Sensor Waveform Research Articles

Improving epilepsy localization accuracy using a 1st-order multipole beamformer

Event Abstract Back to Event Improving epilepsy localization accuracy using a 1st-order multipole beamformer Stephen Robinson1* 1 Henry Ford Hospital, Department of Psychology, Faculty of Arts and Sciences, United States Significant improvements have been made to the SAM(g2) analysis for MEG epilepsy data. Changes include substitution of a 1st-order multipole beamformer in place of a dipole beamformer, addition of an integration window stage prior to computing excess kurtosis, and compensation for frequency dependencies in computing the virtual sensor waveforms. The multipole beamformer uses a dipole plus quadrupole forward model that accounts, in part, for extended sources along the curved cortical surface. This feature is shown to improve localization accuracy such that sources are associated with the cortical mantle, increase source signal-to-noise ratio – especially for hippocampal spikes, and provide better rejection of muscle artifacts. Muscle artifacts arise from superficial extended source that had been incorrectly localized within the brain by the dipole beamformer. The multipole beamformer localizes the muscle artifact external to the skull. For each coordinate, the multipole beamformer is used to compute the estimated source waveform in a 20 to 70 Hz bandpass. A 20 ms integration window is applied to the source waveform in order to reduce sensitivity to very short transients signals. Excess kurtosis (g2) is then computed for the smoothed source waveform. An image of spikiness is generated by mapping the g2 value at 5 mm intervals, throughout the head. Next, local maxima are located within the image. These are the centroids of spikiness. Last, the source waveforms are estimated at the locations of the maxima for the entire recording bandwidth. The image and source waveforms can then be interpreted by an epileptologist. A comparison showing between the previous SAM(g2) method and the improved method demonstrates that the new method improves localization, signal-to-noise, and artifact rejection. This research was supported by NIH/NINDS Grant R01 NS30914.

A multipole beamformer for improved functional imaging of spontaneous MEG signals

Event Abstract Back to Event A multipole beamformer for improved functional imaging of spontaneous MEG signals Stephen Robinson1* and Jiri Vrba2 1 Henry Ford Hospital, United States 2 Elekta, Finland A scalar LCMV beamformer using a 1st order current multipole (dipole plus quadrupole) forward solution constraint has been developed and tested. The current multipole expansion provides a compact parametric representation of MEG signals arising from sources having significant extent over a curved cortical surface. Although the dipole model has been useful for localizing simple focal sources, it is not optimal for beamformer imaging of spontaneous MEG signals. Epileptic activity and background brain rhythms arise from sources with extent comparable to the distance to the MEG sensors. For any specified coordinate the beamformer weights are computed by first determining the moment vector that maximizes signal-to-noise ratio (SNR). This is done using a variant of Sekihara’s method, except that the dipole and quadrupole parts of the moment vector must be normalized independently in order to compute the forward solution for the scalar beamformer. This step accounts for their different physical units. All subsequent calculations of virtual sensor waveforms and functional images are derived from SNR to avoid representing activity in mixed units. We compared the multipole and dipole beamformers using simulated data and acquired MEG signals. The spatial selectivity of the multipole beamformer is nearly identical to that of the dipole beamformer for simulation of a single dipole plus noise. However, the multipole beamformer has been shown to be able to resolve two closely spaced dipole sources under conditions where the dipole beamformer could find only a single spatial peak between the sources. Using acquired MEG data the multipole beamformer is shown to localize activity closely to the cortical mantle whereas the dipole beamformer localized the same activity deeper – sometimes within the white matter. In each case, the multipole beamformer yielded higher SNR as a consequence of the improvement in modeling. This research was supported by NIH/NINDS Grant R01 NS30914. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: MEG Modeling Citation: Robinson S and Vrba J (2010). A multipole beamformer for improved functional imaging of spontaneous MEG signals. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00041 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Mar 2010; Published Online: 19 Mar 2010. * Correspondence: Stephen Robinson, Henry Ford Hospital, Detroit, United States, robinson@neurnis.neuro.hfh.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Stephen Robinson Jiri Vrba Google Stephen Robinson Jiri Vrba Google Scholar Stephen Robinson Jiri Vrba PubMed Stephen Robinson Jiri Vrba Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Dynamic Configuration of Time-Varying Waveforms for Agile Sensing and Tracking in Clutter

The advent of waveform-agile sensors has enabled the design of tracking systems where the transmitted waveform is changed on-the-fly in response to the tracker's requirements. This approach can provide performance improvements over individual optimization of the sensor waveform or the tracking algorithm. In this paper, we consider joint sensor configuration and tracking for the problem of tracking a single target in the presence of clutter using range and range-rate measurements obtained by waveform-agile, active sensors in a narrowband environment. We propose an algorithm to select and configure linear and nonlinear frequency-modulated waveforms to minimize the predicted mean square error (MSE) in the target state estimate; the MSE is predicted using the Cramer-Rao lower bound on the measurement error in conjunction with the unscented transform. We further extend our algorithm to match wideband environments, and we demonstrate the algorithm performance through a Monte Carlo simulation of a radar tracking example.

Sensor waveform assessor and its application

CAE sensor methodology development includes Sensor Waveform Assessor (SWA) development, primarily for CAE generated sensor waveform quality control and secondarily for evaluation testing. CAE restraint and safety engineers assessing CAE results for final virtual (i.e. math or CAE-based) signal approval prior to submission of sensor pulses for sensor calibrations to sensor engineers, as well as for further front impact sensor model improvement, use the SWA as a key tool in the CAE sensor implementation critical path process. Using C++, the SWA source code is generated, which allows different workstation platform-applicable executable code compilation, thus allowing program use in a Unix environment by CAE safety engineers. The authors describe the SWA's ranking criteria, underlying principles, and CAE sensor pulse evaluation applications.

Development of a unified model for sensor and crash analyses

This paper describes the development of a unified model particularly for sensor and crash analyses. Technical remarks are made for comparison of differences between a sensor and a crash model. Many useful modelling tips are given to safety analysts for use as reference in creating improved models. It is recommended that a good sensor model should be developed and calibrated using at least three crash tests at low to high velocities in rigid barrier impact and pole or Thatcham impact. All sensor signals generated by the model must be evaluated using the Sensor Waveform Assessor (SWA) to assess their quality and accuracy. Sensor pulses, once they have attained the required ranking, can then be provided to suppliers for sensing system calibration.

Leak detection in spacecraft using structure-borne noise with distributed sensors

We have developed and tested in the laboratory a method for in-orbit detection and location of air leaks in manned spacecraft that uses only a small number of sensors distributed arbitrarily on the inner surface of the spacecraft skin. Then, structure-borne ultrasound in the range of 300–600 kHz is monitored from each of the sensors. When cross correlations between measured sensor waveforms indicate the presence of a leak, these correlations are compared with a large dynamically generated database of simulated correlations to locate the the leak on the pressure vessel. A series of experimental tests were performed and at worst the method identified some false locations, but the true location of the leak always appeared.

Theoretical and Experimental Approaches to Detection of Higher Harmonic Current Component in Resin Molded Sensor for Power Factor in Power Distribution System

The authors have proposed the resin molded type of voltage-current sensor for the real time waveform observation in power distribution systems. The sensor have been designed and implemented based on the FEM, however, it was found that the current waveform will contain the remarkable high-frequency noise experimentally. The paper describes the effect of the outer noise on the current sensor waveform theoretically and experimentally.

Passive wideband cross correlation with differential Doppler compensation using the continuous wavelet transform

An estimate of the time difference for the signal emitted by a stationary source to arrive at two spatially separated sensors is given by the time displacement that maximizes the cross-correlation function. For a fast moving source, however, this estimate is found to be in error because the time scales of the received signals are different for the two sensors. The correct time delay can be extracted by evaluating the continuous wavelet transform, which has the same functional form as the wideband cross-ambiguity function. When the signal-to-noise ratio is high, the coordinates of the ambiguity surface’s global maximum provide reliable estimates of both the differential time of arrival (or time delay) and the ratio of the time scales of the signals received by the two sensors. The continuous wavelet transform is computed using the one-step chirp z-transform method, the cross-wavelet transform method, and the two-step methods where multirate sampled replicas of the sensor waveforms are cross correlated, or else the sensor waveforms are interpolated using the discrete Fourier transform prior to cross correlation. The latter method is applied to real acoustic data recorded from an orthogonal configuration of three microphones during the low-altitude transit of a jet aircraft. The resulting time delay estimates are used to calculate the variation with time of the azimuth and elevation angles of the aircraft during the transit.

Worn tool detector utilizing normalized vibration signals

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