scispace - formally typeset
Search or ask a question

Showing papers in "IEEE Transactions on Biomedical Engineering in 2000"


Journal ArticleDOI
TL;DR: ICA has been shown to be an efficient tool for artifact identification and extraction from electroencephalographic and magnetoencephalographical recordings and has been applied to the analysis of brain signals evoked by sensory stimuli.
Abstract: Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extraction methods are, therefore, useful to facilitate the representation and interpretation of the data. Recently developed independent component analysis (ICA) has been shown to be an efficient tool for artifact identification and extraction from electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings. In addition, ICA has been applied to the analysis of brain signals evoked by sensory stimuli. This paper reviews our recent results in this field.

789 citations


Journal ArticleDOI
TL;DR: An integrated method for clustering of QRS complexes is presented which includes basis function representation and self-organizing neural networks (NN's) and outperforms both a published supervised learning method as well as a conventional template cross-correlation clustering method.
Abstract: An integrated method for clustering of QRS complexes is presented which includes basis function representation and self-organizing neural networks (NN's). Each QRS complex is decomposed into Hermite basis functions and the resulting coefficients and width parameter are used to represent the complex. By means of this representation, unsupervised self-organizing NNs are employed to cluster the data into 25 groups. Using the MIT-BIH arrhythmia database, the resulting clusters are found to exhibit a very low degree of misclassification (1.5%). The integrated method outperforms, on the MIT-BIH database, both a published supervised learning method as well as a conventional template cross-correlation clustering method.

555 citations


Journal ArticleDOI
TL;DR: Slow-wave microcontinuity, being based on a physiological model of sleep, reflects sleep depth more closely than SWP does, and confirms earlier reports that gender affects SWP but not sleep depth.
Abstract: Increasing depth of sleep corresponds to an increasing gain in the neuronal feedback loops that generate the low-frequency (slow-wave) electroencephalogram (EEG). The authors derived the maximum-likelihood estimator of the feedback gain and applied it to quantify sleep depth. The estimator computes the fraction (0%-100%) of the current slow wave which continues in the near future (0.02 s later) EEG. Therefore, this percentage was dubbed slow-wave microconfinuity (SW%). It is not affected by anatomical parameters such as skull thickness, which can considerably bias the commonly used slow-wave power (SWP). In the authors' study, both of the estimators SW% and SWP were monitored throughout two nights in 22 subjects. Each subject took temazepam (a benzodiazepine) on one of the two nights, Both estimators detected the effects of age, temazepam, and time of night on sleep. Females were found to have twice the SWP of males, but no gender effect on SW% was found. This confirms earlier reports that gender affects SWP but not sleep depth. Subjectively assessed differences in sleep quality between the nights were correlated to differences in SW%, not in SWP. These results demonstrate that slow-wave microcontinuity, being based on a physiological model of sleep, reflects sleep depth more closely than SWP does.

551 citations


Journal ArticleDOI
TL;DR: A wavelet electrocardiogram (ECG) data codec based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed and is significantly more efficient in compression and in computation than previously proposed ECG compression schemes.
Abstract: A wavelet electrocardiogram (ECG) data codec based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm (A. Said and W.A. Pearlman, IEEE Trans. Ccts. Syst. II, vol. 6, p. 243-50, 1996) has achieved notable success in still image coding. The authors modified the algorithm for the one-dimensional case and applied it to compression of ECG data. Experiments on selected records from the MIT-BIH arrhythmia database revealed that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. The coder also attains exact bit rate control and generates a bit stream progressive in quality or rate.

521 citations


Journal ArticleDOI
TL;DR: The emerging technique of independent component analysis, also known as blind source separation, is proposed as an interesting tool for the extraction of the antepartum fetal electrocardiogram from multilead cutaneous potential recordings.
Abstract: We propose the emerging technique of independent component analysis, also known as blind source separation, as an interesting tool for the extraction of the antepartum fetal electrocardiogram from multilead cutaneous potential recordings. The technique is illustrated by means of a real-life example.

487 citations


Journal ArticleDOI
TL;DR: The conductivity of the human skull was measured both in vitro and in vivo, and a ratio of 1:1/15:1 was found, consistent with some of the reports on conductivities found in the literature, but differs considerably from the ratio 1: 1/80:1 commonly used in neural source localization.
Abstract: The conductivity of the human skull was measured both in vitro and in vivo. The in vitro measurement was performed on a sample of fresh skull placed within a saline environment. For the in vivo measurement a small current was passed through the head by means of two electrodes placed on the scalp. The potential distribution thus generated on the scalp was measured in two subjects for two locations of the current injecting electrodes. Both methods revealed a skull conductivity of about 0.015 (1//spl Omega/)/m. For the conductivities of the brain, the skull and the scalp a ratio of 1:1/15:1 was found. This is consistent with some of the reports on conductivities found in the literature, but differs considerably from the ratio 1:1/80:1 commonly used in neural source localization. An explanation is provided for this discrepancy, indicating that the correct ratio is 1:1/15:1.

470 citations


Journal ArticleDOI
TL;DR: A new sensitive microwave life-detection system which can be used to locate human subjects buried earthquake rubble or hidden behind various barriers has been constructed and tested extensively.
Abstract: A new sensitive microwave life-detection which can be used to locate human subjects buried earthquake rubble or hidden behind various barriers has been constructed. This system operating at 1150 MHz or 450 MHz can detect the breathing and heartbeat signals of human subjects through an earthquake rubble or a construction barrier of about 10-ft thickness. The basic physical principle for the operation of a microwave life-detection system is rather simple. When a microwave beam of appropriate frequency (L or S band) is aimed at a pile of earthquake rubble covering a human subject or illuminated through a barrier obstructing a human subject, the microwave beam can penetrate the rubble or the barrier to reach the human subject. When the human subject is illuminated by a microwave beam, the reflected wave from the human subject will be modulated by tile subject's body movements, which include the breathing and the heartbeat. If the clutter consisting of the reflected wave from stationary background can be completely eliminated and the reflected wave from the human subject's body is properly modulated, the breathing and heartbeat signals of the subject can be extracted. Thus, a human subject buried under earthquake rubble or hidden behind barriers can be located. This system has been tested extensively in a simulated earthquake rubble in the laboratory and also in a field test using realistic earthquake rubble conducted by a Federal Emergency Management Agency (FEMA) Task Force.

407 citations


Journal ArticleDOI
TL;DR: The correlation between the proposed WDD measure and the MOS test measure (MOS/sub error/) was found superior to the correlation betweenThe popular PRD measure andThe MOS/ sub error/.
Abstract: In this paper, a new distortion measure for electrocardiogram (ECG) signal compression, called weighted diagnostic distortion (WDD) is introduced. The WDD measure is designed for comparing the distortion between original ECG signal and reconstructed ECG signal (after compression). The WDD is based on PQRST complex diagnostic features (such as P wave duration, QT interval, T shape, ST elevation) of the original ECG signal and the reconstructed one. Unlike other conventional distortion measures [e.g. percentage root mean square (rms) difference, or PRD], the WDD contains direct diagnostic information and thus is more meaningful and useful. Four compression algorithms were implemented (AZTEC, SAPA2, LTP, ASEC) in order to evaluate the WDD. A mean opinion score (MOS) test was applied to test the quality of the reconstructed signals and to compare the quality measure (MOS/sub error/) with the proposed WDD measure and the popular PRD measure. The evaluators in the WIGS test were three independent expert cardiologists, who studied the reconstructed ECG signals in a blind and a semiblind tests. The correlation between the proposed WDD measure and the MOS test measure (MOS/sub error/) was found superior to the correlation between the popular PRD measure and the MOS/sub error/.

393 citations


Journal ArticleDOI
TL;DR: The results support theories that identify psychomotor disturbances as central elements in depression and suicidality.
Abstract: Acoustic properties of speech have previously been identified as possible cues to depression, and there is evidence that certain vocal parameters may be used further to objectively discriminate between depressed and suicidal speech. Studies were performed to analyze and compare the speech acoustics of separate male and female samples comprised of normal individuals and individuals carrying diagnoses of depression and high-risk, near-term suicidality. The female sample consisted of ten control subjects, 17 dysthymic patients, and 21 major depressed patients. The male sample contained 24 control subjects, 21 major depressed patients, and 22 high-risk suicidal patients. Acoustic analyses of voice fundamental frequency (F/sub 0/), amplitude modulation (AM), formants, and power distribution were performed on speech samples extracted from audio recordings collected from the sample members. Multivariate feature and discriminant analyses were performed on feature vectors representing the members of the control and disordered classes. Features derived from the formant and power spectral density measurements were found to be the best discriminators of class membership in both the male and female studies. AM features emerged as strong class discriminators of the male classes. Features describing F/sub 0/ were generally ineffective discriminators in both studies. The results support theories that identify psychomotor disturbances as central elements in depression and suicidality.

391 citations


Journal ArticleDOI
TL;DR: It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets.
Abstract: Introduces nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner-Ville distribution, the Choi-Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.

345 citations


Journal ArticleDOI
TL;DR: This work provides a design for an asynchronous BCI switch and performs the first extensive evaluation of an asynchronous device in attentive, spontaneous electroencephalographic (EEG) testing.
Abstract: Asynchronous control applications are an important class of application that has not received much attention from the brain-computer interface (BCI) community. This work provides a design for an asynchronous BCI switch and performs the first extensive evaluation of an asynchronous device in attentive, spontaneous electroencephalographic (EEG) signals. The switch design [named the low-frequency asynchronous switch design (LF-ASD)] is based on a new feature set related to imaginary movements in the 1-4 Hz frequency range. This new feature set was identified from a unique analysis of EEG using a bi-scale wavelet. Offline evaluations of a prototype switch demonstrated hit (true positive) rates in the range of 38%-81% with corresponding false positive rates in the range of 0.3%-11.6%. The performance of the LF-ASD was contrasted with two other ASDs: one based on mu-power features and another based on the outlier processing method (OPM) algorithm. The minimum mean error rates for the LF-ASD were shown to be significantly lower than either of these other two switch designs.

Journal ArticleDOI
TL;DR: The data and modeling results shows that applying charge to the electrode can consistently reduce the impedance of the electrode-tissue system, and analysis of explanted probes suggests that the interaction between the tissue and electrode is dependent on whether chronic pulses were applied.
Abstract: Experiments were conducted to assess the effect of chronic stimulation on the electrical properties of the electrode-tissue system, as measured using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Silicon, micromachined probes with multiple iridium oxide stimulating electrodes (400-1600 /spl mu/m/sup 2/) were implanted in guinea pig cortex. A 10-17 day post-operative recovery period was followed by five days of monopolar stimulation, two hours/electrode each day using biphasic constant current stimulation (5-100 /spl mu/A, 100 /spl mu/s/phase). EIS and CV data were taken before and after stimulation. The post stimulation impedance [at mid-range frequencies (100 Hz-100 kHz)] consistently and significantly decreased relative to prestimulation levels. Impedance magnitude increased permanently at low frequencies (<100 Hz), correlating to a change in the charge storage capacity (the area under a cyclic voltammagram). Impedance magnitude significantly increased during the recovery period, though this increase could be mostly reversed by applying small currents. A mathematical model of the electrode-tissue system impedance was used to analyze in vivo behavior. The data and modeling results shows that applying charge to the electrode can consistently reduce the impedance of the electrode-tissue system. Analysis of explanted probes suggests that the interaction between the tissue and electrode is dependent on whether chronic pulses were applied. It is hypothesized that the interface between the tissue and metal is altered by current pulsing, resulting in a temporary impedance shift.

Journal ArticleDOI
TL;DR: A dynamic insertion technique has been explored to allow the implantation of high-density probe arrays into feline cortex at high-speed and with minimal traumatic injury.
Abstract: This paper presents a practical microassembly process for three-dimensional (3-D) microelectrode arrays for recording and stimulation in the central nervous system (CNS). Orthogonal lead transfers between the micromachined two-dimensional probes and a cortical surface platform are formed by attaching gold beams on the probes to pads on the platform using wire-free ultrasonic bonding. The low-profile (150 /spl mu/m) outrigger design of the probes allows the bonding of fully assembled high-density arrays. Micromachined assembly tools allow the formation of a full 3-D probe array within 30 min. Arrays having up to 8/spl times/16 shanks on 200-/spl mu/m centers have been realized and used to record cortical single units successfully. Active 3-D probe arrays containing on-chip CMOS signal processing circuitry have also been created using the microassembly approach. In addition, a dynamic insertion technique has been explored to allow the implantation of high-density probe arrays into feline cortex at high-speed and with minimal traumatic injury.

Journal ArticleDOI
TL;DR: The superior detection ability facilitates the collection of a training set under lower SNR than that of the methods which employ simple amplitude thresholding, so that the statistical characteristics of the input vectors can be better represented in the neural-network classifier.
Abstract: Reports a result on neural spike sorting under conditions where the signal-to-noise ratio is very low. The use of nonlinear energy operator enables the detection of an action potential, even when the SNR is so poor that a typical amplitude thresholding method cannot be applied. The superior detection ability facilitates the collection of a training set under lower SNR than that of the methods which employ simple amplitude thresholding. Thus, the statistical characteristics of the input vectors can be better represented in the neural-network classifier The trained neural-network classifiers yield the correct classification ratio higher than 90% when the SNR is as low as 1.2 (0.8 dB) when applied to data obtained from extracellular recording from Aplysia abdominal ganglia using a semiconductor microelectrode array.

Journal ArticleDOI
TL;DR: A method for producing high-resolution chemical patterns on surfaces to control the attachment and growth of cultured neurons and rat hippocampal neurons showed degree of attachment selectivity to the PL and produced neurites that faithfully grew onto the electrode recording sites.
Abstract: We describe a method for producing high-resolution chemical patterns on surfaces to control the attachment and growth of cultured neurons. Microcontact printing has been extended to allow the printing of /spl mu/m-scale protein lines aligned to an underlying pattern of planar microelectrodes. Poly-L-lysine (PL) lines have been printed on the electrode array for electrical studies on cultured neural networks. Rat hippocampal neurons showed degree of attachment selectivity to the PL and produced neurites that faithfully grew onto the electrode recording sites.

Journal ArticleDOI
TL;DR: A wavelet transform-based method to extract the fetal electrocardiogram (ECG) from the composite abdominal signal using the modulus maxima in the wavelet domain, which exploits the most distinct features of the signal, leading to more robustness with respect to signal perturbations.
Abstract: We developed a wavelet transform-based method to extract the fetal electrocardiogram (ECG) from the composite abdominal signal. This is based on the detection of the singularities obtained from the composite abdominal signal, using the modulus maxima in the wavelet domain. Modulus maxima locations of the abdominal signal are used to discriminate between maternal and fetal ECG signals. Two different approaches have been considered, In the first approach, at least one thoracic signal is used as the a prior to perform the classification whereas in the second approach no thoracic signal is needed, A reconstruction method is utilized to obtain the fetal ECG signal from the detected fetal modulus maxima. The proposed technique is different from the classical time-domain methods, in that we exploit the most distinct features of the signal, leading to more robustness with respect to signal perturbations. Results of experiments with both synthetic and real ECG data have been presented to demonstrate the efficacy of the proposed method.

Journal ArticleDOI
TL;DR: The authors conclude that these materials, especially PEG, are adequate for the maintenance of long-term patterned cultures of neurons, and believe that this is the first report of high-quality long- term patterning of cultured neurons.
Abstract: For neurons to attach and remain in precise micropatterns for weeks in culture, background molecules that remain nonpermissive for extended culture durations need to be identified. Nonpermissive background molecules of either polyethylene glycol (PEG) or the amino acid serine (C/sub 3/H/sub 7/NO/sub 3/) were evaluated. The foreground regions were microstamped with 3-, 5-, or 10-/spl mu/m lines of poly-D-lysine (PDL), which promotes neural attachment and growth. After 29 days in culture the foreground compliance, or the fraction of all live somata which rested on the desired PDL surface, averaged 86% for serine and 90% for PEG, with only a small decline. The background compliance, or the fraction of square areas in the pattern background which were free of neurite extension, declined from highs of 40% and 55% (midculture) to 5.5% and 12% (29 days) for serine and PEG, respectively. Images of the cultures suggest that PEG is significantly more effective as a nonpermissive substrate. The authors conclude that these materials, especially PEG, are adequate for the maintenance of long-term patterned cultures of neurons. They believe that this is the first report of high-quality long-term patterning of cultured neurons.

Journal ArticleDOI
TL;DR: The authors introduce a new time domain HRV signal, the Heart Timing (HT) signal, and demonstrate that this HT signal makes it possible to recover an unbiased estimation of the modulating signal spectra.
Abstract: The heart rate variability (HRV) is an extended tool to analyze the mechanisms controlling the cardiovascular system. In this paper, the integral pulse frequency modulation model (IPFM) is assumed. It generates the beat occurrence times from a modulating signal. This signal is thought to represent the autonomic nervous system action, mostly studied in its frequency components. Different spectral estimation methods try to infer the modulating signal characteristics from the available beat timing on the electrocardiogram signal. These methods estimate the spectrum through the heart period (HP) or the heart rate (HR) signal. The authors introduce a new time domain HRV signal, the Heart Timing (HT) signal. They demonstrate that this HT signal, in contrast with the HR or HP, makes it possible to recover an unbiased estimation of the modulating signal spectra. In this estimation the authors avoid the spurious components and the low-pass filtering effect generated when analyzing HR or HP.

Journal ArticleDOI
TL;DR: A very low-power preamplifier intended for use in pasteless-electrode recording of the human electrocardiogram meets the recommendations of the American Heart Association, ensuring low distortion of the output ECG signal and making it suitable for clinical monitoring.
Abstract: This paper describes the development of a very low-power preamplifier intended for use in pasteless-electrode recording of the human electrocardiogram. The expected input signal range is 100 /spl mu/V-10 mV from a lead-II electrode configuration. The amplifier provides a gain of 43 dB in a 3-dB bandwidth of 0.05 Hz-2 kHz with a defined high input impedance of 75 M/spl Omega/. It uses a driven common electrode to enhance rejection of common-mode interfering signals, including low-frequency motion artifact, achieving a common-mode rejection ratio (CMRR) of better than 80 dB over its entire bandwidth. The gain and phase characteristics meet the recommendations of the American Heart Association, ensuring low distortion of the output ECG signal and making it suitable for clinical monitoring. The amplifier has a power consumption of 30 /spl mu/W operating from a 3.3-V battery and is intended for use in small, lightweight, portable electrocardiographic equipment and heart-rate monitoring instrumentation.

Journal ArticleDOI
TL;DR: The degree of tissue-segmentation for whole-body models was found to have a minimal effect on calculated azimuthal radiation patterns and bodyworn radiation efficiency, provided the region surrounding the implanted source was sufficiently detailed.
Abstract: Tissue-implanted ultra-high frequency (UHF) radio devices are being employed in both humans and animals for telemetry and telecommand applications. This paper describes the experimental measurement and electromagnetic modeling of propagation from 418-MHz and 916.5-MHz sources placed in the human vagina. Whole-body homogeneous and semi-segmented software models were constructed using data from the Visible Human Project. Bodyworn radiation efficiencies for a vaginally placed 418-MHz source were calculated using finite-difference time-domain and ranged between 1.6% and 3.4% (corresponding to net body losses of between 14.7 and 18.0 dB). Greater losses were encountered at 916.5 MHz, with efficiencies between 0.36% and 0.46% (net body loss ranging between 23.4 and 24.4 dB). Practical measurements mere in good agreement with simulations, to within 2 dB at 418 MHz and 3 dB at 916.5 MHz. The degree of tissue-segmentation for whole-body models was found to have a minimal effect on calculated azimuthal radiation patterns and bodyworn radiation efficiency, provided the region surrounding the implanted source was sufficiently detailed.

Journal ArticleDOI
TL;DR: An electrocardiogram (ECG) compression algorithm, called analysis by synthesis ECG compressor (ASEC), is introduced and was found to be superior to several well-known ECG compression algorithms at all tested bit rates.
Abstract: An electrocardiogram (ECG) compression algorithm, called analysis by synthesis ECG compressor (ASEC), is introduced. The ASEC algorithm is based on analysis by synthesis coding, and consists of a beat codebook, long and short-term predictors, and an adaptive residual quantizer. The compression algorithm uses a defined distortion measure in order to efficiently encode every heartbeat, with minimum bit rate, while maintaining a predetermined distortion level. The compression algorithm was implemented and tested with both the percentage rms difference (PRD) measure and the recently introduced weighted diagnostic distortion (WDD) measure. The compression algorithm has been evaluated with the MIT-BIH Arrhythmia Database. A mean compression rate of approximately 100 bits/s (compression ratio of about 30:1) has been achieved with a good reconstructed signal quality (WDD below 4% and PRD below 8%). The ASEC was compared with several well-known ECG compression algorithms and was found to be superior at all tested bit rates. A mean opinion score (MOS) test was also applied. The testers were three independent expert cardiologists. As In the quantitative test, the proposed compression algorithm was found to be superior to the other tested compression algorithms.

Journal ArticleDOI
TL;DR: The proposed technique, based on surface electrode array recording, is useful for the diagnosis of neuromuscular disorders, for the monitoring of muscle fatigue and for noninvasive investigation of individual motor units.
Abstract: Determining the conduction velocity of motor unit action potentials is one of the most important problems in surface electromyography. The estimate of one average conduction velocity value depends on a variety of uncontrollable factors. More meaningful information is obtained from the estimation of the distribution of the different delays in the myoelectric signals. A solution to the problem is the separation and characterization of the individual components propagating at different velocities. A technique, based on surface electrode array recording, is proposed to estimate motor unit conduction velocity distribution. The method consists in the identification of the single action potentials in the time scale domain (with the continuous wavelet transform) and in the estimation of their conduction velocities based on the beamforming algorithm. The performances of the technique have been evaluated using simulated and real myoelectric signals. The results demonstrate that the technique Is accurate and reliable. The method may be useful for the diagnosis of neuromuscular disorders, for the monitoring of muscle fatigue and for noninvasive investigation of individual motor units.

Journal ArticleDOI
TL;DR: Using the probe in recording from rat's somatosensory cortex, the authors obtained four channel simultaneous recordings which showed clear independence among channels with a signal-to-noise ratio performance comparable with that obtained using other devices.
Abstract: A process of making a new type of silicon depth-probe microelectrode array is described using a combination of plasma and wet etch. The plasma etch, which is done using a low temperature oxide (LTO) mask, enables probe thickness to be controlled over a range from 5 to 90 /spl mu/. Bending tests show that the probe's mechanical strength depends largely on shank thickness. More force can he applied to thicker shanks while thinner shanks are more flexible. One can then choose a thickness and corresponding mechanical strength using the process developed. The entire probe shaping process is performed only at low temperature, and thus is consistent with the standard CMOS fabrication. Using the probe in recording from rat's somatosensory cortex, the authors obtained four channel simultaneous recordings which showed clear independence among channels with a signal-to-noise ratio performance comparable with that obtained using other devices.

Journal ArticleDOI
TL;DR: The updating of preoperative images using the model calculations is presented and demonstrates that model-updated image-guided neurosurgery may be a viable option for addressing registration errors related to intraoperative tissue motion.
Abstract: Clinicians using image-guidance for neurosurgical procedures have recently recognized that intraoperative deformation from surgical loading can compromise the accuracy of patient registration in the operating room. While whole brain intraoperative imaging is conceptually appealing it presents significant practical limitations. Alternatively, a promising approach may be to combine incomplete intraoperatively acquired data with a computational model of brain deformation to update high resolution preoperative images during surgery. The success of such an approach is critically dependent on identifying a valid model of brain deformation physics. Towards this end, the authors evaluate a three-dimensional finite element consolidation theory model for predicting brain deformation in vivo through a series of controlled repeat-experiments. This database is used to construct an interstitial pressure boundary condition calibration curve which is prospectively tested in a fourth validation experiment. The computational model is found to recover 75%-85% of brain motion occurring under loads comparable to clinical conditions. Additionally, the updating of preoperative images using the model calculations is presented and demonstrates that model-updated image-guided neurosurgery may be a viable option for addressing registration errors related to intraoperative tissue motion.

Journal ArticleDOI
TL;DR: The authors show that under specific circumstances this algorithm solves the sufficiency condition for signal reconstruction in linear saturation estimators.
Abstract: Describes a noise-resistant pulse oximetry algorithm suited to both signal reconstruction and oxygen saturation estimation. The algorithm first detects relatively clean signal sections from which the heart rate is estimated. The heart rate is used to construct a synthetic reference signal that matches an idealized pulse signal. An adaptive filter continuously processes the sensor signals, reconstructing signals in a linear subspace defined by the reference signal. A projective subspace algorithm is then applied to find the oxygenation level of the blood. The authors show that under specific circumstances this algorithm solves the sufficiency condition for signal reconstruction in linear saturation estimators. The core principle of using a frequency modulated synthetic reference signal can be applied to adaptive filtering of other physiological signals controlled by the heartbeat, such as blood pressure and electrocardiogram.

Journal ArticleDOI
TL;DR: The performance of two methods for selecting the corner in the L-curve approach to Tikhonov regularization is evaluated via computer simulation, and it is shown that both resulted in significantly better regularization parameters than that obtained with an often-used empirical Composite REsidual and Smoothing Operator approach.
Abstract: The performance of two methods for selecting the corner in the L-curve approach to Tikhonov regularization is evaluated via computer simulation. These methods are selecting the corner as the point of maximum curvature in the L-curve, and selecting it as the point where the product of abcissa and ordinate is a minimum. It is shown that both these methods resulted in significantly better regularization parameters than that obtained with an often-used empirical Composite REsidual and Smoothing Operator approach, particularly in conditions where correlated geometry noise exceeds Gaussian measurement noise. It is also shown that the regularization parameter that results with the minimum-product method is identical to that selected with another empirical zero-crossing approach proposed earlier.

Journal ArticleDOI
TL;DR: The authors develop a method for estimating regional head tissue conductivities in vivo, by injecting small electric currents into the scalp, and measuring the potentials at the remaining electrodes of a dense-array electroencephalography net, which is robust to the noise levels expected in practice.
Abstract: The authors develop a method for estimating regional head tissue conductivities in vivo, by injecting small (1-10 /spl mu/A) electric currents into the scalp, and measuring the potentials at the remaining electrodes of a dense-array electroencephalography net. They first derive analytic expressions for the potentials generated by scalp current injection In a four-sphere model of the human head. They then use a multistart downhill simplex algorithm to find regional tissue conductivities which minimize the error between measured and computed scalp potentials. Two error functions are studied, with similar results. The results show that, despite the low skull conductivity and expected shunting by the scalp, all four regional conductivities can be determined to within a few percent error. The method is robust to the noise levels expected in practice. To obtain accurate results the cerebrospinal fluid must be included In the forward solution, but may be treated as a known parameter in the inverse solution.

Journal ArticleDOI
TL;DR: A blind source separation algorithm using only second-order temporal correlations for cleaning biomagnetic measurements of evoked responses in the peripheral nervous system is proposed and shows its efficiency by eliminating disturbances originating from biological and technical noise sources and successfully extracting the signal of interest.
Abstract: Artifacts in magnetoneurography data due to endogenous biological noise sources, like the cardiac signal, can be four orders of magnitude higher than the signal of interest. Therefore, it is important to establish effective artifact reduction methods. We propose a blind source separation algorithm using only second-order temporal correlations for cleaning biomagnetic measurements of evoked responses in the peripheral nervous system. The algorithm showed its efficiency by eliminating disturbances originating from biological and technical noise sources and successfully extracting the signal of interest. This yields a significant improvement of the neuro-magnetic source analysis.

Journal ArticleDOI
TL;DR: The proposed method of VAG signal analysis is independent of joint angle and clinical information, and shows good potential for noninvasive diagnosis and monitoring of patellofemoral disorders such as chondromalacia patella.
Abstract: Vibroarthrographic (VAG) signals emitted by human knee joints are nonstationary and multicomponent in nature; time-frequency distributions (TFD's) provide powerful means to analyze such signals. The objective of this paper is to construct adaptive TFD's of VAG signals suitable for feature extraction. An adaptive TFD was constructed by minimum cross-entropy optimization of the TFD obtained by the matching pursuit decomposition algorithm. Parameters of VAG signals such as energy, energy spread. frequency, and frequency spread were extracted from their adaptive TFD's. The parameters carry information about the combined TF dynamics of the signals. The mean and standard deviation of the parameters were computed, and each VAG signal was represented by a set of just six features. Statistical pattern classification experiments based on logistic regression analysis of the parameters showed an overall normal/abnormal screening accuracy of 68.9% with 90 VAG signals (51 normals and 39 abnormals), and a higher accuracy of 77.5% with a database of 71 signals with 51 normals and 20 abnormals of a specific type of patellofemoral disorder. The proposed method of VAG signal analysis is independent of joint angle and clinical information, and shows good potential for noninvasive diagnosis and monitoring of patellofemoral disorders such as chondromalacia patella.

Journal ArticleDOI
TL;DR: A broader, second-order model of high-frequency electric fields effects on cells and their membranes is proposed, which shows that above 10 MHz, the membrane field amplification stops decreasing and levels off again in the range of tens (high-frequency plateau).
Abstract: With biological cells exposed to ac electric fields below 100 kHz, external field is amplified in the cell membrane by a factor of several thousands (low-frequency plateau), while above 100 kHz, this amplification gradually decreases with frequency. Below 10 MHz, this situation is well described by the established first-order theory which treats the cytoplasm and the external medium as pure conductors. At higher frequencies, capacitive properties of the cytoplasm and the external medium become increasingly important and thus must be accounted for. This leads to a broader, second-order model, which is treated in detail in this paper. Unlike the first-order model, this model shows that above 10 MHz, the membrane field amplification stops decreasing and levels off again in the range of tens (high-frequency plateau). Existence of the high-frequency plateau could have an important impact on present theories of high-frequency electric fields effects on cells and their membranes.