By Topic

Biomedical Engineering, IEEE Transactions on

Issue 5 • Date May 2004

Filter Results

Displaying Results 1 - 25 of 30
  • Table of contents

    Publication Year: 2004 , Page(s): c1 - c4
    Save to Project icon | Request Permissions | PDF file iconPDF (39 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Biomedical Engineering publication information

    Publication Year: 2004 , Page(s): c2
    Save to Project icon | Request Permissions | PDF file iconPDF (40 KB)  
    Freely Available from IEEE
  • Dynamic modeling of renal blood flow in Dahl hypertensive and normotensive rats

    Publication Year: 2004 , Page(s): 689 - 697
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (302 KB) |  | HTML iconHTML  

    A method is proposed in this paper which allows characterization of renal autoregulatory dynamics and efficiency using quantitative mathematical methods. Based on data from rat experiments, where arterial blood pressure and renal blood flow are measured, a quantitative model for renal blood flow dynamics is constructed. The mathematical structure for the dynamics is chosen as a "grey-box model," i.e. the model structure is inspired from physiology, but the actual parameters is found by numerical methods. Based on a number of experiments, features are extracted from the estimated parameters, which describe myogenic responses and tubuloglomerular feedback responses separately. The method is applied to data from normo- and hypertensive Dahl rats, and a discriminator that separates data from normotensive Dahl R rats and hypertensive Dahl S rats is constructed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Different pulse shapes to obtain small fiber selective activation by anodal blocking-a simulation study

    Publication Year: 2004 , Page(s): 698 - 706
    Cited by:  Papers (11)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (288 KB) |  | HTML iconHTML  

    The aim of this study was to investigate whether it is possible to reduce a charge per pulse, which is needed for selective nerve stimulation. Simulation is performed using a two-part simulation model: a volume conductor model to calculate the electrical potential distribution inside a tripolar cuff electrode and a human fiber model to simulate the fiber response to simulation. Selective stimulation is obtained by anodal block. To obtain anodal block of large fibers, long square pulses (>350 μs) with a relatively high currents (1-2.5 mA) are usually required. These pulses might not be safe for a long-term application because of a high charge per pulse. In this study, several pulse shapes are proposed that have less charge per pulse compared with the conventional square pulse and would therefore be safer in a chronic application. Compared with the conventional square pulse, it was possible to reduce the charge with all proposed pulse shapes, but the best results are obtained with a combination of a square depolarizing pulse and a blocking pulse. The charge per pulse was up to 32% less with that pulse shape than with a square pulse. Using a hyperpolarizing anodal prepulse preceding a square pulse, it was not possible to block nerve fibers in a whole nerve bundle and to obtain reduction of a charge per phase. Reduction of the charge could be achieved only with spatially selective blocking. The charge per phase was larger for the combination of a hyperpolarizing anodal prepulse and a two-step pulse than for the two-step pulse alone. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Bayesian class discovery in microarray datasets

    Publication Year: 2004 , Page(s): 707 - 718
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (723 KB) |  | HTML iconHTML  

    A novel approach to class discovery in gene expression datasets is presented. In the context of clinical diagnosis, the central goal of class discovery algorithms is to simultaneously find putative (sub-)types of diseases and to identify informative subsets of genes with disease-type specific expression profile. Contrary to many other approaches in the literature, the method presented implements a wrapper strategy for feature selection, in the sense that the features are directly selected by optimizing the discriminative power of the used partitioning algorithm. The usual combinatorial problems associated with wrapper approaches are overcome by a Bayesian inference mechanism. On the technical side, we present an efficient optimization algorithm with guaranteed local convergence property. The only free parameter of the optimization method is selected by a resampling-based stability analysis. Experiments with Leukemia and Lymphoma datasets demonstrate that our method is able to correctly infer partitions and corresponding subsets of genes which both are relevant in a biological sense. Moreover, the frequently observed problem of ambiguities caused by different but equally high-scoring partitions is successfully overcome by the model selection method proposed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation

    Publication Year: 2004 , Page(s): 719 - 727
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (277 KB) |  | HTML iconHTML  

    This paper proposes the use of variational Kalman filtering as an inference technique for adaptive classification in a brain computer interface (BCI). The proposed algorithm translates electroencephalogram segments adaptively into probabilities of cognitive states. It, thus, allows for nonstationarities in the joint process over cognitive state and generated EEG which may occur during a consecutive number of trials. Nonstationarities may have technical reasons (e.g., changes in impedance between scalp and electrodes) or be caused by learning effects in subjects. We compare the performance of the proposed method against an equivalent static classifier by estimating the generalization accuracy and the bit rate of the BCI. Using data from two studies with healthy subjects, we conclude that adaptive classification significantly improves BCI performance. Averaging over all subjects that participated in the respective study, we obtain, depending on the cognitive task pairing, an increase both in generalization accuracy and bit rate of up to 8%. We may, thus, conclude that adaptive inference can play a significant contribution in the quest of increasing bit rates and robustness of current BCI technology. This is especially true since the proposed algorithm can be applied in real time. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A novel method for determining the nature of time series

    Publication Year: 2004 , Page(s): 728 - 736
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    The delay vector variance (DVV) method, which analyzes the nature of a time series with respect to the prevalence of deterministic or stochastic components, is introduced. Due to the standardization within the DVV method, it is possible both to statistically test for the presence of nonlinearities in a time series, and to visually inspect the results in a DVV scatter diagram. This approach is convenient for interpretation as it conveys information about the linear or nonlinear nature, as well as about the prevalence of deterministic or stochastic components in the time series, thus unifying the existing approaches which deal either with only deterministic versus stochastic, or the linear versus nonlinear aspect. The results on biomedical time series, namely heart rate variability (HRV) and functional Magnetic Resonance Imaging (fMRI) time series, illustrate the applicability of the proposed DVV-method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Characterization of event related potentials using information theoretic distance measures

    Publication Year: 2004 , Page(s): 737 - 743
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (209 KB) |  | HTML iconHTML  

    Analysis of event-related potentials (ERPs) using signal processing tools has become extremely widespread in recent years. Nonstationary signal processing tools such as wavelets and time-frequency distributions have proven to be especially effective in characterizing the transient phenomena encountered in event-related potentials. In this paper, we focus on the analysis of event-related potentials collected during a psychological experiment where two groups of subjects, spider phobics and snake phobics, are shown the same set of stimulus: A blank stimulus, a neutral stimulus and a spider stimulus. We introduce a new approach, based on time-frequency distributions, for analyzing the ERPs. The difference in brain activity before and after a stimulus is presented is quantified using distance measures as adapted to the time-frequency plane. Three different distance measures, including a new information theoretic distance measure, are applied on the time-frequency plane to discriminate between the responses of the two groups of subjects. The results illustrate the effectiveness of using distance measures combined with time-frequency distributions in differentiating between the two classes of subjects and the different regions of the brain. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • EEG signal modeling using adaptive Markov process amplitude

    Publication Year: 2004 , Page(s): 744 - 751
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (417 KB) |  | HTML iconHTML  

    In this paper, an adaptive Markov process amplitude algorithm is used to model and simulate electroencephalogram (EEG) signals. EEG signal modeling is used as a tool to identify pathophysiological EEG changes potentially useful in clinical diagnosis. The least mean square algorithm is adopted to continuously estimate the parameters of a first-order Markov process model. EEG signals recorded from rodent brains during injury and recovery following global cerebral ischemia are utilized as input signals to the model. The EEG was recorded in a controlled experimental brain injury model of hypoxic-ischemic cardiac arrest. The signals from the injured brain during various phases of injury and recovery were modeled. Results show that the adaptive model is accurate in simulating EEG signal variations following brain injury. The dynamics of the model coefficients successfully capture the presence of spiking and bursting in EEG. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A novel speech-processing strategy incorporating tonal information for cochlear implants

    Publication Year: 2004 , Page(s): 752 - 760
    Cited by:  Papers (34)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (355 KB) |  | HTML iconHTML  

    Good performance in cochlear implant users depends in large part on the ability of a speech processor to effectively decompose speech signals into multiple channels of narrow-band electrical pulses for stimulation of the auditory nerve. Speech processors that extract only envelopes of the narrow-band signals (e.g., the continuous interleaved sampling (CIS) processor) may not provide sufficient information to encode the tonal cues in languages such as Chinese. To improve the performance in cochlear implant users who speak tonal language, we proposed and developed a novel speech-processing strategy, which extracted both the envelopes of the narrow-band signals and the fundamental frequency (F0) of the speech signal, and used them to modulate both the amplitude and the frequency of the electrical pulses delivered to stimulation electrodes. We developed an algorithm to extract the fundamental frequency and identified the general patterns of pitch variations of four typical tones in Chinese speech. The effectiveness of the extraction algorithm was verified with an artificial neural network that recognized the tonal patterns from the extracted F0 information. We then compared the novel strategy with the envelope-extraction CIS strategy in human subjects with normal hearing. The novel strategy produced significant improvement in perception of Chinese tones, phrases, and sentences. This novel processor with dynamic modulation of both frequency and amplitude is encouraging for the design of a cochlear implant device for sensorineurally deaf patients who speak tonal languages. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Electrical impedance tomography for imaging tissue electroporation

    Publication Year: 2004 , Page(s): 761 - 767
    Cited by:  Papers (26)  |  Patents (39)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (250 KB) |  | HTML iconHTML  

    Electroporation is a method to introduce molecules, such as gene constructs or small drugs, into cells by temporarily permeating the cell membrane with electric pulses. In molecular medicine and biotechnology, tissue electroporation is performed with electrodes placed in the target area of the body. Currently, tissue electroporation, as with all other methods of molecular medicine, is performed without real-time control or near-term information regarding the extent and degree of electroporation. This paper expands the work from our previous study by implementing new ex vivo experimental data with "front-tracking" analysis for the image reconstruction algorithm. The experimental data is incorporated into numerical simulations of electroporation procedures and images are generated using the new reconstruction algorithm to demonstrate that electrical impedance tomography (EIT) can produce an image of the electroporated area. Combining EIT with electroporation could become an important biotechnological and medical technique to introduce therapeutic molecules into cells in tissue at predetermined areas of the body. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Spatio-temporal cortical source imaging of brain electrical activity by means of time-varying parametric projection filter

    Publication Year: 2004 , Page(s): 768 - 777
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (583 KB) |  | HTML iconHTML  

    In the present study, we explore suitable spatio-temporal filters for inverse estimation of an equivalent dipole-layer distribution from the scalp electroencephalogram (EEG) for imaging of brain electric sources. We propose a time-varying parametric projection filter (tPPF) for the spatio-temporal EEG analysis. The performance of this tPPF algorithm was evaluated by computer simulation studies. An inhomogeneous three-concentric-spheres model was used in the present simulation study to represent the head volume conductor. An equivalent dipole layer was used to represent equivalently brain electric sources and estimated from the scalp potentials. The tPPF filter was tested to remove time-varying noise such as instantaneous artifacts caused by eyes-blink. The present simulation results indicate that the proposed time-variant tPPF method provides enhanced performance in rejecting time-varying noise, as compared with the time-invariant parametric projection filter. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Local contralateral subtraction based on bilateral symmetry of lung for reduction of false positives in computerized detection of pulmonary nodules

    Publication Year: 2004 , Page(s): 778 - 789
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (831 KB) |  | HTML iconHTML  

    A novel method called local contralateral subtraction has been developed for the removal of normal anatomic structures in chest radiographs based on the symmetry between the left and right lung regions. The method was oriented to the reduction of false positives reported by a computer-aided diagnosis (CAD) scheme for detection of lung nodules in chest radiographs. In our method, two regions of interest (ROIs) are extracted, one from the position where a nodule candidate is located, and the other from the anatomically corresponding location in the opposite lung, which contains similar normal structures. A wavelet-based, multiresolution image registration method is employed for matching the two ROIs, and subtraction is performed. If no structure remains in the subtracted ROI, then the original ROI is identified as negative (i.e., it contains only normal structures); otherwise, it is regarded as positive (i.e., it contains a nodule). A measure that quantifies the remaining structures was developed to distinguish between nodules and false positives. Application of the method to clinical chest radiographs showed that it was effective in eliminating normal anatomic structures and reducing the number of false detections in the CAD scheme for detection of lung nodules. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Estimating joint contact areas and ligament lengths from bone kinematics and surfaces

    Publication Year: 2004 , Page(s): 790 - 799
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (471 KB)  

    We present a novel method for modeling contact areas and ligament lengths in articulations. Our approach uses volume images generated by computed tomography and allows the in vivo and noninvasive study of articulations. In our method, bones are modeled both implicitly (scalar distance fields) and parametrically (manifold surfaces). Using this double representation, we compute interbone distances and estimate joint contact areas. Using the same types of representation, we model ligament paths; in our model, the ligaments are approximated by the shortest paths in a three-dimensional space with bone obstacles. We demonstrate the method by applying our contact area and ligament model to the distal radioulnar joints of a volunteer diagnosed with malunited distal radius fracture in one forearm. Our approach highlights focal changes in the articulation at the distal radioulnar joint (location and area of bone contact) and potential soft-tissue constraints (increased "length" of the distal ligaments and ligament-bone impingement in the injured forearm). Results suggest that the method could be useful in the study of normal and injured anatomy and kinematics of complex joints. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Automatic segmentation of thalamus from brain MRI integrating fuzzy clustering and dynamic contours

    Publication Year: 2004 , Page(s): 800 - 811
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (737 KB) |  | HTML iconHTML  

    Thalamus is an important neuro-anatomic structure in the brain. In this paper, an automated method is presented to segment thalamus from magnetic resonance images (MRI). The method is based on a discrete dynamic contour model that consists of vertices and edges connecting adjacent vertices. The model starts from an initial contour and deforms by external and internal forces. Internal forces are calculated from local geometry of the model and external forces are estimated from desired image features such as edges. However, thalamus has low contrast and discontinues edges on MRI, making external force estimation a challenge. The problem is solved using a new algorithm based on fuzzy C-means (FCM) unsupervised clustering, Prewitt edge-finding filter, and morphological operators. In addition, manual definition of the initial contour for the model makes the final segmentation operator-dependent. To eliminate this dependency, new methods are developed for generating the initial contour automatically. The proposed approaches are evaluated and validated by comparing automatic and radiologist's segmentation results and illustrating their agreement. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multichannel magnetic stimulation system design considering mutual couplings among the stimulation coils

    Publication Year: 2004 , Page(s): 812 - 817
    Cited by:  Papers (9)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (244 KB) |  | HTML iconHTML  

    We introduce some simulation and experiment results of the multichannel magnetic stimulator development that has been carried out as an initial attempt to realize a multichannel functional magnetic stimulator. For efficient functional magnetic stimulations, precise spatial localization of stimulation sites without any movements of the stimulation coils is very important. We have found that the mutual coupling effect among the adjacent stimulation coils in the coil array has to be considered in the determination of the charge voltages in some coil array configurations. Experimental results obtained with a 4-channel magnetic stimulator are presented. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Pulse oximetry theory and calibration for low saturations

    Publication Year: 2004 , Page(s): 818 - 822
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (190 KB) |  | HTML iconHTML  

    Pulse oximetry is a widely used technique in biomedical optics, but currently available pulse oximeters rely on empirical calibration approaches, which perform poorly at low saturations. We present an exact solution for pulse oximetry and show how this can be used as the basis for the development of a semi-empirical calibration approach that may be useful, especially at low saturations and variable probe geometries. This new approach was experimentally tested against traditional empirical calibration techniques on transmission pulse oximetry for monitoring of fetal sheep using a minimally invasive spiral probe. The results open the way for the development of more accurate pulse oximetry. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A closed-loop mechanical ventilation controller with explicit objective functions

    Publication Year: 2004 , Page(s): 823 - 831
    Cited by:  Papers (10)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB) |  | HTML iconHTML  

    A closed-loop lung ventilation controller was designed, aiming to: 1) track a desired end-tidal CO2 pressure (PetCO2), 2) find the positive end-expiratory pressure (PEEP) of minimum estimated respiratory system elastance (Ers,e), and 3) follow objective functions conjectured to reduce lung injury. After numerical simulations, tests were performed in six paralyzed piglets. Respiratory mechanics parameters were estimated by the recursive least squares (RLS) method. The controller incorporated a modified PI controller for PetCO2 and a gradient descent method for PEEP. In each animal, three automated PEEP control runs were performed, as well as a manual PEEP titration of Ers,e and a multiple PetCO2 step change trial. Overall performance indexes were obtained from PEEP control, such as minimum Ers,e (37.0±4.5cmH2O.L-1), time to reach the minimum Ers,e (235±182 s) and associated PEEP (6.5±1.0 cmH2O), and from PetCO2 control, such as rise time (53 ± 22 s), absolute overshoot/undershoot of PetCO2 (3±1 mmHg), and settling time (145 ± 72 s). The resulting CO2 controller dynamics approximate physiological responses, and results from PEEP control were similar to those obtained by manual titration. Multiple dependencies linking the involved variables are discussed. The present controller can help to implement and evaluate objective functions that meet clinical goals. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A fully integrated neural recording amplifier with DC input stabilization

    Publication Year: 2004 , Page(s): 832 - 837
    Cited by:  Papers (72)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (325 KB) |  | HTML iconHTML  

    This paper presents a low-power low-noise fully integrated bandpass operational amplifier for a variety of biomedical neural recording applications. A standard two-stage CMOS amplifier in a closed-loop resistive feedback configuration provides a stable ac gain of 39.3 dB at 1 kHz. A subthreshold PMOS input transistor is utilized to clamp the large and random dc open circuit potentials that normally exist at the electrode-electrolyte interface. The low cutoff frequency of the amplifier is programmable up to 50 Hz, while its high cutoff frequency is measured to be 9.1 kHz. The tolerable dc input range is measured to be at least ±0.25 V with a dc rejection factor of at least 29 dB. The amplifier occupies 0.107 mm2 in die area, and dissipates 115 μW from a 3 V power supply. The total measured input-referred noise voltage in the frequency range of 0.1-10 kHz is 7.8 μVrms. It is fabricated using AMI 1.5 μm double-poly double-metal n-well CMOS process. This paper presents full characterization of the dc, ac, and noise performance of this amplifier through in vitro measurements in saline using two different neural recording electrodes. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Three-dimensional localization of cochlear implant electrodes using epipolar stereophotogrammetry

    Publication Year: 2004 , Page(s): 838 - 846
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (312 KB) |  | HTML iconHTML  

    Three-dimensional (3-D) localization of individual cochlear implant electrodes within the inner ear is of importance for modeling the electrical field of the cochlea, designing the electrode array, and programming the associated speech processor. A 3-D reconstruction method of cochlear implant electrodes is proposed to localize individual electrodes from two X-ray views in combination with the spiral computed tomography technique. By adapting epipolar geometry to the configuration of an X-ray imaging system, we estimate individual electrode locations in the least square sense without using a patient attachment required by an existing stereophotogrammetry technique. Furthermore, our method does not require any knowledge of the intrinsic and extrinsic parameters of the imaging system. The performance of our method is studied in numerical simulation and with patient data and is found to be sufficiently accurate for clinical use. The maximum root mean-square errors measured are 0.0445 and 0.214 mm for numerical simulation and patient data, respectively. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Comparative psychometric analysis of vector and isochrone cardiac activation maps

    Publication Year: 2004 , Page(s): 847 - 855
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (406 KB) |  | HTML iconHTML  

    Isochronal cardiac activation maps can be constructed from local activation times associated with spatial locations, and are frequently used to study cardiac arrhythmias. Cardiac velocity vector mapping has been proposed as an alternative method to study cardiac activation in both clinical and research environments. Velocity vectors inherently contain more information than scalar measures of latency, but it is unknown how vector maps and isochronal maps compare when they are used to identify patterns and features associated with arrhythmias. In order to quantitatively compare these two visualization methods, eight cardiologists were asked to complete forced-choice tasks in which they selected ablation sites based on synthetic vector or isochronal maps. Maps varied in arrhythmia complexity, number of vectors or activation times included, and errors in magnitude or angle for maps of velocity vectors. Quantitative comparison was achieved by using psychometric functions to characterize the learning curve and the total number of measurements needed in order to choose a correct ablation site. For simple arrhythmias, performance with vector maps was superior to isochronal maps. Subjects required fewer measurements, and learned more rapidly by studying vector maps. For more complex arrhythmias, there was no significant difference in performance between vector and isochronal maps. However, arrhythmia features were clearer with vector maps, even though this clarity did not necessarily change the ablation site choice. When errors were added to vector maps, performance was satisfactory for angle errors <55°, and speed errors did not affect performance. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Proposed corrections for the quantification of coupling patterns by recurrence plots

    Publication Year: 2004 , Page(s): 856 - 859
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (181 KB) |  | HTML iconHTML  

    The aim of this paper is to quantify the coupling during phase-locking patterns by using the recurrence plot quantification approach. We found that the percent determinism of the recurrences and the entropy of recurrences-corrected for border effect induced by finite data length-succeeded in distinguishing three coupling conditions both in simulation signals and in real data from cardiorespiratory synchronization experiments. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Cultured neurons coupled to microelectrode arrays: circuit models, simulations and experimental data

    Publication Year: 2004 , Page(s): 859 - 863
    Cited by:  Papers (31)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (232 KB) |  | HTML iconHTML  

    The purpose of this paper is to characterize the neuron-microelectrode junction, based on the equivalent electric-circuit approach. As a result, recording of action potentials can be simulated with a general-purpose circuit simulation program such as HSPICE. The response of the microelectrode was analyzed as a function of parameters such as sealing resistance and adhesion conditions. The models of the neuron and microelectrode implemented in HSPICE were first described. These models were used to simulate the behavior of the junction between a patch of neuronal membrane (described by the compartmental model) and a microelectrode. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A novel method of estimation of DPOAE signals

    Publication Year: 2004 , Page(s): 864 - 867
    Cited by:  Papers (9)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (182 KB) |  | HTML iconHTML  

    A new method of measurement of distortion product otoacoustic emission (DPOAE) signal level based on a recently introduced nonlinear adaptive method of extraction of nonstationary sinusoids is presented. Essentially, three units of such an algorithm are employed to extract and measure the two stimuli and the DPOAE signal. Each unit has the capability of locking on a specified sinusoidal component of the input signal and tracking its variations over time. Performance of the proposed method is demonstrated with the aid of computer simulations and is verified in laboratory using recorded clinical data. Comparison is made between the proposed technique and existing methods. The proposed method features structural simplicity which renders it particularly attractive for implementation on both software and hardware platforms. It offers a high degree of immunity with regard to background noise and parameter variations. Compared to conventional methods, the proposed method offers a shorter measurement time which is of significant value in clinical examinations. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Interictal spike detection using the Walsh transform

    Publication Year: 2004 , Page(s): 868 - 872
    Cited by:  Papers (30)  |  Patents (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (210 KB) |  | HTML iconHTML  

    The objective of this study was to evaluate the feasibility of using the Walsh transformation to detect interictal spikes in electroencephalogram (EEG) data. Walsh operators were designed to formulate characteristics drawn from experimental observation, as provided by medical experts. The merits of the algorithm are: 1) in decorrelating the data to form an orthogonal basis and 2) simplicity of implementation. EEG recordings were obtained at a sampling frequency of 500 Hz using standard 10-20 electrode placements. Independent sets of EEG data recorded on 18 patients with focal epilepsy were used to train and test the algorithm. Twenty to thirty minutes of recordings were obtained with each subject awake, supine, and at rest. Spikes were annotated independently by two EEG experts. On evaluation, the algorithm identified 110 out of 139 spikes identified by either expert (True Positives=79%) and missed 29 spikes (False Negatives=21%). Evaluation of the algorithm revealed a Precision (Positive Predictive Value) of 85% and a Sensitivity of 79%. The encouraging preliminary results support its further development for prolonged EEG recordings in ambulatory subjects. With these results, the false detection (FD) rate is estimated at 7.2 FD per hour of continuous EEG recording. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Bin He
Department of Biomedical Engineering