A system for tracking changes in the mid-latency evoked potential during anesthesia.

This paper describes a method to measure changes in the mid-latency auditory evoked potential (MLAEP) during anesthesia. It is claimed that the position of the Nb-trough of the MLAEP indicates the level of consciousness. The component shows graded changes corresponding to the dose of anesthetic and it exhibits stable reproducible properties between different subjects. We propose a system that reduces the disturbances in an averaged MLAEP using fewer realizations than in the standard averaging procedure. The resulting smoothing error is reduced if the number of stimulus is decreased. Unfortunately, the variance of the waveform estimate is, thereby, increased. An improved method must be used in order to estimate the Nb-trough within a prescribed time interval of one minute. The procedure is based on inherent properties of the MLAEP and the noise. A simulation and examples of the performance on real data recorded during surgery are shown.

Categorization of interictal epileptiform potentials using a graph-theoretic method.

OBJECTIVES: In patients with epileptic seizures, localization of the source of interictal epileptiform activity is of interest. For correct source localization, a favorable signal to noise ratio is important, and to achieve this, averaging of several epileptiform potentials is often necessary. Before averaging, a careful categorization of epileptiform potentials with different potential distributions is crucial. The aim of this study was to investigate whether a a hierarchic, graph-theoretic algorithm could be used for this categorization. METHODS: In 4 patients, 50-100 sharp waves with different surface distributions were categorized independently with the algorithm, and by visual inspection of the traces. As an independent evaluation of the algorithm, a dipole reconstruction was performed for each sharp wave, and the dipole results for the sharp waves from the different automatically obtained categories were compared. RESULTS: All patients showed a high degree of correspondence between the results of the automatic analysis and the visual estimation. There were clear differences in dipole results between the sharp waves of the different categories obtained from the automatic categorization. CONCLUSION: The results indicate that the graph-theoretic categorization algorithm provides a reliable clustering of interictal epileptiform potentials, and that the method may become a useful tool in the pre-averaging categorization of interictal epileptiform potentials prior to source localization.

Image enhancement based on a nonlinear multiscale method.

An image enhancement method that reduces speckle noise and preserves edges is introduced. The method is based on a new nonlinear multiscale reconstruction scheme that is obtained by successively combining each coarser scale image with the corresponding modified interscale image. Simulation results are included to demonstrate the performance of the proposed method.

Feature extraction and clustering of EEG epileptic spikes.

This paper treats algorithms for feature extraction and clustering of multichannel EEG transients occurring in epilepsy, so called spikes. Hermite functions with a variable width parameter is used as features. We study nonlinear optimization of a series expansion for multichannel spikes. For the clustering problem, the nearest mean (NM) algorithm, generalized to matrix features, is used. The number of classes is assumed to be known a priori. The series expansion gives good signal description while reducing information. A simulation to estimate the space resolution capability of the algorithms indicates that perfect clustering requires approximately one head radius distance between the dipoles, which each generate one cluster. The NM algorithm was used to cluster two sets of clinically recorded spikes, and the clustering was compared to the manual clustering obtained by a neurophysiologist. For both spike sets evaluated, the clusters obtained by the algorithms had high accordance with the result of the neurophysiologist.

Estimation of single event-related potentials utilizing the Prony method.

This paper deals with estimation of the waveform of a single event-related potential, sERP. An additive noise model is used for the measured signal and the SNR of the disturbed sERP is approximately 0 dB. The sERP is described by a series expansion where the basis functions are damped sinusoids. The fundamental basis function is estimated by the least squares Prony method, derived for colored noise. The performance of the Prony method for different forms of the power density spectrum of the noise is investigated. A white noise approximation can be used at a low signal-to-noise (SNR). The basis functions change slowly but the waveform of the sERP may vary from one stimulus to another, thus we average a small number of correlation functions in order to increase the SNR. The method is evaluated by using measurements from four subjects and the results confirm the variability of the sERP.

Weighted least-squares pulse-shaping filters with application to ultrasonic signals.

The resolution of adjacent surfaces in medical ultrasonic imaging depends on the duration of a reflected echo. By shaping the excitation signal of the transducer, this duration can be decreased. The authors present a method for effective calculation of the excitation pulse by introducing a weighting function that defines the resolution. A class of filter is obtained that includes the least-mean-squares filter, the pure inverse filter, and the matched filter. The method is demonstrated in an application that increases the resolution of an ultrasonic transducer.

Frequency- and depth-dependent compensation of ultrasonic signals.

The resolution in ultrasonic images decreases with depth when using traditional time-gain compensation (TGC) of the received signal. To reduce this effect, both frequency-dependent and depth-dependent compensation is introduced. A time-varying digital filtering method is presented for this purpose, which is based on Wiener filtering. Images obtained from a simulated tissue equivalent are presented and the frequency-compensated images are compared to conventional TGC-compensated images. It is shown that the improvement in resolution using frequency-dependent compensation is considerable when the signal-to-noise ratio in the received signal is high.

Optimization of the lateral resolution of a transducer.

This paper deals with the problem of optimizing the lateral resolution with respect to the velocity distribution of the transducer surface. In order to determine the acoustic field, the transducer is divided into circular annuli with a predetermined shape of the velocity distribution. The acoustic field from the transducer is a weighted sum of the fields from the annuli. The lateral resolution is optimized with respect to these weights. Examples are given to illustrate the method.

Analysis of a system for ultrasonic imaging of attenuation and texture in soft tissue.

Attenuation in tissue decreases both the amplitude and the bandwidth of a reflected ultrasonic signal. Only the amplitude is restored in conventional ultrasonic equipment by amplifying the signal in a time-gain-compensator. This paper describes a method for restoring both the amplitude and bandwidth of the signal and an implemention of this method is proposed. This consists of two main parts: a device for estimating the attenuation and a time-variable circuit. The time-variable circuit is controlled by the estimated attenuation such that its transfer function approximates the inverse of the transfer function of the attenuation within the transducer passband. Its output is then almost independent of the attenuation and contains information on the texture of the tissue. Both the texture and attenuation estimates are displayed graphically. The quality of the image of the texture can be improved by choosing a wideband transducer, since it is almost exclusively dependent of transducer bandwidth.

Estimation of varying ultrasonic attenuation.

This paper aims to investigate a method of estimating the attenuation and its variation. It is treated as an estimation problem by using modelling techniques known from communication theory. The model includes magnitude and position of specular echoes, a random description of echoes from diffuse reflectors, and a parametric characterization of attenuation. By processing the observed signal only in the time domain, low complexity calculation algorithms are achieved. Results obtained using simulated data indicate that the method works well on both broad-band and narrow-band signals.