Showing papers in "IEEE Transactions on Biomedical Engineering in 1997"
TL;DR: This paper presents a development and analysis of the spatial filtering method for localizing sources of brain electrical activity from surface recordings and explores its sensitivity to deviations between actual and assumed data models.
Abstract: A spatial filtering method for localizing sources of brain electrical activity from surface recordings is described and analyzed. The spatial filters are implemented as a weighted sum of the data recorded at different sites. The weights are chosen to minimize the filter output power subject to a linear constraint. The linear constraint forces the filter to pass brain electrical activity from a specified location, while the power minimization attenuates activity originating at other locations. The estimated output power as a function of location is normalized by the estimated noise power as a function of location to obtain a neural activity index map. Locations of source activity correspond to maxima in the neural activity index map. The method does not require any prior assumptions about the number of active sources of their geometry because it exploits the spatial covariance of the source electrical activity. This paper presents a development and analysis of the method and explores its sensitivity to deviations between actual and assumed data models. The effect on the algorithm of covariance matrix estimation, correlation between sources, and choice of reference is discussed. Simulated and measured data is used to illustrate the efficacy of the approach.
2,313 citations
TL;DR: Preliminary evaluation of the system in 13 male subjects during standardized activities in the laboratory demonstrated a significant relationship between accelerometer output and energy expenditure due to physical activity, the standard reference for physical activity.
Abstract: The present study describes the development of a triaxial accelerometer (TA) and a portable data processing unit for the assessment of daily physical activity. The TA is composed of three orthogonally mounted uniaxial piezoresistive accelerometers and can be used to register accelerations covering the amplitude and frequency ranges of human body acceleration. Interinstrument and test-retest experiments showed that the offset and the sensitivity of the TA were equal for each measurement direction and remained constant on two measurement days. Transverse sensitivity was significantly different for each measurement direction, but did not influence accelerometer output (<3% of the sensitivity along the main axis). The data unit enables the on-line processing of accelerometer output to a reliable estimator of physical activity over eight-day periods. Preliminary evaluation of the system in 13 male subjects during standardized activities in the laboratory demonstrated a significant relationship between accelerometer output and energy expenditure due to physical activity, the standard reference for physical activity (r=0.89). Shortcomings of the system are its low sensitivity to sedentary activities and the inability to register static exercise. The validity of the system for the assessment of normal daily physical activity and specific activities outside the laboratory should be studied in free-living subjects.
951 citations
TL;DR: A "mixture-of-experts" (MOE) approach to develop customized electrocardiogram (EGG) beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care.
Abstract: Presents a "mixture-of-experts" (MOE) approach to develop customized electrocardiogram (EGG) beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. A small customized classifier is developed based on brief, patient-specific ECG data. It is then combined with a global classifier, which is tuned to a large ECG database of many patients, to form a MOE classifier structure. Tested with MIT/BIH arrhythmia database, the authors observe significant performance enhancement using this approach.
610 citations
TL;DR: By combining power spectrum estimation, principal component analysis and artificial neural networks, the authors show that continuous, accurate, noninvasive, and near real-time estimation of an operator's global level of alertness is feasible using EEC; measures recorded from as few as two central scalp sites.
Abstract: In tasks requiring sustained attention, human alertness varies on a minute time scale. This can have serious consequences in occupations ranging from air traffic control to monitoring of nuclear power plants. Changes in the electroencephalographic (EEG) power spectrum accompany these fluctuations in the level of alertness, as assessed by measuring simultaneous changes in EEG and performance on an auditory monitoring task. By combining power spectrum estimation, principal component analysis and artificial neural networks, the authors show that continuous, accurate, noninvasive, and near real-time estimation of an operator's global level of alertness is feasible using EEC; measures recorded from as few as two central scalp sites. This demonstration could lead to a practical system for noninvasive monitoring of the cognitive state of human operators in attention-critical settings.
504 citations
TL;DR: Modelers of electrical sources in the human brain have underestimated human CSF conductivity by as much as 44% for nearly two decades, and this should be corrected to increase the accuracy of source localization models.
Abstract: The electrical conductivity of human cerebrospinal fluid (CSF) from seven patients was measured at both room temperature (25/spl deg/C) and body temperature (37/spl deg/C). Across the frequency range of 10 Hz-10 kHz, room temperature conductivity was 1.45 S/m, but body temperature conductivity was 1.79 S/m, approximately 23% higher. Modelers of electrical sources in the human brain have underestimated human CSF conductivity by as much as 44% for nearly two decades, and this should be corrected to increase the accuracy of source localization models.
465 citations
TL;DR: Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECGs are clinically useful.
Abstract: Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful.
445 citations
TL;DR: This paper deals with the identification of the optimal cluster position and orientation on the limb aimed at the minimization of error propagation to anatomical landmark laboratory coordinates.
Abstract: When three-dimensional (3-D) human or animal movement is recorded using a photogrammetric system, bone-embedded frame positions and orientations are estimated from reconstructed surface marker trajectories using either nonoptimal or optimal algorithms. The effectiveness of these mathematical procedures in accommodating for both photogrammetric errors and skin movement artifacts depends on the number of markers associated with a given bone as well as on the size and shape characteristics of the relevant cluster. One objective of this paper deals with the identification of marker cluster design criteria aimed at the minimization of error propagation from marker coordinates to bone-embedded frame position and orientation. Findings allow for the quantitative estimation of these errors for any given cluster configuration and suggest the following main design criteria. A cluster made up of four markers represents a good practical compromise. Planar clusters are acceptable, provided in quasi-isotropic distribution. The root mean square distance of the markers from their centroid should be greater than ten times the standard deviation of the marker position error. The second objective of this paper deals with the identification of the optimal cluster position and orientation on the limb aimed at the minimization of error propagation to anatomical landmark laboratory coordinates. Cluster position should be selected to minimize skin movement artifacts. The longest principal axis of the marker distribution should be oriented toward the relevant anatomical landmark position.
441 citations
TL;DR: It is concluded that reflex stiffness can be large enough to be important functionally, but that its effects will depend strongly upon the particular conditions.
Abstract: The authors have examined dynamic stiffness at the human ankle using position perturbations which were designed to provide a wide-bandwidth input with low average velocity. A parallel-cascade, nonlinear system identification technique was used to separate overall stiffness into intrinsic and reflex components. Intrinsic stiffness was described by a linear, second-order system similar to that demonstrated previously. Reflex stiffness dynamics were more complex, comprising a delay, a unidirectional rate-sensitive element and then lowpass dynamics. Reflex mechanisms were found to be most important at frequencies of 5-10 Hz. The gain and dynamics of reflex stiffness varied strongly with the parameters of the perturbation, the gain decreasing as the mean velocity of the perturbation increased. Under some conditions, torques generated by reflex mechanisms were of the same magnitude as those from intrinsic mechanisms. It is concluded that reflex stiffness can be large enough to be important functionally, but that its effects will depend strongly upon the particular conditions.
412 citations
TL;DR: A new approach to the recovering of dipole magnitudes in a distributed source model for magnetoencephalographic (MEG) and electroencephalography (EEG) imaging is presented, introducing spatial and temporal a priori information as a cure to this ill-posed inverse problem.
Abstract: We present a new approach to the recovering of dipole magnitudes in a distributed source model for magnetoencephalographic (MEG) and electroencephalographic (EEG) imaging. This method consists in introducing spatial and temporal a priori information as a cure to this ill-posed inverse problem. A nonlinear spatial regularization scheme allows the preservation of dipole moment discontinuities between some a priori noncorrelated sources, for instance, when considering dipoles located on both sides of a sulcus. Moreover, we introduce temporal smoothness constraints on dipole magnitude evolution at time scales smaller than those of cognitive processes. These priors are easily integrated into a Bayesian formalism, yielding a maximum a posteriori (MAP) estimator of brain electrical activity. Results from EEG simulations of our method are presented and compared with those of classical quadratic regularization and a now popular generalized minimum-norm technique called low-resolution electromagnetic tomography (LORETA).
364 citations
TL;DR: The aim of this paper is to examine the influence of tissue resistivity changes on the neuromagnetic field and the electric scalp potential, using a high-resolution finite element method of the human head with 13 different tissue types.
Abstract: Modeling in magnetoencephalography (MEG) and electroencephalography (EEG) requires knowledge of the in vivo tissue resistivities of the head. The aim of this paper is to examine the influence of tissue resistivity changes on the neuromagnetic field and the electric scalp potential. A high-resolution finite element method (FEM) model (452162 elements, 2-mm resolution) of the human head with 13 different tissue types is employed for this purpose. Our main finding was that the magnetic fields are sensitive to changes in the tissue resistivity in the vicinity of the source. In comparison, the electric surface potentials are sensitive to changes in the tissue resistivity in the vicinity of the source and in the vicinity of the position of the electrodes. The magnitude (strength) of magnetic fields and electric surface potentials is strongly influenced by tissue resistivity changes, while the topography is not as strongly influenced. Therefore, an accurate modeling of magnetic field and electric potential strength requires accurate knowledge of tissue resistivities, while for source localization procedures this knowledge might not be a necessity.
314 citations
TL;DR: The extraction of fetal electrocardiogram (ECG) from the composite maternal ECG signal obtained from the abdominal lead is discussed, and the proposed method employs singular value decomposition (SVD) and analysis based on the singular value ratio (SVR) spectrum.
Abstract: The extraction of fetal electrocardiogram (ECG) from the composite maternal ECG signal obtained from the abdominal lead is discussed. The proposed method employs singular value decomposition (SVD) and analysis based on the singular value ratio (SVR) spectrum. The maternal ECG (M-ECG) and the fetal ECG (F-ECG) components are identified in terms of the SV-decomposed modes of the appropriately configured data matrices, and elimination of the M-ECG and determination of F-ECG are achieved through selective separation of the SV-decomposed components. The unique feature of the method is that only one composite maternal ECG signal is required to determine the P-ECG component. The method is numerically robust and computationally efficient.
TL;DR: Describes the design, fabrication, and output capabilities of a microminiature electrical stimulator that can be injected in or near nerves and muscles and used successfully for chronic stimulation in hindlimb muscles of cats.
Abstract: Describes the design, fabrication, and output capabilities of a microminiature electrical stimulator that can be injected in or near nerves and muscles. Each single channel microstimulator consists of a cylindrical glass capsule with hermetically sealed electrodes in either end (2-mm diameter/spl times/13-mm overall length). Power and digital control data can be transmitted to multiple implants (256 unique addresses) via a 2-MHz RF field created by an external AM oscillator and inductive coil. In vitro testing demonstrated accurate control of output pulsewidth (3-258 /spl mu/s in 1-/spl mu/s steps) and current (0-30 mA in two linear ranges of 16 steps each, up to 8.5 V available compliance voltage). Microstimulators were used successfully for chronic stimulation in hindlimb muscles of cats. Design and fabrication issues affecting yield and reliability of the packaging and electronics are discussed.
TL;DR: A bulk-micromachined multichannel silicon probe capable of selectively delivering chemicals at the cellular level as well as electrically recording from and stimulating neurons in vivo has been developed and a shutter is proposed for chronic use.
Abstract: A bulk-micromachined multichannel silicon probe capable of selectively delivering chemicals at the cellular level as well as electrically recording from and stimulating neurons in vivo has been developed. The process buries multiple flow channels in the probe substrate, resulting in a hollow-core device, Microchannel formation requires only one mask in addition to those normally used for probe fabrication and is compatible with on-chip signal-processing circuitry. Flow in these microchannels has been studied theoretically and experimentally. For an effective channel diameter of 10 /spl mu/m, a channel length of 4 mm, and water as the injected fluid, the flow velocity at 11 torr is about 1.3 mm/s, delivering 100 pl in 1 s. Intermixing of chemicals, with the tissue fluid due to natural diffusion through the outlet orifice becomes significant for dwell times in excess of about 30 min, and a shutter is proposed for chronic use. The probe has been used for acute monitoring of the neural responses to various chemical stimuli in guinea pig superior and inferior colliculus.
TL;DR: The design, test methods, and results of an ambulatory QRS detector are presented and the aim of the design work was to achieve high QRS detection performance in terms of timing accuracy and reliability, without compromising the size and power consumption of the device.
Abstract: The design, test methods, and results of an ambulatory QRS detector are presented. The device is intended for the accurate measurement of heart rate variability (HRV) and reliable QRS detection in both ambulatory and clinical use. The aim of the design work was to achieve high QRS detection performance in terms of timing accuracy and reliability, without compromising the size and power consumption of the device. The complete monitor system consists of a host computer and the detector unit. The detector device is constructed of a commonly available digital signal processing (DSP) microprocessor and other components. The QRS detection algorithm uses optimized prefiltering in conjunction with a matched filter and dual edge threshold detection. The purpose of the prefiltering is to attenuate various noise components in order to achieve improved detection reliability. The matched filter further improves signal-to-noise ratio (SNR) and symmetries the QRS complex for the threshold detection, which is essential in order to achieve the desired performance. The decision for detection is made in real-time and no search-back method is employed. The host computer is used to configure the detector unit, which includes the setting of the matched filter impulse response, and in the retrieval and postprocessing of the measurement results. The QRS detection timing accuracy and detection reliability of the detector system was tested with an artificially generated electrocardiogram (EGG) signal corrupted with various noise types and a timing standard deviation of less than 1 ms was achieved with most noise types and levels similar to those encountered in real measurements. A QRS detection error rate (ER) of 0.1 and 2.2% was achieved with records 103 and 105 from the MIT-BIH Arrhythmia database, respectively.
TL;DR: Patient-specific classifiers to detect seizure onsets are designed and shown to be effective and reasonably reliable during long-term EEG monitoring of epileptic patients.
Abstract: During long-term electroencephalogram (EEG) monitoring of epileptic patients, a seizure warning system would allow patients and observers to take appropriate precautions. It would also allow observers to interact with patients early during the seizure, thus revealing clinically useful information. We designed patient-specific classifiers to detect seizure onsets. After a seizure and some nonseizure data are recorded in a patient, they are used to train a classifier. In subsequent monitoring sessions, EEG patterns have to pass this classifier to determine if a seizure onset occurs. If it does, an alarm is triggered. Extreme care has been taken to ensure a low false-alarm rate, since a high false-alarm rate would render the system ineffective. Features were extracted from the time and frequency domains and a modified nearest-neighbor (NN) classifier was used. The system reached an onset detection rate of 100% with an average delay of 9.35 s after onset. The average false-alarm rate was only 0.02/h. The method was evaluated in 12 patients with a total of 47 seizures. Results indicate that the system is effective and reasonably reliable. Computation load has been kept to a minimum so that real-time processing is possible.
TL;DR: Electrical conductivities in the bidomain model of cardiac tissue are expressed as functions of four parameters, which allow simulations to be performed using nominal, equal, and reciprocal anisotropy without introducing undesired effects, such as length constant variations.
Abstract: Electrical conductivities in the bidomain model of cardiac tissue are expressed as functions of four parameters. These expressions allow simulations to be performed using nominal, equal, and reciprocal anisotropy without introducing undesired effects, such as length constant variations. Relative values of the bidomain conductivities are estimated to be: /spl sigma//sub iL/=1, /spl sigma//sub iT/=0.1, /spl sigma//sub eL/=1, and /spl sigma//sub eT/=0.4.
TL;DR: Noninvasive images of the myocardial activation sequence are acquired, based on a new formulation of the inverse problem of electrocardiography in terms of the critical points of the ventricular surface activation map, and it is shown that the method is stable with respect to substantial amounts of correlated noise.
Abstract: Noninvasive images of the myocardial activation sequence are acquired, based on a new formulation of the inverse problem of electrocardiography in terms of the critical points of the ventricular surface activation map. It is shown that the method is stable with respect to substantial amounts of correlated noise common in the measurements and modeling of electrocardiography and that problems associated with conventional regularization techniques can be circumvented. Examples of application of the method to measured human data are presented. This first invasive validation of results compares well to previously published results obtained by using a standard approach. The method can provide additional constraints on, and thus improve, traditional methods aimed at solving the inverse problem of electrocardiography.
TL;DR: The single-channel implantable microstimulator device measures 2/spl times/2/ spl times/10 mm/sup 3/ and can be inserted into paralyzed muscle groups by expulsion from a hypodermic needle.
Abstract: The single-channel implantable microstimulator device measures 2/spl times/2/spl times/10 mm/sup 3/ and can be inserted into paralyzed muscle groups by expulsion from a hypodermic needle. Power and data to the device are supplied from outside by RF telemetry using an amplitude-modulated 2-MHz RF carrier generated using a high-efficiency class-E transmitter. The transmitted signal carries a 5-b address which selects one of the 32 possible microstimulators. The selected device then delivers up to 2 /spl mu/C of charge stored in a tantalum chip capacitor for up to 200 /spl mu/s (10 mA) into loads of <800 /spl Omega/ through a high-current thin-film iridium-oxide (IrO/sub x/) electrode (/spl sim/0.3 mm/sup 2/ in area). A bi-CMOS receiver circuitry is used to: generate two regulated voltage supplies (4.5 and 9 V), recover a 2-MHz clock from the carrier, demodulate the address code, and activate the output current delivery circuitry upon the reception of an external command. The overall power dissipation of the receiver circuitry is 45-55 mW. The implant is hermetically packaged using a custom-made glass capsule.
TL;DR: The purpose of this study was to develop a device with the following design criteria: lightweight, easy attachment, little hindrance to the natural gait pattern, sufficient memory to record for one day, and practicality in clinical use.
Abstract: Long-term monitoring of stride length and walking velocity is considered to provide useful information for making decisions on treatment of patients with gait disabilities. The purpose of this study was to develop a device with the following design criteria: lightweight, easy attachment, little hindrance to the natural gait pattern, sufficient memory to record for one day, and practicality in clinical use. The prototype consists of a piezoelectric gyroscope, which detects angular velocity of the thigh of one leg in the sagittal plane, and a microprocessor-based maximum/minimum detector/data logger of a cyclic analog signal associated with the gait cycle. The accuracy of the device was evaluated in 20 normal subjects, seven above-the-knee (A/K) amputees, and ten hemiplegic patients, and relative accuracy within /spl plusmn/15% was obtained, except for two special cases.
TL;DR: A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in terms of classification and quantification of different oscillating mechanisms.
Abstract: A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in terms of classification and quantification of different oscillating mechanisms. For this purpose, a class of MV dynamic adjustment (MDA) models in which a MV autoregressive (MAR) network of causal interactions is fed by uncorrelated autoregressive (AR) processes is defined. Poles relevant to the MAR network closed-loop interactions (cl-poles) and poles relevant to each AR input are disentangled and accordingly classified. The autospectrum of each channel can be divided into partial spectra each relevant to an input. Each partial spectrum is affected by the cl-poles and by the poles of the corresponding input; consequently, it is decomposed into the relevant components by means of the residual method. Therefore, different oscillating mechanisms, even at similar frequencies, are classified by different poles and quantified by the corresponding components. The structure of MDA models is quite flexible and can be adapted to various sets of available signals and a priori hypotheses about the existing interactions; a graphical layout is proposed that emphasizes the oscillation sources and the corresponding closed-loop interactions. Application examples relevant to cardiovascular variability are briefly illustrated.
TL;DR: Electroencephalograph (EEG) and Holter EEG data compression techniques which allow perfect reconstruction of the recorded waveform from the compressed one are presented and discussed and the adoption of a collapsed Huffman tree for the encoding/decoding operations is shown.
Abstract: Electroencephalograph (EEG) and Holter EEG data compression techniques which allow perfect reconstruction of the recorded waveform from the compressed one are presented and discussed. Data compression permits one to achieve significant reduction in the space required to store signals and in transmission time. The Huffman coding technique in conjunction with derivative computation reaches high compression ratios (on average 49% on Holter and 58% on EEG signals) with low computational complexity. By exploiting this result a simple and fast encoder/decoder scheme capable of real-time performance on a PC was implemented. This simple technique is compared with other predictive transformations, vector quantization, discrete cosine transform (DCT), and repetition count compression methods. Finally, it is shown that the adoption of a collapsed Huffman tree for the encoding/decoding operations allows one to choose the maximum codeword length without significantly affecting the compression ratio. Therefore, low cost commercial microcontrollers and storage devices can be effectively used to store long Holter EEG's in a compressed format.
TL;DR: It is postulated that the most repeatable and stable accuracy of the pulse oximeter occurs when the fractional change in photon path lengths due to perturbations in the tissue (relative to the conditions present during system calibration) is equivalent at the two wavelengths.
Abstract: Conventional pulse oximeters are accurate at high oxygen saturation under a variety of physiological conditions but show worsening accuracy at lower saturation (below 70%). Numerical modeling suggests that sensors fabricated with 735 and 890 nm emitters should read more accurately at low saturation under a variety of conditions than sensors made with conventionally used 660 and 900 nm band emitters. Recent animal testing confirms this expectation. It is postulated that the most repeatable and stable accuracy of the pulse oximeter occurs when the fractional change in photon path lengths due to perturbations in the tissue (relative to the conditions present during system calibration) is equivalent at the two wavelengths. Additionally, the penetration depth (and/or breadth) of the probing light needs to be well matched at the two wavelengths in order to minimize the effects of tissue heterogeneity. At high saturation these conditions are optimally met with 660 and 900 nm band emitters, while at low saturation 735 and 890 nm provide better performance.
TL;DR: The simulations show that an isotropic spatial filtering procedure reduces the spatial extension of the filter response and improves the spatial resolution of the electromyography-recording arrangement in comparison to anisotropic spatial filters up to 30%, which increases the spatial selectivity of the arrangement.
Abstract: In the present study, different isotropic and anisotropic filters have been compared by means of theoretical field simulations and experiments in volunteers. A tripole model for an excited motor unit (MU) was used as the basis for simulating the spatial extension of the filter response for each of the investigated filters. The spatial extension is an indicative of the spatial resolution. For the experimental validation, the total number of single motor units was not directly investigated, but the signal-to-noise ratio (SNR) has been determined. Therefore, the potential distribution generated on the skin surface during maximum voluntary contraction has been simultaneous spatially filtered with each of the investigated filters. The simulations show that an isotropic spatial filtering procedure reduces the spatial extension of the filter response and improves the spatial resolution of the electromyography (EMG)-recording arrangement in comparison to anisotropic spatial filters up to 30%. In other words, the spatial selectivity of the arrangement is increased. This improvement in the filter performance is more pronounced for MU's located close to the skin surface than for MU's more distantly located. Additionally, this theoretical improvement in selectivity depends on the direction of the excitation spread relative to the filter alignment. However, the investigations also show that isotropic filters offer an advantage, compared to anisotropic filters, only when the investigated MU is located extremely close to the filter input. The results of the simulations can be confirmed by the experimental investigations. An improvement of 11% in the SNR, relative to anisotropic spatial filters, can be established when using an isotropic spatial filter. This experimental improvement in selectivity is less than the theoretical improvement because the experimentally investigated MU's have less portion in the anisotropic range of the filters than the simulated one at best.
TL;DR: This research developed a technique to excite selectively nerve fibers distant from an electrode without exciting nerve fibers close to the electrode through subthreshold depolarization, which inverted the current-distance relationship and allowed selective stimulation of nerve fibers far from the electrode.
Abstract: The objective of this research was to develop a technique to excite selectively nerve fibers distant from an electrode without exciting nerve fibers close to the electrode. The shape of the stimulus current waveform was designed based on the nonlinear conductance properties of neuronal sodium channels. Models of mammalian peripheral myelinated axons and experimental measurements on cat sciatic nerve were used to determine the effects of subthreshold polarization on neural excitability and recruitment. Subthreshold membrane depolarization generated a transient decrease in neural excitability and thus an increase in the threshold for stimulation by a subsequent stimulus pulse. The decrease in excitability increased as the duration and amplitude of the subthreshold depolarization were increased, and the increase in threshold was greater for fibers close to the electrode. When a depolarizing stimulus pulse was applied immediately after the subthreshold depolarization, nerve fibers far from the electrode could be stimulated without stimulating fibers close to the electrode. Subthreshold depolarizing prepulses inverted the current-distance relationship and allowed selective stimulation of nerve fibers far from the electrode.
TL;DR: The localization of measurement sensitivity using these techniques was evaluated quantitatively in an inhomogeneous spherical head model using a new concept called half-sensitivity volume (HSV), and it is shown that the planar gradiometers has a far smaller HSV than the axial gradiometer.
Abstract: It is generally believed that because the skull has low conductivity to electric current but is transparent to magnetic fields, the measurement sensitivity of the magnetoencephalography (MEG) in the brain region should be more concentrated than that of the electroencephalography (EEG). It is also believed that the information recorded by these techniques is very different. If this were indeed the case, it might be possible to justify the cost of MEG instrumentation which is at least 25 times higher than that of EEG instrumentation. The localization of measurement sensitivity using these techniques was evaluated quantitatively in an inhomogeneous spherical head model using a new concept called half-sensitivity volume (HSV). It is shown that the planar gradiometer has a far smaller HSV than the axial gradiometer. However, using the EEG it is possible to achieve even smaller HSVs than with whole-head planar gradiometer MEG devices. The micro-superconducting quantum interference device (SQUID) MEG device does have HSVs comparable to those of the EEG. The sensitivity distribution of planar gradiometers, however, closely resembles that of dipolar EEG leads and, therefore, the MEG and EEG record the electric activity of the brain in a very similar way.
TL;DR: A connectionist neural network was applied to the spike sorting challenge and performed as well as the MTF in identifying nonoverlapping spikes, and was significantly better in resolving superpositions and rejecting noise.
Abstract: Determination of single-unit spike trains from multiunit recordings obtained during extracellular recording has been the focus of many studies over the last two decades. In multiunit recordings, superpositions can occur with high frequency if the firing rates of the neurons are high or correlated, making superposition resolution imperative for accurate spike train determination. In this work, a connectionist neural network (NN) was applied to the spike sorting challenge. A novel training scheme was developed which enabled the NN to resolve some superpositions using single-channel recordings. Simulated multiunit spike trains were constructed from templates and noise segments that were extracted from real extracellular recordings. The simulations were used to determine the performances of the NN and a simple matched template filter (MTF), which was used as a basis for comparison. The network performed as well as the MTF in identifying nonoverlapping spikes, and was significantly better in resolving superpositions and rejecting noise. An on-line, real-time implementation of the NN discriminator, using a high-speed digital signal processor mounted inside an IBM-PC, is now in use in six laboratories.
TL;DR: A polarimetric glucose sensor utilizing a digital closed-loop controller was designed and implemented and evaluated in vitro for both glucose doped water and bovine aqueous humor mediums in order to further improve system repeatability and stability without sacrificing accuracy.
Abstract: A polarimetric glucose sensor utilizing a digital closed-loop controller was designed and implemented during this study. Its potential as a noninvasive glucose sensor was evaluated in vitro for both glucose doped water and bovine aqueous humor mediums. A physiological hyperglycemic concentration range was used in both calibration and validation of each set of experiments. Ideally, the end application of this system could estimate blood glucose concentrations indirectly by measuring the amount of rotation of a light beam's polarization state after it propagates through the aqueous humor contained within the anterior chamber of the eye. The polarimeter designed in this study differs from similar investigated systems in that it utilizes a digital closed-loop control system. This type of controller was implemented in order to further improve system repeatability and stability without sacrificing accuracy. Unique to this investigation, independent validation sets other than those used to create each respective calibration model were obtained. The results of the glucose-doped water experiments yielded mean standard errors of prediction for calibration and validation of 6.91 and 8.84 mg/dl, respectively. The mean standard errors of prediction during calibration and validation of the glucose-doped aqueous humor experiments were higher at 27.20 and 27.47 mg/dl, respectively, due to medium degradation over time while exposed to air.
TL;DR: The proposed algorithm combines multiresolution analysis with hard thresholding in order to compose a wavelet transform-based stationary-nonstationary filter (WTST-NST), which performed more accurately, objectively, and with lower computational cost than other separation tools.
Abstract: The separation of pathological discontinuous adventitious sounds (DAS) from vesicular sounds (VS) is of great importance to the analysis of lung sounds, since DAS are related to certain pulmonary pathologies. An automated way of revealing the diagnostic character of DAS by isolating them from VS, based on their nonstationarity, is presented in this paper. The proposed algorithm combines multiresolution analysis with hard thresholding in order to compose a wavelet transform-based stationary-nonstationary filter (WTST-NST). Applying the WTST-NST filter to fine/coarse crackles and squawks, selected from three lung sound databases, the coherent structure of DAS is revealed and they are separated from VS. When compared to other separation tools, the WTST-NST filter performed more accurately, objectively, and with lower computational cost. Due to its simple implementation it can easily be used in clinical medicine.
TL;DR: The significant feature of the proposed technique is that, while the error is nearly uniform throughout the cycle, the diagnostically crucial QRS region is kept free of maximal reconstruction error.
Abstract: Presents a novel coding scheme for the electrocardiogram (ECG). Following beat delineation, the periods of the beats are normalized by multirate processing. After amplitude normalization, a discrete wavelet transform is applied to each beat. Due to the period and amplitude normalization, the wavelet transform coefficients bear a high correlation across beats at identical locations. To increase the compression ratio, the residual sequence obtained after linear prediction of the significant wavelet coefficients is transmitted to the decoder. The difference between the actual period and the mean beat period, and that between the actual scale factor and the average amplitude scale factor are also transmitted for each beat. At the decoder, the inverse wavelet transform is computed from the reconstructed wavelet transform coefficients. The original amplitude and period of each beat are then recovered. The approximation achieved, at an average rate of 180 b/s, is of high quality. The authors have evaluated the normalized maximum amplitude error and its position in each cycle, in addition to the normalized root mean square error. The significant feature of the proposed technique is that, while the error is nearly uniform throughout the cycle, the diagnostically crucial QRS region is kept free of maximal reconstruction error.
TL;DR: The results of this study suggest that accurate representation of tissue inhomogeneity has a significant effect on the accuracy of the forward solution, with regions near the torso surface playing a larger role, in general, than those near the heart.
Abstract: The aim of this study was to quantify the effects of selected inhomogeneities and anisotropies on computed electric potential fields associated with the electrocardiographic forward problem. The model construction was based on the Utah Torso model and included geometry for major anatomical structures such as subcutaneous fat, skeletal muscle, and lungs, as well as for epicardial fatpads, major arteries and veins, and the sternum, ribs, spine, and clavicles. Measured epicardial potentials served as the electrical source for solutions to the electrocardiographic forward problem computed using the finite element method (FEM). The geometry of the torso model for each simulation was constant, but different combinations of conductivities were assigned to individual organs or tissues. Comparisons of different conductivity combinations followed one of two basic schemes: 1) a homogeneous torso served as the reference against which we compared simulations with a single organ or tissue and assigned its nominal conductivity, or 2) a fully inhomogeneous torso served as the reference and we removed the effect of individual organs or tissues by assigning it the homogeneous conductivity value. When single inhomogeneities were added to an otherwise homogeneous isotropic model, anisotropic skeletal muscle (at a 15:1 anisotropy ratio) and the right and left lung had larger average effects (12.8, 12.7, and 12.1% relative error (RE), respectively) than the other inhomogeneities tested. Our results for removing single inhomogeneities show that the subcutaneous fat, the anisotropic skeletal muscle (with the degree of anisotropy equal to 7:1), and the lungs have larger average impacts on the body surface potential distributions than other elements of the model (with values of 14.9, 12.6, and 11.7% RE, respectively). The results also show that the size of the effect depended strongly on the distribution of epicardial potentials. The results of this study suggest that accurate representation of tissue inhomogeneity has a significant effect on the accuracy of the forward solution, with regions near the torso surface playing a larger role, in general, than those near the heart.