multiple reflections) which have no effect upon the accuracy of break picks. Thus, trough picking is signal‐sensitive and break picking is noise‐sensitive.Clearly, an ideal first‐arrival picking scheme would combine the noise‐tolerant features of trough picking with the signal‐tolerant features of break picking. This ideal may be approached by exploiting known properties of the VSP trace using conventional signal processing techniques. The result of such processing is to reduce the problem to that of picking a trough correctly centered about the true break time.

Practical considerations in the implementation of the French-Holden algorithm for sampling of neuronal spike trains.

The French-Holden algorithm (1), (2), (3) provides a sampled data time series representation of a neuronal spike train in order to facilitate subsequent analyses by conventional signal processing techniques. Two characteristics of this filtering algorithm make the choice of data record length particularly important: (a) an ideal, sharp cutoff filter is used on the spike train, and (b) the Nyquist sampling frequency is chosen exactly equal to the filter cutoff frequency. In this note, sources of distortion and aliasing errors due to finite data records are discussed and guidelines for the selection of minimum record length are given.

Simple Technique for Sequential Q-Switching of Molecular Lasers

A simple technique for sequentially Q-switching molecular lasers (e.g., CO(2), CO, HF) is discussed in which an optical scanner is used as an optical folding element in a laser cavity consisting of a stationary diffraction grating and partially reflecting mirror. Sequential Q-swtiching of a conventional CO(2) laser is demonstrated in which over sixty-two transitions between 9.2 micro and 10.8 micro are observed. Rapid repetition rates (200 Hz) and narrow laser pulses (<5 microsec) allow conventional signal processing techniques to be used with this multi-wavelength laser source which is a versatile tool for laser propagation studies, absorption spectroscopy, and gain measurements. Results of a preliminary experiment demonstrating the utility of measuring selective absorption of CO(2) laser wavelengths by C(2)H(4) is shown, but selective absorption by atmospheric CO(2), NH(3), and O(3) can also be studied. With appropriate optical sca ners and diffraction gratings, sequential Q-switching of CO and HF lasers is possible.