Showing papers in "Medical & Biological Engineering & Computing in 2004"

Emotion recognition system using short-term monitoring of physiological signals.

Abstract: A physiological signal-based emotion recognition system is reported. The system was developed to operate as a user-independent system, based on physiological signal databases obtained from multiple subjects. The input signals were electrocardiogram, skin temperature variation and electrodermal activity, all of which were acquired without much discomfort from the body surface, and can reflect the influence of emotion on the autonomic nervous system. The system consisted of preprocessing, feature extraction and pattern classification stages. Preprocessing and feature extraction methods were devised so that emotion-specific characteristics could be extracted from short-segment signals. Although the features were carefully extracted, their distribution formed a classification problem, with large overlap among clusters and large variance within clusters. A support vector machine was adopted as a pattern classifier to resolve this difficulty. Correct-classification ratios for 50 subjects were 78.4% and 61.8%, for the recognition of three and four categories, respectively.

Classification of basic daily movements using a triaxial accelerometer.

Abstract: A generic framework for the automated classification of human movements using an accelerometry monitoring system is introduced. The framework was structured around a binary decision tree in which movements were divided into classes and subclasses at different hierarchical levels. General distinctions between movements were applied in the top levels, and successively more detailed subclassifications were made in the lower levels of the tree. The structure was modular and flexible: parts of the tree could be reordered, pruned or extended, without the remainder of the tree being affected. This framework was used to develop a classifier to identify basic movements from the signals obtained from a single, waist-mounted triaxial accelerometer. The movements were first divided into activity and rest. The activities were classified as falls, walking, transition between postural orientations, or other movement. The postural orientations during rest were classified as sitting, standing or lying. In controlled laboratory studies in which 26 normal, healthy subjects carried out a set of basic movements, the sensitivity of every classification exceeded 87%, and the specificity exceeded 94%; the overall accuracy of the system, measured as the number of correct classifications across all levels of the hierarchy, was a sensitivity of 97.7% and a specificity of 98.7% over a data set of 1309 movements.

Removal of ocular artifacts from electro-encephalogram by adaptive filtering

Abstract: The electro-encephalogram (EEG) is useful for clinical diagnosts and in biomedical research. EEG signals, however, especially those recorded from frontal channels, often contain strong electro-oculogram (EOG) artifacts produced by eye movements. Existing regression-based methods for removing EOG artifacts require various procedures for preprocessing and calibration that are inconvenient and timeconsuming. The paper describes a method for removing ocular artifacts based on adaptive filtering. The method uses separately recorded vertical EOG and horizontal EOG signals as two reference inputs. Each reference input is first processed by a finite impulse response filter of length M (M=3 in this application) and then subtracted from the original EEG. The method is implemented by a recursive leastsquares algorithm that includes a forgetting factor (λ=0.9999 in this application) to track the non-stationary portion of the EOG signals. Results from experimental data demonstrate that the method is easy to implement and stable, converges fast and is suitable for on-line removal of EOG artifacts. The first three coefficients (up to M=3) were significantly larger than any remaining coefficients.

Nerve conduction block utilising high-frequency alternating current.

Abstract: High-frequency alternating current (AC) waveforms have been shown to produce a quickly reversible nerve block in animal models, but the parameters and mechanism of this block are not well understood. A frog sciatic nerve/gastrocnemius muscle preparation was used to examine the parameters for nerve conduction block in vivo, and a computer simulation of the nerve membrane was used to identify the mechanism for block. The results indicated that a 100% block of motor activity can be accomplished with a variety of waveform parameters, including sinusoidal and rectangular waveforms at frequencies from 2 kHz to 20 kHz. A complete and reversible block was achieved in 34 out of 34 nerve preparations tested. The most efficient waveform for conduction block was a 3-5 kHz constant-current biphasic sinusoid, where block could be achieved with stimulus levels as low as 0.01 microCphase(-1). It was demonstrated that the block was not produced indirectly through fatigue. Computer simulation of high-frequency AC demonstrated a steady-state depolarisation of the nerve membrane, and it is hypothesised that the conduction block was due to this tonic depolarisation. The precise relationship between the steady-state depolarisation and the conduction block requires further analysis. The results of this study demonstrated that high-frequency AC can be used to produce a fast-acting, and quickly reversible nerve conduction block that may have multiple applications in the treatment of unwanted neural activity.

Mechanotransduction of bone cells in vitro: mechanobiology of bone tissue.

Abstract: Mechanical force plays an important role in the regulation of bone remodelling in intact bone and bone repair. In vitro, bone cells demonstrate a high responsiveness to mechanical stimuli. Much debate exists regarding the critical components in the load profile and whether different components, such as fluid shear, tension or compression, can influence cells in differing ways. During dynamic loading of intact bone, fluid is pressed through the osteocyte canaliculi, and it has been demonstrated that fluid shear stress stimulates osteocytes to produce signalling molecules. It is less clear how mechanical loads act on mature osteoblasts present on the surface of cancellous or trabecular bone. Although tissue strain and fluid shear stress both cause cell deformation, these stimuli could excite different signalling pathways. This is confirmed by our experimental findings, in human bone cells, that strain applied through the substrate and fluid flow stimulate the release of signalling molecules to varying extents. Nitric oxide and prostaglandin E2 values increased by between two- and nine-fold after treatment with pulsating fluid flow (0.6±0.3 Pa). Cyclic strain (1000 μstrain) stimulated the release of nitric oxide two-fold, but had no effect on prostaglandin E2. Furthermore, substrate strains enhanced the bone matrix protein collagen I two-fold, whereas fluid shear caused a 50% reduction in collagen I. The relevance of these variations is discussed in relation to bone growth and remodelling. In applications such as tissue engineering, both stimuli offer possibilities for enhancing bone cell growth in vitro.

Feature selection of stabilometric parameters based on principal component analysis.

Abstract: This study addresses the challenge of identifying the features of the Centre of pressure (COP) trajectory that are most sensitive to postural performance, with the aim of avoiding redundancy and allowing a straightforward interpretation of the results. Postural sway in 50 young, healthy subjects was measured by a force platform. Thirty-seven stabilometric parameters were computed from the one-dimensional and two-dimensional COP time series. After normalisation to the relevant biomechanical factors, by means of multiple regression models, a feature selection process was performed based on principal component analysis. Results suggest that COP two-dimensional time series can be primarily characterised by four parameters, describing the size of the COP path over the support surface; the principal sway direction; and the shape and bandwidth of the power spectral density plot. COP one-dimensional time series (antero-posterior (AP) and medio-lateral (ML)) can be characterised by six parameters describing COP dispersion along the AP direction; mean velocity along the ML and AP directions; the contrast between ML and AP regulatory activity; and two parameters describing the spectral characteristics of the COP along the AP direction. On the basis of the results obtained, some guidelines are suggested for the choice of stabilometric parameters to use, with the aim of promoting standardisation in quantitative posturography.

Classification of cardiac abnormalities using heart rate signals.

Abstract: The heart rate is a non-stationary signal, and its variation can contain indicators of current disease or warnings about impending cardiac diseases. The indicators can be present at all times or can occur at random, during certain intervals of the day. However, to study and pinpoint abnormalities in large quantities of data collected over several hours is strenuous and time consuming. Hence, heart rate variation measurement (instantaneous heart rate against time) has become a popular, non-invasive tool for assessing the autonomic nervous system. Computer-based analytical tools for the in-depth study and classification of data over day-long intervals can be very useful in diagnostics. The paper deals with the classification of cardiac rhythms using an artificial neural network and fuzzy relationships. The results indicate a high level of efficacy of the tools used, with an accuracy level of 80-85%.

Methods for estimating muscle fibre conduction velocity from surface electromyographic signals.

Abstract: The review focuses on the methods currently available for estimating muscle fibre conduction velocity (CV) from surface electromyographic (EMG) signals. The basic concepts behind the issue of estimating CV from EMG signals are discussed. As the action potentials detected at the skin surface along the muscle fibres are, in practice, not equal in shape, the estimation of the delay of propagation (and thus of CV) is not a trivial task. Indeed, a strictly unique definition of delay does not apply in these cases. Methods for estimating CV can thus be seen as corresponding to specific definitions of the delay of propagation between signals of unequal shape. The most commonly used methods for CV estimation are then reviewed. Together with classic methods, recent approaches are presented. The techniques are described with common notations to underline their relationships and to highlight when an approach is a generalisation of a previous one or when it is based on new concepts. The review identifies the difficulties of CV estimation and underlines the issues that should be considered by the investigator when selecting a particular method and detection system for assessing muscle fibre CV. The many open issues in CV estimation are also presented.

Correlation-based decomposition of surface electromyograms at low contraction forces.

Abstract: The paper studies a surface electromyogram (SEMG) decomposition technique suitable for identification of complete motor unit (MU) firing patterns and their motor unit action potentials (MUAPs) during low-level isometric voluntary muscle contractions. The algorithm was based on a correlation matrix of measurements, assumed unsynchronised (uncorrelated) MU firings, exhibited a very low computational complexity and resolved the superimposition of MUAPs. A separation index was defined that identified the time instants of an MU's activation and was eventually used for reconstruction of a complete MU innervation pulse train. In contrast with other decomposition techniques, the proposed approach worked well also when the number of active MUs was slightly underestimated, if the MU firing patterns partly overlapped and if the measurements were noisy. The results on synthetic SEMG show 100% accuracy in the detection of innervation pulses down to a signal-to-noise ratio (SNR) of 10 dB, and 93±4.6% (mean± standard deviation) accuracy with 0 dB additive noise. In the case of real SEMG, recorded with an array of 61 electrodes from biceps brachii of five subjects at 10% maximum voluntary contraction, seven active MUs with a mean firing rate of 14.1 Hz were identified on average.

Combined compression and elongation experiments and non-linear modelling of liver tissue for surgical simulation.

Abstract: Uniaxial stress-strain data were obtained from in vitro experiments on 20 porcine livers for compressions, elongations and cycles of compression and then elongation. There were about 70 cylindrical samples, with diameter 7 mm and varying height (4–11 mm). The combined compression and elongation test provide a unified framework for both compression and elongation for applications such as computer-aided surgical simulation. It enable the zero stress state of the experimental liver sample to be precisely determined. A new equation that combined both logarithmic and polynomial strain energy forms was proposed in modelling these experimental data. The assumption of incompressibility was justified from a preliminary Poisson's ratio for elongation and compression at 0.43±0.16 and 0.47±0.15, respectively. This equation provided a good fit for the observed mechanical properties of liver during compression-elongation cycles and for separate compressions or elongations. The root mean square errors were 91.92±17.43 Pa, 57.55±13.23 Pa and 29.78±17.67 Pa, respectively. In comparison with existing strain energy functions, this combined model was the better constitutive equation. Application of this theoretical model to small liver samples and other tissues demonstrated its suitability as the material model of choice for soft tissue.

Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis.

Abstract: Fast changes, in the range of milliseconds, in the optical properties of cerebral tissue are associated with brain activity and can be detected using non-invasive near-infrared spectroscopy (NIRS). These changes are assumed to be caused by changes in the light scattering properties of the neuronal tissue. The aim of this study was to develop highly sensitive data analysis algorithms to detect this fast signal, which is small compared with other physiological signals. A frequency-domain tissue oximeter, whose laser diodes were intensity modulated at 110 MHz, was used. The amplitude, mean intensity and phase of the modulated optical signal were measured at a sample rate of 96 Hz. The probe, consisting of four crossed source detector pairs was placed above the motor cortex, contralateral to the hand performing a tapping exercise consisting of alternating rest and tapping periods of 20 s each. An adaptive filter was used to remove the arterial pulsatility from the optical signals. Independent component analysis allowed further separation of a signal component containing the fast signal. In nine out of 14 subjects, a significant fast neuronal signal related to the finger tapping was found in the intensity signals. In the phase signals, indications of the fast signal were found in only two subjects.

Reduction of false arterial blood pressure alarms using signal quality assessment and relationships between the electrocardiogram and arterial blood pressure.

Abstract: The paper presents an algorithm for reducing false alarms related to changes in arterial blood pressure (ABP) in intensive care unit (ICU) monitoring. The algorithm assesses the ABP signal quality, analyses the relationship between the electrocardiogram and ABP using a fuzzy logic approach and post-processes (accepts or rejects) ABP alarms produced by a commercial monitor. The algorithm was developed and evaluated using unrelated sets of data from the MIMIC database. By rejecting 98.2% (159 of 162) of the false ABP alarms produced by the monitor using the test set of data, the algorithm was able to reduce the false ABP alarm rate from 26.8% to 0.5% of ABP alarms, while accepting 99.8% (441 of 442) of true ABP alarms. The results show that the algorithm is effective and practical, and its use in future patient monitoring systems is feasible.

Identification of the breast boundary in mammograms using active contour models.

Abstract: A method for the identification of the breast boundary in mammograms is presented. The method can be used in the preprocessing stage of a system for computer-aided diagnosis (CAD) of breast cancer and also in the reduction of image file size in picture archiving and communication system applications. The method started with modification of the contrast of the original image. A binarisation procedure was then applied to the image, and the chain-code algorithm was used to find an approximate breast contour. Finally, the identification of the true breast boundary was performed by using the approximate contour as the input to an active contour model algorithm specially tailored for this purpose. After demarcation of the breast boundary, all artifacts outside the breast region were eliminated. The method was applied to 84 medio-lateral oblique mammograms from the Mini-MIAS database. Evaluation of the detected breast boundary was performed based upon the percentage of false-positive and false-negative pixels determined by a quantitative comparison between the contours identified by a radiologist and those identified by the proposed method. The average false positive and false negative rates were 0.41% and 0.58%, respectively. The two radiologists who evaluated the results considered the segmentation results to be acceptable for CAD purposes.

Multiple-electrode nerve cuffs for low-velocity and velocity-selective neural recording.

Abstract: In the paper, a method using multiple-electrode nerve cuffs is presented that enables electroneurographic signals (ENG) to be recorded selectively by action potential velocity. The theory uses a one-dimensional model of the electrodes in the cuff. Using this model, the transfer function for a single tripole is derived, and it is shown that more than one tripole signal can be recorded from within a cuff. When many tripole signals are available and are temporally aligned by artificial delays and summed, there is a significant increase in the amplitude of the recorded action potential, depending on the cuff length and the action potential velocity, with the greatest gain occurring for low velocities. For example, a cuff was considered that was constrained by surgical considerations to 30 mm between the end electrodes. For action potentials with a velocity of 120 ms−1, it was shown that, as the number of tripoles increased from one, the peak energy spectral density of the recorded output increased by a factor of about 1.6 with three tripoles, whereas, for 20 ms−1, the increase was about 19, with ten tripoles. The time delays and summation act as a velocity-selective filter. With consideration of the energy spectral densities at frequencies where are maximum (to give the best signal-to-noise ratio), the tuning curves are presented for these velocity-selective filters and show that useful velocity resolution is possible using this method. For a 30 mm cuff with nine tripoles, it is demonstrated that it is possible to resolve at least five distinct velocity bands in the range 20–120 ms−1.

Patient-specific mechanical properties of a flexible multi-body model of the scoliotic spine.

Abstract: The flexibility of the scoliotic spine is an important biomechanical parameter to take into account in the planning of surgical instrumentation. The objective of the paper was to develop a method to characterise in vivo the mechanical properties of the scoliotic spine using a flexible multi-body model. Vertebrae were represented as rigid bodies, and intervertebral elements were defined at every level using a spherical joint and three torsion springs. The initial mechanical properties of motion segments were defined from in vitro experimental data reported in the literature. They were adjusted using an optimisation algorithm to reduce the discrepancy between the simulated and the measured Ferguson angles in lateral bending of three spine segments (major or compensatory left thoracic, right thoracic and left lumbar scoliosis curves). The flexural rigidity of the spine segments was defined in three categories (flexible, nominal, rigid) according to the estimated mechanical factors (alpha). This approach was applied with ten scoliotic patients undergoing spinal correction. Personalisation of the model resulted in an increase of the initial flexural rigidity for seven of the ten lumbar segments (1.38 < or = alpha < or = 10.0) and four of the ten right thoracic segments (1.74 < or = alpha < or = 5.18). The adjustment of the mechanical parameters based on the lateral bending tests improved the model's ability to predict the spine shape change described by the Ferguson angles by up to 50%. The largest differences after personalisation were for the left lumbar segments in left bending (4 degrees +/- 3 degrees). The in vivo identification of the mechanical properties of the scoliotic spine will improve the ability of biomechanical models adequately to predict the surgical correction, which should help clinicians in the planning of surgical instrumentation manoeuvres.

Reducing power line interference in digitised electromyogram recordings by spectrum interpolation.

Abstract: Interference from power lines (50 or 60 Hz) is the largest source of extraneous noise in many bio-electric signals and is within the bandwidth of many such signals. In this study, two different methods were compared for their efficacy in removing 50 Hz noise added to surface electromyogram (EMG) signals free of power line interference. The first was a simple second-order recursive digital notch filter. The second was an approach called spectrum interpolation, in which it is assumed that the magnitude of the original 50 Hz component of the EMG signal can be approximated by interpolation of the amplitude spectrum of the signal. When the spectrum was based on records containing an integer number of cycles of 50 Hz interference, and the frequency resolution was finer than 1 Hz, spectrum interpolation performed similarly to, or significantly better than, the notch filter (p < 0.01). It was also possible to make spectrum interpolation more robust than the notch filter. The Pearson squared correlation coefficient r2 between clean signals and signals processed using the notch filter was reduced from 0.98 to 0.65 when the interference frequency was increased by 0.5 Hz, but r2 for spectrum interpolation at 0.2 Hz resolution was only reduced from 0.99 to 0.85 if spectral values between approximately 49.5 and 50.5 Hz were modified by interpolation.

Biomechanical modelling of orthotic treatment of the scoliotic spine including a detailed representation of the brace-torso interface

Abstract: As part of the development of new modelling tools for the simulation and design of brace treatment of scoliosis, a finite element model of a brace and its interface with the torso was proposed. The model was adapted to represent one scoliotic adolescent girl treated with a Boston brace. The 3D geometry was acquired using multiview radiographs. The model included the osseo-ligamentous structures, thoracic and abdominal soft tissues, brace foam and shell, and brace-torso interface. The simulations consisted of brace opening to include the patient's trunk followed by brace closing. To validate the model, the resulting geometry was compared with the real in-brace geometry, and the resulting contact reaction forces at the brace-torso interface were compared with the equivalent forces calculated from pressure measurements made on the in-brace patient. Differences between coronal equivalent and reaction forces were less than 7N. However, sagittal reaction forces (47N) were computed on the abdomen, whereas negligible equivalent forces were measured. The simulated geometry presented partially reduced coronal Cobb angles (1–40), over-corrected sagittal Cobb angles and maximum deformation plane (50), completely corrected coronal shift, and sagittal shift and rib humps that were not corrected. This study demonstrated the feasibility of a new approach that represents the load transfer from the brace to the spine more realistically than does the direct application of forces.

Respiratory acoustic thoracic imaging (RATHI): assessing deterministic interpolation techniques.

Abstract: As respiratory sounds contain mechanical and clinical pulmonary information, technical efforts have been devoted during the past decades to analysing, processing and visualising them. The aim of this work was to evaluate deterministic interpolating functions to generate surface respiratory acoustic thoracic images (RATHIs), based on multiple acoustic sensors. Lung sounds were acquired from healthy subjects through a 5×5 microphone array on the anterior and posterior thoracic surfaces. The performance of five interpolating functions, including the linear, cubic spline, Hermite, Lagrange and nearest neighbour method, were evaluated to produce images of lung sound intensity during both breathing phases, at low (∼0.5ls−1) and high (∼1.0ls−1) airflows. Performance indexes included the normalised residual variance nrv (i.e. inaccuracy), the prediction covariance cv (i.e. precision), the residual covariance rcv (i.e. bias) and the maximum squared residual error semax (i.e. tolerance). Among the tested interpolating functions and in all experimental conditions, the Hermite function (nrv=0.146±0.059, cv=0.925±0.030, rcv=−0.073±0.068, semax=0.005±0.004) globally provided the indexes closert to the optimum, whereas the nearest neighbour (nrv=0.339±0.023, cv=0.870±0.033, rcv=0.298±0.032, semax=0.007±0.005) and the Lagrange methods (nrv=0.287±0.148, cv=0.880±0.039, rcv=−0.524±0.135, semax=0.007±0.0001) presented the poorest statistical measurements. It is concluded that, although deterministic interpolation functions indicate different performances among tested techniques, the Hermite interpolation function presents a more confident deterministic interpolation for depicting surface-type RATHI.

Validation of a head-neck computer model for whiplash simulation.

Abstract: A head-neck computer model was comprehensively validated over a range of rear-impact velocities using experiments conducted by the same group of authors in the same laboratory. Validations were based on mean ±1 standard deviation response curves, i.e. corridors. Global head-neck angle, segmental angle and local facet joint regional kinematic responses from the model fell within experimental corridors. This was true for all impact velocities (1.3, 1.8 and 2.6 ms−1). The non-physiological S-curvature lasted approximately 100 ms. The present, comprehensively validated model can be used to conduct parametric studies and investigate the effects of factors such as active sequential and parallel muscle contractions, thoracic ramping and local tissue strain responses, as a function of cervical level, joint region and impact velocity in whiplash injury assessment.

Experimental evaluation of lesion prediction modelling in the presence of cavitation bubbles: intended for high-intensity focused ultrasound prostate treatment.

Abstract: The accuracy of high-intensity focused ultrasound (HIFU) lesion prediction modelling was evaluated for a truncated spherical transducer designed for prostate cancer treatment The modelling adapted the bio heat transfer equation (BHTE) to take into account the activity of cavitation bubbles generated during HIFU exposure. This modelling was used to predict the lesions produced by three different transducer geometries: fixed-focus, concentric-ring and 1.5D phased-array. Lesions were predicted for different ultrasound exposure conditions close to those used in prostate cancer treatment. Twenty-one in vitro and nine in vitro experiments were performed on pig liver to validate the accuracy of the predictions. A good match was found between the predicted and experimental lesion shapes. Lesion dimensions (maximum depth and length, area at the centre of the lesion or central surface area) were measured on experimental and predicted lesions. The central surface area was predicted by the model with a range of error of 0.15-6.5% for in vitro tests and 0.97-9% in vivo. For comparison, BHTE without bubbles had a range of error of 0.4-55.5% (in vitro) and 9-25.5% (in vivo). The model should be accurate enough to predict HIFU lesions under ultrasound exposure conditions used in prostate cancer treatment.

Improved neuromonitoring during spinal surgery using double-train transcranial electrical stimulation.

Abstract: Motor evoked potentials (MEPs) evoked by transcranial electrical stimulation (TES) have become an important technique for monitoring spinal cord function intra-operatively, but can fail in some patients. A new technique of double-train stimulation is described. A multipulse transcranial electrical stimulus is preceded by a preconditioning pulse train that leads to larger MEP responses. An MEP monitoring system was adapted for double-train transcranial stimulation (DTS). MEP responses from 160 anterior tibial muscles obtained by double-train stimulation were analysed. All patients received propofol/remifentanil/O2/N2O anaesthesia. Fifty-two (83%) out of 63 single-train tibial MEPs with response amplitudes below 100 microV were magnified to over 100 microV, with an inter-train (inter-stimulus) interval ITI = 10-35 ms. These 63 amplitudes were magnified by an overall logarithmic mean factor of 15.5. For 97 MEPs with amplitudes above 100 microV, the logarithmic mean facilitation factor was 2.4. It was concluded that double-train TES stimulation can markedly facilitate responses to a single stimulus train (STS). The facilitation appears to be most effective when the responses to STS would otherwise be small or absent. This preconditioning stimulation technique is therefore useful when an STS leads to responses that are too small for effective monitoring.

Surface electromyogram signal modelling.

Abstract: The paper reviews the fundamental components of stochastic and motorunit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.

Using independent component analysis to remove artifact from electroencephalographic measured during stuttered speech.

Abstract: The electro-encephalographic (EEG) activity of people who stutter could provide invaluable information about the association of neural processing and stuttering. However, the EEG has never been adequately studied during speech in which stuttering naturally occurs. This is owing, in part, to the masking of the EEG signal by artifact from sources such as the speech musculature and from ocular activity. The aim of this paper was to demonstrate the ability of independent component analysis (ICA) to remove artifact from the EEG of stuttering children recorded while they are speaking and stuttering. The EEG of 16 male children who stuttered and 16 who did not stutter was recorded during a reading task. The recorded EEG that contained artifact was then subjected to ICA. The results demonstrated that the EEG assessed during stuttered speech had substantially more noise than the EEG of speech that did not contain stuttering (p<0.01). Furthermore, it was shown that ICA could effectively remove this artifact in all 16 children (p<0.01). The results from one child highlight the findings that ICA can be used to remove dominant artifact that has prevented the study of EEG activity during stuttered speech in children.

Anatomy- and physics-based facial animation for craniofacial surgery simulations.

Abstract: A modelling approach for the realistic simulation of facial expressions of emotion in craniofacial surgery planning is presented. The method is different from conventional, non-physical techniques for character animation in computer graphics. A consistent physiological mechanism for facial expressions was assumed, which was the effect of contracting muscles on soft tissues. For the numerical solution of the linear elastic boundary values, the finite element method on tetrahedral grids was used. The approach was validated on a geometrical model of a human head derived from tomographic data. Using this model, individual facial expressions of emotion were estimated by the superpositioning of precomputed single muscle actions.

Stroke volume and systolic time intervals: beat-to-beat comparison between echocardiography and ambulatory impedance cardiography in supine and tilted positions.

Abstract: The aim of the study was to compare stroke volume (SV), ejection time (ET) and pre-ejection period (PEP) measurements obtained using a central haemodynamics ambulatory monitoring device based on impedance cardiography (ICG), in supine and tilted positions (60 degrees), with pulsed Doppler echocardiography as a non-invasive reference method. The Holter-type ICG device was used for off-line, beat-to-beat, automatic determination of SV, ET and PEP. ICG data were compared with those obtained simultaneously using pulsed Doppler echocardiography in the ascending aorta from a suprasternal projection, 1 min before and 10 min after tilting. The tests were performed in 13 young, healthy subjects (six men and seven women, aged 23-33 years). Linear regression between the measured values obtained for all subjects was described by the following formulas: SVicg= 13.9 + 0.813 x SVecho (r = 0.857, SEE = 9.03, n = 496), ETicg = 16.8 + 0.987 x ETecho (r = 0.841, SEE=21.3, n = 496), PEPicg= 22.8 + 0.890 x PEPecho (r = 0.727, SEE = 14.6, n = 496). The data showed that ambulatory impedance cardiography gives useful absolute values of SV and systolic time intervals measured in supine and tilted positions.

Segmentation of the fibro-glandular disc in mammograms using gaussian mixture modelling

Abstract: The paper presents a technique for the segmentation of the fibro-glandular disc in mammograms based upon a statistical model of breast density. The density function of the model was represented by a mixture of up to four weighted Gaussians, each one corresponding to a specific density class in the breast. The parameters of the model and the number of tissue classes in the breast were determined using the expectation-maximisation algorithm and the minimum description length method. Grey-level statistics of the pectoral muscle were used to determine the tissue categories that are likely to represent the fibro-glandular disc. The method was applied to 84 medio-lateral oblique mammograms from the Mini-MIAS database. The results of the segmented fibro-glandular disc were assessed by a radiologist using the original and the segmented images, with reference to a ranking table categorising the results of segmentation as: 1: excellent; 2: good; 3: average; 4: poor; and 5: complete failure. Of the 84 cases analysed, 64.3% were rated as excellent, 16.7% were rated as good, 10.7% were rated as average, and 4.7% were rated as poor; only 3.6% of the cases were rated as a complete failure with regard to segmentation of the fibro-glandular disc.

Single-trabecula building block for large-scale finite element models of cancellous bone.

Abstract: Recent development of high-resolution imaging of cancellous bone allows finite element (FE) analysis of bone tissue stresses and strains in individual trabeculae. However, specimen-specific stress/strain analyses can include effects of anatomical variations and local damage that can bias the interpretation of the results from individual specimens with respect to large populations. This study developed a standard (generic) 'building-block' of a trabecula for large-scale FE models. Being parametric and based on statistics of dimensions of ovine trabeculae, this building block can be scaled for trabecular thickness and length and be used in commercial or custom-made FE codes to construct generic, large-scale FE models of bone, using less computer power than that currently required to reproduce the accurate micro-architecture of trabecular bone. Orthogonal lattices constructed with this building block, after it was scaled to trabeculae of the human proximal femur, provided apparent elastic moduli of approximately 150 MPa, in good agreement with experimental data for the stiffness of cancellous bone from this site. Likewise, lattices with thinner, osteoporotic-like trabeculae could predict a reduction of approximately 30% in the apparent elastic modulus, as reported in experimental studies of osteoporotic femora. Based on these comparisons, it is concluded that the single-trabecula element developed in the present study is well-suited for representing cancellous bone in large-scale generic FE simulations.

Effect of accelerometer location on mechanomyogram variables during voluntary, constant-force contractions in three human muscles

Abstract: To understand better the features of the mechanomyogram (MMG) with different force levels and muscle architectures, the MMG signals detected at many points along three muscles were analysed by the application of a linear array of MMG sensors (up to eight) over the skin. MMG signals were recorded from the biceps brachii, tibialis anterior and upper trapezius muscles of the dominant side of ten healthy male subjects. The accelerometers were aligned along the direction of the muscle fibres. One accelerometer was located over the distal muscle innervation zone, and the other six or seven accelerometers were placed over the muscle, forming an array of sensors with fixed distances between them. The array covered almost the entire muscle length in all cases. MMG signals detected from adjacent accelerometers had similar shapes, with correlation coefficients ranging from about 0.5 to about 0.9. MMG amplitude and characteristic spectral frequencies significantly depended on accelerometer location. The MMG amplitude was maximum at the muscle belly for the biceps brachii and the tibialis anterior. Higher MMG characteristic spectral frequencies were associated with higher amplitudes in the case of the biceps brachii, whereas the opposite was observed for the tibialis anterior muscle. In the upper trapezius, the relationship between characteristic spectral frequencies, MMG amplitude and contraction force depended on the accelerometer location. This suggested that MMG spectral features do not only reflect the mechanical properties of the recruited muscle fibres but depend on muscle architecture and motor unit territorial distribution. It was concluded that the location of the accelerometer can have an influence on both amplitude and spectral MMG features, and this dependence should be considered when MMG signals are used for muscle assessment.

Tuned vibration absorber for suppression of rest tremor in Parkinson's disease.

Abstract: A simple approach for the suppression of the tremor associated with Parkinson's disease is presented. The proposed system is a tuned vibration absorber (TVA), which has been very effective in the suppression of vibrations in an experimental model of the human arm with two degrees of freedom. Theoretical and numerical methods were used to study the behaviour of the arm model and to develop an effective tremor reduction approach. Based on these studies, a vibration absorber was designed, tested numerically and fabricated for experimental testing. Expermental investigations indicated that optimum control performance was related to the position of the controller and the excitation frequency. With a distance of 160 mm from the end of forearm, the TVA was found to have the best performance, and, for different tremor frequencies, the vibration of the experimental model was reduced by more than 80%.

Three-dimensional stress analysis for the mechanics of plantar ulcers in diabetic neuropathy.

Abstract: In diabetic neuropathic subjects, the hardness of foot sole soft tissue increases, and its thickness reduces, in different foot sole areas. Finite element analysis (FEA) of a three-dimensional two-arch model of the foot was performed to evaluate the effect of foot sole stresses on plantar ulcer development. Three sets of foot sole soft-tissue properties, i.e. isotropic (with control hardness value), diabetic isotropic (with higher hardness value) and anisotropic diabetic conditions, were simulated in the push-off phase, with decreasing foot sole soft-tissue thicknesses in the forefoot region, and the corresponding stresses were calculated. The results of the stress analyses for diabetic subject (anisotropic) foot models showed that, with non-uniformly increased hardness and decreased foot sole soft-tissue thickness, the normal and shear stresses at the foot sole increased (compared with control values) by 52.6% and 53.4%, respectively. Stress analyses also showed high ratios of gradients of normal and shear stresses of the order of 6.6 and 3.3 times the control values on the surface of the foot sole, and high relative values of stress gradients for normal and shear stresses of 6.25 and 4.35 times control values, respectively, between the foot sole surface and the adjacent inner layer of the foot sole, around a particular region of the foot sole with anisotropic properties. These ratios of high gradients and relative gradients of stresses due to changes in soft-tissue properties may be responsible for the development of plantar ulcers in diabetic neuropathic feet.