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PubMed2002

Experimental investigation of subspace identification and LQ control of a pressure tank.

Many control studies of complex processes are limited to simulation studies. However, many real processes exhibit peculiarities and nonlinearities that are difficult to model. Also some control designs are difficult to implement online in practice. Because of the recent availability of economical real time software, more complex control algorithms will see real time testing and implementation. In spite of this, many compromises are often necessary when the final control is implemented. This paper follows the identification (using subspace methods) and real time linear quadratic control of a pressure tank system and points to some of the compromises in identification and control design that are often necessary. A multivariate control is implemented on a pressure tank process with rather good results in spite of these compromises.

Air Pressure↗
PubMed2002

Identification and robust control of an experimental servo motor.

In this work, the design of a robust controller for an experimental laboratory-scale position control system based on a dc motor drive as well as the corresponding identification and robust stability analysis are presented. In order to carry out the robust design procedure, first, a classic closed-loop identification technique is applied and then, the parametrization by internal model control is used. The model uncertainty is evaluated under both parametric and global representation. For the latter case, an interesting discussion about the conservativeness of this description is presented by means of a comparison between the uncertainty disk and the critical perturbation radius approaches. Finally, conclusions about the performance of the experimental system with the robust controller are discussed using comparative graphics of the controlled variable and the Nyquist stability margin as a robustness measurement.

Computer Simulation↗
PubMed2003

An approach to improve the offshore platform coordinates accuracy by using multichannel Kalman filtering.

In this paper, multichannel Kalman filters for estimation of offshore platform (OP) coordinates are designed. The complete OP motion is assumed to be composed of the low-frequency motion caused by the wind and undercurrent, and the high-frequency motion caused by the sea. The mathematical model of the low-frequency OP motion is given by the normal differential equation system, and the high-frequency OP motion is represented by a moving-average multivariable autoregression model. The parameter estimation problem for the model of the low-frequency OP motion, on which the in-service control is performed, is solved through two jointly operating Kalman filters: the first one is for the estimation of the parameters of the low-frequency motion model, and the second one is for the parameter estimation for the high-frequency model. The parameters of the first filter are automatically adapted to variations of the second filter, i.e., they are adapted to disturbances from the sea. Two algorithms for the OP motion parameter estimation (parallel and with preliminary data compression). employed for several measuring channels data estimation, are developed, and simulated on a computer. Some recommendations on their use are given.

Algorithms↗
PubMed2003

Auto-tuning of cascade control systems.

In this paper, a novel auto-tuning method for a cascade control system is proposed. By employing a simple relay feedback test, both inner and outer loop model parameters can be simultaneously identified. Consequently, well-established proportional-integral-derivative (PID) tuning rules can be applied to tune both loops. Compared with existing methods, the new method is simpler and yet more effective. It can be directly integrated into commercially available industrial auto-tuning systems. Some examples are given to illustrate the effectiveness and robustness of the proposed method.

Aircraft↗
PubMed2003

Practical approach to tuning MPC.

This paper presents the results of a heuristic approach for developing model predictive control (MPC) tuning rules. The tuning has been applied and tested in easy-to-use MPC. Process modeling in this MPC uses normalized input/ output range. As a result there is no need for tuning outputs, a procedure known as adjusting equal concern error. Penalties on moves are set as a function of process dead time as the primary factor, with some correction from process gain. The default calculation delivers robust control, which tolerates up to triple increase in process static gain. If control is too aggressive, further on-line adjustment can be done by set point reference trajectory. Test results show that this tuning is robust for process gain change, however, it is much less efficient in compensating for process dead-time changes. It was found that dead-time mismatch is much better compensated with the model correction filter. Combining the three handles, i.e., penalties on moves, reference trajectory, and model filter, easy and intuitively understandable MPC tuning was achieved. The findings are illustrated by numerous MPC simulated tests.

Computer Simulation↗
PubMed2006

An online novel adaptive filter for denoising time series measurements.

A nonstationary form of the Wiener filter based on a principal components analysis is described for filtering time series data possibly derived from noisy instrumentation. The theory of the filter is developed, implementation details are presented and two examples are given. The filter operates online, approximating the maximum a posteriori optimal Bayes reconstruction of a signal with arbitrarily distributed and non stationary statistics.

Algorithms↗
PubMed1999

Maximum a posteriori deconvolution of sparse ultrasonic signals using genetic optimization.

Deconvolution of sparse spike sequences has received much attention in the field of seismic exploration. In certain situations in ultrasonic non-destructive testing (NDT) of materials, similar conditions as those found in seismic exploration occur. One example is the problem of detecting disbonds in layered aluminum structures. The reflection sequence convolved with the impulse response of the transducer results in masking closely spaced reflections. Deconvolution of these signals may reveal the reflection sequence and thus make the interpretation easier. In this paper we use the Bernoulli-Gaussian (BG) distribution for modeling the signal generation. This relatively simple model allows maximum a posteriori (MAP) estimation of the reflection sequence. A derivation of the MAP criterion is given for clarity. We propose a genetic algorithm for optimizing the MAP criterion. The genetic algorithm approach is motivated by the fact that the criterion is non-convex, implying that the criterion may have more than one local minimum point. The probability of obtaining the global optimal solution is increased by using the proposed genetic algorithm. One of the key features in genetic algorithms, the so-called cross-over operator, has been modified and adapted to the structure of the BG deconvolution problem to improve the efficiency of the search. The algorithm is tested on simulated data using the probability of detection (PD) and probability of false alarm (PFA) as evaluation criteria. The algorithm is also tested on real ultrasonic data from a layered aluminum structure. The results show considerable improvements in the possibility of interpreting the signals.

Algorithms↗
PubMed2002

Detection of onset of neuronal activity by allowing for heterogeneity in the change points.

We consider situations in which there is a change point in the activity of a cell, that is, some time after an external event the firing rate of the cell changes. The change can occur after a random delay. The distribution of the time to change is considered unknown. Formally we deal with n random point processes, each of these is an inhomogeneous Poisson process, with one intensity until a random time, and a different intensity thereafter. Thus, the change point is not explicitly observed. We present both a simple estimator and the non-parametric maximum likelihood estimator (NPMLE) of the change point distribution, both having the same rate of convergence. This rate is proved to be the best possible. The extension of the basic model to multiple processes per trial with different intensities and joint multiple change points is demonstrated using both simulated and neural data. We show that for realistic spike train data, trial by trial estimation of a change point may be misleading, while the distribution of the change point distribution can be well estimated.

Action Potentials↗
PubMed2002

Using noise signature to optimize spike-sorting and to assess neuronal classification quality.

We have developed a simple and expandable procedure for classification and validation of extracellular data based on a probabilistic model of data generation. This approach relies on an empirical characterization of the recording noise. We first use this noise characterization to optimize the clustering of recorded events into putative neurons. As a second step, we use the noise model again to assess the quality of each cluster by comparing the within-cluster variability to that of the noise. This second step can be performed independently of the clustering algorithm used, and it provides the user with quantitative as well as visual tests of the quality of the classification.

Action Potentials↗
PubMed2003

A method for quantifying reflex responses from intra-muscular and surface electromyogram.

Measuring human reflex responses from electromyogram (EMG) traces in an accurate, repeatable and reliable way with a high degree of specificity has traditionally been a difficult task. This paper describes a new method that can be used to quantify reflex responses from both surface and intra-muscular EMG. This technique extends the classical cumulative sum (CUSUM) calculations by defining precise points for the calculation of latencies, durations and strengths to facilitate automatic reflex detection and permit the strength of a reflex to be defined in absolute units. The effect of varying the pre-stimulus time, the number of trials averaged and the amount of filtering used on the identification and classification of reflex parameters are also investigated. Furthermore, the effect of noise on these values, and how to remove it, is discussed. The new method, which is an expansion of the CUSUM analysis, is compared and contrasted with the more common threshold-crossing method in two different muscles: masseter and first dorsal interosseous (FDI), in experiments utilizing both mechanical and electrical stimulation. There are a number of advantages to using the new method; not only does the modified CUSUM method detect reflexes earlier than threshold-crossing methods but also the strength and duration are less susceptible to averaging and filtering parameters while giving a better indication of the reflex size. The data suggests that a pre-stimulus analysis period of at least 100 ms be used to correctly identify the variability inherent in EMG traces. It is also concluded that for subtle reflexes, 50 stimuli should be the minimum number used when spike trigger averaging is employed as lower numbers are associated with much greater pre-stimulus variability. Zero-phase filtering the rectified averaged EMG traces is recommended as this makes it easier to identify significant changes in the electrical activity of the muscle in question. In addition, noise estimation and removal from averaged rectified EMG recordings yields results that are a more accurate representation of the synaptic activity of the motor units in question.

Action Potentials↗
PubMed2002

Phase-coupling of theta-gamma EEG rhythms during short-term memory processing.

Because of the importance of oscillations as a general phenomenon of neuronal activity the use of EEG spectral analysis is among the most important approaches for studying human information processing. Usually, oscillations at different frequencies occur simultaneously during information processing. Thus, the question for synchronisation of different frequencies by phase coupling and its possible functional significance is of primary importance. An answer may be given by bispectral analysis. Estimation of the (cross-) bispectrum allows to identify synchronised frequencies and possibly, the existence of non-linear phase coupling of different oscillators. Previous studies have demonstrated the simultaneous occurrence of slow (4-7 Hz) and fast (20-30 Hz) oscillations at frontal and prefrontal electrode positions during memory processing. However, interrelations between these rhythms have not been investigated up to now. In order to test short-term memory, the Sternberg task with random figures and number words was carried out on 10 female subjects. During the task EEG was recorded. Power and bispectral analyses from frontal, prefrontal and frontopolar regions were performed off-line. Increased power was found in both the theta and the gamma bands. Strong phase-coupling between theta at Fz and gamma at F3 and at Fp1, respectively, was shown for memorising number words by means of cross-bicoherence. A possible reason for this is an amplitude modulation of gamma frequencies by slow oscillations. The correspondent coherence analysis between the envelope of gamma frequencies at Fp1 and the raw EEG at Fz supports this presumption. This finding is interpreted as an EEG aspect of the functional linking between the prefrontal areas and the G.cinguli (as part of the limbic system), which are both extremely important for memory functions.

Adult↗
PubMed1999

Preferential and non-preferential transmission of formant information by an analogue cochlear implant using noise: the role of the nerve threshold.

Previous experiments have shown that, in principle, the addition of noise to any vowel coded by an analogue multichannel cochlear implant can enhance the representation of formant information by the temporal pattern of evoked nerve discharges. The optimal addition of noise to some vowel stimuli caused a largely uniform transmission of all input harmonics, including those related to a formant. But for other vowel stimuli, the optimal addition of noise caused preferential transmission of the harmonic closest to a formant compared with other input harmonics. Such preferential transmission may be useful to a cochlear implantee for formant estimation, but the basis of this transmission is unknown. In the present study, the nature of this preferential transmission was investigated with a set of parallel discriminators (or level-crossing detectors) to determine whether the inherent threshold of a nerve fiber was the main cause of the effect. An explicit threshold was found to account for some but not all of the previously observed preferential transmission. Furthermore, many discriminators were required to obtain preferential transmission. Therefore, preferential transmission of a formant-related harmonic may be best achieved by pre-processing a stimulus and using methods associated with stochastic resonance.

Auditory Threshold↗
PubMed1994

Power spectral analysis of fetal heart rate.

This chapter examines the role of power spectral analysis (PSA) in elucidation of the physiological control mechanisms of fetal heart rate and as a potential indicator of fetal well-being. The importance of fetal heart rate variability (FHRV) as an indicator of fetal oxygenation is discussed, and the limitations in the current methods of measurement of FHRV are highlighted. Evidence is presented for the paramount influence of the autonomic nervous system in the control of heart rate variability. The basic proposition underlying spectral analysis is that the two autonomic branches influence heart rate in a frequency-dependent way, and their differential effects can be determined by PSA which breaks down the heart rate trace into its component frequencies. The application of PSA to heart rate variability data is an established tool in cardiology, and the published literature related to its use in the adult, neonate and fetus is reviewed. The power spectrum is sensitive to the activity state of the fetus, particularly fetal breathing movements, which have a variable effect on short- and long-term FHRV. There are a variety of mathematical approaches to the construction of power spectra, and a particular method of data acquisition and analysis is presented together with some theoretical background. Recent experimental evidence indicates a role for PSA as an indicator of fetal activity state, and the effect of hypoxia on the spectrum of the fetus in labour is discussed. There are some problems with the technique of PSA, particularly in regard to accepted definitions and methods of analysis. It is a powerful non-invasive tool in the elucidation of fetal cardiac control, but its value in the detection of the compromised fetus has yet to be tested in a clinical trial.

Adult↗
PubMed2003

Frequency-domain method based on the singular value decomposition for frequency-selective NMR spectroscopy.

In several applications of NMR spectroscopy the user is interested only in the components lying in a small frequency band of the spectrum. A frequency selective analysis deals precisely with this kind of NMR spectroscopy: parameter estimation of only those spectroscopic components that lie in a preselected frequency band of the NMR data spectrum, with as little interference as possible from the out-of-band components and in a computationally efficient way. In this paper we introduce a frequency-domain singular value decomposition (SVD)-based method for frequency selective spectroscopy that is computationally simple, statistically accurate, and which has a firm theoretical basis. To illustrate the good performance of the proposed method we present a number of numerical examples for both simulated and in vitro NMR data.

Algorithms↗
PubMed2002

A wavelet packets decomposition algorithm for quantification of in vivo (1)H-MRS parameters.

In this paper a novel method for the extraction of magnetic resonance spectroscopy (MRS) parameters is presented. The method applies the traditional time-domain linear prediction singular value decomposition (LPSVD) on the set of orthonormal sub-signals obtained by wavelet packets (WP) decomposition of the original free induction decay (FID) signal. Using the properties of WP the desired, optimal, sub-band FID decomposition is obtained and used to progressively separate the different metabolic components in distinct sub-bands. A pseudo-optimal WP tree is obtained using the minimum description length (MDL) criteria. The proposed algorithm preserves all the advantages of the traditional LPSVD method, but the WP decomposition considerably improves the LPSVD performances in the presence of noise. The paper addresses this aspect in details by comparing the innovative sub-band and the traditional full-band approaches. Algorithms are tested on simulated signals that mimic real MRS data.

Algorithms↗
PubMed2003

Determination of the trabecular bone direction from digitised radiographs.

There is increasing evidence for monitoring the bone trabecular structure to explain, in part, the mechanical properties of bone. Despite the emergence of Computed Tomography, a radiograph is the standard format as it is cheap and used for assessing implant performance. Furthermore, various image-processing techniques developed to assess the trabecular structure from radiographs have regained interest owing to improvements in imaging equipment. This study assessed the precision and accuracy of the Co-occurrence and Run-length matrix, Spatial-frequency and Minkowski-fractal techniques to infer the trabecular direction from radiographs. Ten clinical images of femoral neck regions were obtained from digitised pelvic radiographs and subsequently analysed. These data were also used to generate synthetic images where the trabecular thickness, separation and directions were controlled in order to calculate the accuracy of the techniques. Additionally, a Laplacian noise was added in order to infer the precision of the techniques. All methods assessed the trabecular direction with a high degree of accuracy in these synthetic images including a single direction and no noise. However, only the Spatial-frequency and Co-occurrence matrix methods performed well on the clinical and heavily corrupted synthetic images. This demonstrated the possibility of inferring a linear trabecular direction in clinical conditions.

Algorithms↗
PubMed1997

A multivariate time-variant AR method for the analysis of heart rate and arterial blood pressure.

This paper approaches the problem of short-term mechanisms that regulate heart rate and blood pressure variability signals, by focusing the evident changes of their frequency content during transients (dynamic situations in which the behaviour of these control mechanisms may vary on a beat-to-beat basis). In this study, we suggest an autoregressive time-variant spectral estimation method, which is able to follow such dynamic changes in the signals. This method has also been extended to a multivariate approach in order to take into account more than one process at a time, and to assess the mutual influences between the different controlling systems. The algorithms successfully tested on simulated series have also been used to analyse series recorded during a vaso-vagal syncope episode in a tilt manoeuvre and a physical exercise stress test protocol. The results show how this method is able to follow the changing dynamics of the signals on the basis of a closed-loop model of their interaction on a beat-to-beat basis. After a proper identification procedure of the blocks forming the model, it is possible, therefore, to obtain the classical spectral parameters and the gain of the transfer function between the signals. Such parameters constitute new time series that describe the physiopathology of the cardiovascular control systems, even during non-stationary epochs.

Algorithms↗
PubMedDate not supplied

Objective motor response onset detection in surface myoelectric signals.

Precise detection of discrete motor events like the onsets of voluntary muscle contractions is a prerequisite for various psychophysiological approaches in sensorimotor system analysis. In biomedical research and clinical diagnosis, motor events frequently are determined from surface electromyographic (SEMG) signals by some computerized detection algorithm. However, little is known about the reliability and accuracy of these methods, which frequently rely on intuitive and heuristic criteria. Therefore, the systematic approach to computerized detection of discrete motor events from SEMG signals presented by this paper fills a basic gap in EMG signal processing. Based upon a dynamic process model for the SEMG signal, a formal detection scheme is established which incorporates the essential processing modules common to the majority of algorithms. In addition, using concepts of statistically optimal change detection in random processes, a new model-based algorithm is presented which serves as a reference for optimum performance. The validity of this concept is demonstrated for the specific example of accurate detection of muscle activation onsets in rapid voluntary contractions; the estimation error (i.e., the deviation between estimated and "true" onset time) was evaluated by statistical simulations for three representative methods. Results show a substantial decrease of performance of traditional methods in the case of highly variable dynamic muscle activation profiles and/or superimposed activation patterns (e.g., due to a secondary motor task simultaneously executed by the same muscle). The model-based approach provided significantly more accurate results, even when the exact model parameters were unknown but estimated from the SEMG signal actually measured. It is concluded that the detection algorithm has to be critically taken into consideration during interpretation of motor events resolved from SEMG signals. The process model together with the corresponding statistically optimal detector represents an efficient tool for selecting appropriate detection algorithms for a particular experimental condition, and it allows a quantitative assessment of their performance.

Algorithms↗