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Biomedical Engineering, IEEE Transactions on

Issue 6 • Date June 2005

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Displaying Results 1 - 25 of 28
  • Table of contents

    Page(s): c1 - c4
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  • IEEE Transactions on Biomedical Engineering publication information

    Page(s): c2
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  • Needle steering and motion planning in soft tissues

    Page(s): 965 - 974
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1174 KB) |  | HTML iconHTML  

    In this work, needle insertion into deformable tissue is formulated as a trajectory planning and control problem. A new concept of needle steering has been developed and a needle manipulation Jacobian defined using numerical needle insertion models that include needle deflection and soft tissue deformation. This concept is used in conjunction with a potential-field-based path planning technique to demonstrate needle tip placement and obstacle avoidance. Results from open loop insertion experiments are provided. View full abstract»

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  • Fat and hydration monitoring by abdominal bioimpedance analysis: data interpretation by hierarchical electrical modeling

    Page(s): 975 - 982
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (731 KB) |  | HTML iconHTML  

    In a previous publication, it was demonstrated that the abdominal subcutaneous fat layer thickness (SFL) is strongly correlated with the abdominal electrical impedance when measured with a transversal tetrapolar electrode arrangement. This article addresses the following questions: 1) To which extent do different abdominal compartments contribute to the impedance? 2) How does the hydration state of tissues affect the data? 3) Can hydration and fat content be assessed independently? For simulating the measured data a hierarchical electrical model was built. The abdomen was subdivided into three compartments (subcutaneous fat, muscle, mesentery). The true anatomical structure of the compartment boundaries was modeled using finite-element modeling (FEM). Each compartment is described by an electrical tissue model parameterized in physiological terms. Assuming the same percent change of the fat fraction in the mesentery and the SFL the model predicts a change of 1,24 Ω/mm change of the SFL compared to 1,1 Ω/mm measured. 42% of the change stem from the SFL, 56% from the mesentery and 2% from changes of fat within the muscle compartment. A 1% increase of the extracellular water in the muscle is not discernible from a 1% decrease of the SFL. The measured data reflect not only the SFL but also the visceral fat. The tetrapolar electrode arrangement allows the measurement of the abdominal fat content only if the hydration remains constant. View full abstract»

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  • Noninvasive measurement and analysis of intestinal myoelectrical activity using surface electrodes

    Page(s): 983 - 991
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (429 KB) |  | HTML iconHTML  

    Intestinal myoelectrical activity (IMA), which determines bowel mechanical activity, is the result of two components: a low-frequency component [slow wave (SW)] that is always present, and a high-frequency component [spike bursts (SB)] which is associated with bowel contractions. Despite of the diagnostic significance of internal recordings of IMA, clinical application of this technique is limited due to its invasiveness. Thus, surface recording of IMA which is also called electroenterogram (EEnG) could be a solution for noninvasive monitoring of intestinal motility. The aim of our work was to identify slow wave and spike burst activity on surface EEnG in order to quantify bowel motor activity. For this purpose, we conducted simultaneous recordings of IMA in bowel serosa and on abdominal surface of five Beagle dogs in fast state. Surface EEnG was studied in spectral domain and frequency bands for slow wave and spike burst energy were determined. Maximum signal-to-interference ratio (7.5dB±36%) on SB frequency band was obtained when reducing upper frequency limit of signal analysis. Energy of external EEnG in reduced SB frequency band (2-7.9Hz) presented a high correlation (0.71±7%) with internal intensity of contractions. Our results suggest that energy of SB can be quantified on external EEnG which could provide a noninvasive method for monitoring intestinal mechanical activity. View full abstract»

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  • Soft tissue artifact compensation in knee kinematics by double anatomical landmark calibration: performance of a novel method during selected motor tasks

    Page(s): 992 - 998
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (854 KB) |  | HTML iconHTML  

    The purpose of the present work was to describe and assess the performance on two selected subjects of a new method for the compensation of soft tissue artifact on knee rotations and translations during the execution of step up/down, sit-to-stand/stand-to-sit, and flexion against gravity. Soft tissue artifact has been recognized as the most critical source of error in gait analysis data. Its propagation strongly affects joint angles, in particular those characterized by a small range of motion, such as knee ab/adduction and internal/external rotation. This may be critical in the exploitation of gait analysis data for clinical decisions. The proposed method is based on the flexion/extension angle interpolation of two anatomical landmark calibrations taken at the extremes of motion. Its performance on knee rotation and translations was tested on a kinematics data-set obtained by the synchronous combination of traditional stereophotogrammetry and 3-D fluoroscopy. The newly proposed method was extremely effective on the compensation of soft tissue artifact propagation to knee rotations, in particular mean values of the root mean square error on ab/adduction and internal/external rotation angles decreased from 3.7° and 3.7° to 1.4° and 1.6°, respectively, with respect to single calibration. Mainly, knee translations calculated from stereophotogrammetric data using the proposed compensation method were found to be reliable with respect to the fluoroscopy-based gold standard. The residual mean values of the root mean square error were 2.0, 2.8, and 2.1 mm for anterior/posterior, vertical, and medio/lateral translations, respectively. View full abstract»

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  • A 2-D ECG compression method based on wavelet transform and modified SPIHT

    Page(s): 999 - 1008
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (926 KB) |  | HTML iconHTML  

    A two-dimensional (2-D) wavelet-based electrocardiogram (ECG) data compression method is presented which employs a modified set partitioning in hierarchical trees (SPIHT) algorithm. This modified SPIHT algorithm utilizes further the redundancy among medium- and high-frequency subbands of the wavelet coefficients and the proposed 2-D approach utilizes the fact that ECG signals generally show redundancy between adjacent beats and between adjacent samples. An ECG signal is cut and aligned to form a 2-D data array, and then 2-D wavelet transform and the modified SPIHT can be applied. Records selected from the MIT-BIH arrhythmia database are tested. The experimental results show that the proposed method achieves high compression ratio with relatively low distortion and is effective for various kinds of ECG morphologies. View full abstract»

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  • Bayesian solutions and performance analysis in bioelectric inverse problems

    Page(s): 1009 - 1020
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1019 KB) |  | HTML iconHTML  

    In bioelectric inverse problems, one seeks to recover bioelectric sources from remote measurements using a mathematical model that relates the sources to the measurements. Due to attenuation and spatial smoothing in the medium between the sources and the measurements, bioelectric inverse problems are generally ill-posed. Bayesian methodology has received increasing attention recently to combat this ill-posedness, since it offers a general formulation of regularization constraints and additionally provides statistical performance analysis tools. These tools include the estimation error covariance and the marginal probability density of the measurements (known as the "evidence") that allow one to predictively quantify and compare experimental designs. These performance analysis tools have been previously applied in inverse electroencephalography and magnetoencephalography, but only in relatively simple scenarios. The main motivation here was to extend the utility of Bayesian estimation techniques and performance analysis tools in bioelectric inverse problems, with a particular focus on electrocardiography. In a simulation study we first investigated whether Bayesian error covariance, computed without knowledge of the true sources and based on instead statistical assumptions, accurately predicted the actual reconstruction error. Our study showed that error variance was a reasonably reliable qualitative and quantitative predictor of estimation performance even when there was error in the prior model. We also examined whether the evidence statistic accurately predicted relative estimation performance when distinct priors were used. In a simple scenario our results support the hypothesis that the prior model that maximizes the evidence is a good choice for inverse reconstructions. View full abstract»

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  • Fast wavelet estimation of weak biosignals

    Page(s): 1021 - 1032
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1085 KB) |  | HTML iconHTML  

    Wavelet-based signal processing has become commonplace in the signal processing community over the past decade and wavelet-based software tools and integrated circuits are now commercially available. One of the most important applications of wavelets is in removal of noise from signals, called denoising, accomplished by thresholding wavelet coefficients in order to separate signal from noise. Substantial work in this area was summarized by Donoho and colleagues at Stanford University, who developed a variety of algorithms for conventional denoising. However, conventional denoising fails for signals with low signal-to-noise ratio (SNR). Electrical signals acquired from the human body, called biosignals, commonly have below 0 dB SNR. Synchronous linear averaging of a large number of acquired data frames is universally used to increase the SNR of weak biosignals. A novel wavelet-based estimator is presented for fast estimation of such signals. The new estimation algorithm provides a faster rate of convergence to the underlying signal than linear averaging. The algorithm is implemented for processing of auditory brainstem response (ABR) and of auditory middle latency response (AMLR) signals. Experimental results with both simulated data and human subjects demonstrate that the novel wavelet estimator achieves superior performance to that of linear averaging. View full abstract»

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  • Identification of transient renal autoregulatory mechanisms using time-frequency spectral techniques

    Page(s): 1033 - 1039
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (873 KB) |  | HTML iconHTML  

    Identification of the two principal mediators of renal autoregulation from time-series data is difficult, as both the tubuloglomerular feedback (TGF) and myogenic (MYO) mechanisms interact and share a common effector, the afferent arteriole. Moreover, although both mechanisms can exhibit oscillations in well-characterized frequency bands, these systems often operate in nonoscillatory states not detectable by frequency-domain analysis. To overcome these difficulties, we have developed a new approach to the characterization of the TGF and MYO systems. A laser Doppler probe is used to measure fluctuations in local cortical blood flow (CBF) in response to spontaneous changes in blood pressure (BP) and to large imposed perturbations in BP, which elicit strong, simultaneous, transient, oscillatory blood flow responses. These transient responses are identified by high-resolution time-frequency spectral analysis of the time-series data. In this report, we compare four different time-frequency spectral techniques (the short-time Fourier transform (STFT), smoothed pseudo Wigner-Ville, and two recently developed methods: the Hilbert-Huang transform and time varying optimal parameter search (TVOPS)) to determine which of these four methods is best suited for the identification of transient oscillations in renal autoregulatory mechanisms. We found that TVOPS consistently provided the best performance in both simulation examples and identification of the two autoregulatory mechanisms in actual data. While the STFT suffers in time and frequency resolution as compared to the other three methods, it was able to identify the two autoregulatory mechanisms. Taken together, our experience suggests a two level approach to the analysis of renal blood flow (RBF) data: STFT to obtain a low-resolution time-frequency spectrogram, followed by the use of a higher resolution technique, such as the TVOPS, if even higher time-frequency resolution of the transient responses is required. View full abstract»

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  • Predicting dynamic range and intensity discrimination for electrical pulse-train stimuli using a stochastic auditory nerve model: the effects of stimulus noise

    Page(s): 1040 - 1049
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (379 KB) |  | HTML iconHTML  

    This work investigates dynamic range and intensity discrimination for electrical pulse-train stimuli that are modulated by noise using a stochastic auditory nerve model. Based on a hypothesized monotonic relationship between loudness and the number of spikes elicited by a stimulus, theoretical prediction of the uncomfortable level has previously been determined by comparing spike counts to a fixed threshold, Nucl. However, no specific rule for determining Nucl has been suggested. Our work determines the uncomfortable level based on the excitation pattern of the neural response in a normal ear. The number of fibers corresponding to the portion of the basilar membrane driven by a stimulus at an uncomfortable level in a normal ear is related to Nucl at an uncomfortable level of the electrical stimulus. Intensity discrimination limens are predicted using signal detection theory via the probability mass function of the neural response and via experimental simulations. The results show that the uncomfortable level for pulse-train stimuli increases slightly as noise level increases. Combining this with our previous threshold predictions, we hypothesize that the dynamic range for noise-modulated pulse-train stimuli should increase with additive noise. However, since our predictions indicate that intensity discrimination under noise degrades, overall intensity coding performance may not improve significantly. View full abstract»

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  • Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding-part II: application results

    Page(s): 1050 - 1064
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (767 KB) |  | HTML iconHTML  

    The application of the wavelet transform-fractal dimension-based (WT-FD) filter of Part I of this paper to real bioacoustic data, which include explosive lung sounds (ELS) and explosive bowel sounds (EBS) recorded from patients with pulmonary or gastrointestinal dysfunction, respectively, is presented in this paper. The objective of the latter is the evaluation of the performance of the WT-FD filter on different types of bioacoustic signals, varying not only in their structural morphology but also in the degree of their noise contamination. As it is thoroughly described in Part I of this paper, the WT-FD filter uses the fractal dimension to form an efficient way of thresholding the WT coefficients at different resolution scales, keeping, thus, only those that can contribute to the accurate reconstruction of the ELS and EBS signals. Quantitative and qualitative analysis of the experimental results show an efficient performance of the WT-FD filter to circumvent the noise presence (100% detectability rate, 100% sensitivity, 100% specificity) by faithfully extracting the authentic structure of ELS and EBS from the background noise. The WT-FD filter does not require any noise reference signal or noise reference templates. The results from a noise stress test (mean cross-correlation index of the original and the estimated signal converging to 100%; mean normalized maximum amplitude error converging to 0.7%) prove its robustness to various noise levels (0-20 dB), enabling its potential use in similar noise cases met in everyday clinical medicine. Furthermore, the efficient performance of the WT-FD filter facilitates the physician to better interpret the auscultation findings. Due to its simplicity and low computational cost, the WT-FD filter can possibly be implemented in a real-time context to serve as a tool for the continuous ELS and EBS screening. View full abstract»

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  • Quantifying motion in video recordings of neonatal seizures by robust motion trackers based on block motion models

    Page(s): 1065 - 1077
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1844 KB) |  | HTML iconHTML  

    This paper introduces a methodology for the development of robust motion trackers for video based on block motion models. According to this methodology, the motion of a site between two successive frames is estimated by minimizing an error function defined in terms of the intensities at these frames. The proposed methodology is used to develop robust motion trackers that rely on fractional block motion models. The motion trackers developed in this paper are utilized to extract motor activity signals from video recordings of neonatal seizures. The experimental results reveal that the proposed motion trackers are more accurate and reliable than existing motion tracking methods relying on pure translation and affine block motion models. View full abstract»

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  • Using EMG to anticipate head motion for virtual-environment applications

    Page(s): 1078 - 1093
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1603 KB) |  | HTML iconHTML  

    In virtual environment (VE) applications, where virtual objects are presented in a see-through head-mounted display, virtual images must be continuously stabilized in space in response to user's head motion. Time delays in head-motion compensation cause virtual objects to "swim" around instead of being stable in space which results in misalignment errors when overlaying virtual and real objects. Visual update delays are a critical technical obstacle for implementing head-mounted displays in applications such as battlefield simulation/training, telerobotics, and telemedicine. Head motion is currently measurable by a head-mounted 6-degrees-of-freedom inertial measurement unit. However, even given this information, overall VE-system latencies cannot be reduced under about 25 ms. We present a novel approach to eliminating latencies, which is premised on the fact that myoelectric signals from a muscle precede its exertion of force, thereby limb or head acceleration. We thus suggest utilizing neck-muscles' myoelectric signals to anticipate head motion. We trained a neural network to map such signals onto equivalent time-advanced inertial outputs. The resulting network can achieve time advances of up to 70 ms. View full abstract»

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  • A safe transmission line for MRI

    Page(s): 1094 - 1102
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (599 KB) |  | HTML iconHTML  

    Magnetic resonance imaging (MRI) has been established as a reliable and safe imaging method for the human body. However, electric conductors, such as cables situated near or in the human body, should be avoided because induced currents in the cables can cause hazardous heating in the surrounding tissue. In this paper, a new principle for the design of a transmission line is introduced and demonstrated, which is capable of avoiding dangerous heating of cables. The principle is based on transformers placed along the line, splitting the long line into several short not resonant and thus safe sections. A transformer design is introduced along with the theoretical aspects for both the avoidance of the undesired induced currents and the reduction of signal attenuation. Furthermore, the design fulfills the geometrical requirements of the side lumen of a standard catheter. Matching networks, whose elements are determined by power matching, are used to reduce signal attenuation by the transformers. A prototype was built to validate both theory and the simulations. As demonstrated in this work, it is possible to build safe transmission lines for MRI, making applications such as active catheter tracking possible. We expect that even new applications, such as safe intravascular imaging will be possible in a safe manner in the future. View full abstract»

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  • Electric fields in bone marrow substructures at power-line frequencies

    Page(s): 1103 - 1109
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (994 KB) |  | HTML iconHTML  

    Bone marrow is known to be responsible for leukemia. In order to study the hypothesis relating power-line frequencies electromagnetic fields and childhood leukemia from a subcellular perspective, two models of bone marrow substructures exposed to electric field are computed numerically. A set of cancellous bone data obtained from computed tomography scan is computed using both the finite element method (FEM) and scalar potential finite difference method. A maximum electric field enhancement of 50% is observed. Another model of bone marrow stroma cells is implemented only in FEM using thin film approximation. The transmembrane potential (TMP) change across the gap junctions is found to range from several to over 200 μV. The two results suggest that imperceptible contact currents can produce biologically significant TMP change at least in a limited number of bone marrow stroma cells. View full abstract»

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  • On the development of a biomechatronic system to record tendon sliding movements

    Page(s): 1110 - 1119
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1396 KB) |  | HTML iconHTML  

    The main goal of this paper is to study the feasibility of a novel implantable micro-system able to record information about tendon sliding movements by using contactless measurement devices (magnetic sources and sensors). The system, named "Biomechatronic Position Transducer" (BPT), can be used for the implementation of advanced control strategies in neuroprostheses. After a preliminary analysis based on finite element model simulations, an experimental setup was developed in order to simulate the recording conditions (the sensors fixed to the bones and the magnetic sources placed on the tendons). In order to limit the number of implanted components of the system, a fuzzy Mamdani-like architecture was developed to extract the information from the raw data. The results confirm the possibility of using the presented approach for developing an implantable micro-sensor able to extract kinematic information useful for the control of neuroprostheses. Future works will go in the direction of integrating and testing the sensors and the electronic circuitry (to provide power supply and to record the data) during in vitro and in situ experiments. View full abstract»

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  • Effects of external pressure on arteries distal to the cuff during sphygmomanometry

    Page(s): 1120 - 1127
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (519 KB) |  | HTML iconHTML  

    The aim of this study was to examine the effect on distal arteries of external pressure, applied by upper arm sphygmomanometer cuff. Photoplethysmographic (PPG) signals were measured on the index fingers of 44 healthy male subjects, during the slow decrease of cuff air pressure. For each pulse the ratio of PPG amplitude to its baseline (AM/BL) and its time delay (ΔTD) relative to the contralateral hand were determined as a function of cuff pressure. At cuff pressures equal to systolic blood pressure, pulses reappeared with the pulse time delay in the cuffed arm significantly greater than in the noncuffed arm, with (ΔTD)(mean±SD)150±31 ms (p<0.001). At cuff pressures equal to diastolic blood pressure (81±12 mmHg),ΔTD was 42±19 ms (p<0.001), and at 50 mmHg, which is below diastolic blood pressure, (ΔTD) was still significantly positive at 6±9 ms (p<0.001). AM/BL relative to its initial value rose at cuff pressures between systolic and diastolic blood pressure, then deceased to 0.6±0.41 (p<0.001) at diastolic blood pressure and 0.54±0.24 (p<0.001) at 50 mmHg. The changes in (ΔTD) and AM/BL can be interpreted as originating from changes in the compliance of conduit arteries and small arteries with cuff inflation and deflation. View full abstract»

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  • Adaptive model initialization and deformation for automatic segmentation of T1-weighted brain MRI data

    Page(s): 1128 - 1131
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (452 KB) |  | HTML iconHTML  

    A fully automatic, two-step, T1-weighted brain magnetic resonance imaging (MRI) segmentation method is presented. A preliminary mask of parenchyma is first estimated through adaptive image intensity analysis and mathematical morphological operations. It serves as the initial model and probability reference for a level-set algorithm in the second step, which finalizes the segmentation based on both image intensity and geometric information. The Dice coefficient and Euclidean distance between boundaries of automatic results and the corresponding references are reported for both phantom and clinical MR data. For the 28 patient scans acquired at our institution, the average Dice coefficient was 98.2% and the mean Euclidean surface distance measure was 0.074 mm. The entire segmentation for either a simulated or a clinical image volume finishes within 2 min on a modern PC system. The accuracy and speed of this technique allow us to automatically create patient-specific finite element models within the operating room on a timely basis for application in image-guided updating of preoperative scans. View full abstract»

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  • Fuzzy wavelet packet based feature extraction method and its application to biomedical signal classification

    Page(s): 1132 - 1139
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (545 KB) |  | HTML iconHTML  

    In this paper, we develop an efficient fuzzy wavelet packet (WP) based feature extraction method for the classification of high-dimensional biomedical data such as magnetic resonance spectra. The key design phases involve: 1) a WP transformation mapping the original signals to many WP feature spaces and finding optimal WP decomposition for signal classification; 2) feature extraction based on the optimal WP decomposition; and 3) signal classification realized by a linear classifier. In contrast to the standard method of feature extraction used in WPs, guided by the criteria of signal compression or signal energy, our method is used to extract discriminatory features from the WP coefficients of the optimal decomposition. The extraction algorithm constructs fuzzy sets of features (via fuzzy clustering) to assess their discriminatory effectiveness. This paper includes a number of numerical experiments using magnetic resonance spectra. Classification results are compared with those obtained from common feature extraction methods in the WP domain. View full abstract»

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  • Fetal magnetocardiographic signals extracted by 'signal subspace' blind source separation

    Page(s): 1140 - 1142
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (133 KB) |  | HTML iconHTML  

    In this paper, we apply independent component analysis to fetal magnetocardiographic data. In particular, we propose an extension of the "cumulant-based iterative inversion" algorithm to include a two-step "signal subspace" subdivision, which allows the user to control the number of components to be estimated by analyzing the eigenvalues distribution in an interactive way. Our results show that this method is a powerful means not only for the extraction of the cardiac signals from the background noise but also for a sharp separation of the baby's heart from the mother's. View full abstract»

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  • Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding-part I: methodology

    Page(s): 1143 - 1148
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (232 KB) |  | HTML iconHTML  

    An efficient method for the enhancement of lung sounds (LS) and bowel sounds (BS), based on wavelet transform (WT), and fractal dimension (FD) analysis is presented in this paper. The proposed method combines multiresolution analysis with FD-based thresholding to compose a WT-FD filter, for enhanced separation of explosive LS (ELS) and BS (EBS) from the background noise. In particular, the WT-FD filter incorporates the WT-based multiresolution decomposition to initially decompose the recorded bioacoustic signal into approximation and detail space in the WT domain. Next, the FD of the derived WT coefficients is estimated within a sliding window and used to infer where the thresholding of the WT coefficients has to happen. This is achieved through a self-adjusted procedure that iteratively "peels" the estimated FD signal and isolates its peaks produced by the WT coefficients corresponding to ELS or EBS. In this way, two new signals are constructed containing the useful and the undesired WT coefficients, respectively. By applying WT-based multiresolution reconstruction to these two signals, a first version of the desired signal and the background noise is provided, accordingly. This procedure is repeated until a stopping criterion is met, finally resulting in efficient separation of the ELS or EBS from the background noise. The proposed WT-FD filter introduces an alternative way to the enhancement of bioacoustic signals, applicable to any separation problem involving nonstationary transient signals mixed with uncorrelated stationary background noise. The results from the application of the WT-FD filter to real bioacoustic data are presented and discussed in an accompanying paper. View full abstract»

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  • A novel technique for the extraction of fetal ECG using polynomial networks

    Page(s): 1148 - 1152
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    In this paper, we propose a novel technique for extracting fetal electrocardiogram (FECG) from a thoracic ECG recording and an abdominal ECG recording of a pregnant woman. The polynomial networks technique is used to nonlinearly map the thoracic ECG signal to the abdominal ECG signal. The FECG is then extracted by subtracting the mapped thoracic ECG from the abdominal ECG signal. Visual test results obtained from real ECG signals show that the proposed algorithm is capable of reliably extracting the FECG from two leads only. The visual quality of the FECG extracted by the proposed technique is found to meet or exceed that of published results using other techniques such as the independent component analysis. View full abstract»

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  • 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

    Page(s): 1153 - 1157
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    Freely Available from IEEE
  • Special issue on image management in healthcare enterprises

    Page(s): 1158
    Save to Project icon | Request Permissions | PDF file iconPDF (527 KB)  
    Freely Available from IEEE

Aims & Scope

IEEE Transactions on Biomedical Engineering contains basic and applied papers dealing with biomedical engineering. Papers range from engineering development in methods and techniques with biomedical applications to experimental and clinical investigations with engineering contributions.

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Meet Our Editors

Editor-in-Chief
Bin He
Department of Biomedical Engineering