A SQUID magnetometer system with three-dimensional(3-D) second-order gradiometer was used to measure the magnetocardiograms(MCG) for the normal subject and the patient with myocardial infarction (MI). The multiple sou...
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A SQUID magnetometer system with three-dimensional(3-D) second-order gradiometer was used to measure the magnetocardiograms(MCG) for the normal subject and the patient with myocardial infarction (MI). The multiple sources were estimated using the single current dipole model based on the 3-D MCG measurement. The difference between the normal subject and the patient with MI was discussed in the conduction pathways. It is helpful to discriminate the location and the direction of multiple sources based on combining Bz component with Bx and By components. The 3-D MCG measurement may be more efficient than the 1-D MCG measurement in estimating the multiple sources.
A SQUID magnetometer system with three-dimensional(3-D) second-order gradiometer was used to measure the magnetocardiograms(MCG) for the normal subject and the patient with myocardial infarction (MI). In order to disc...
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A SQUID magnetometer system with three-dimensional(3-D) second-order gradiometer was used to measure the magnetocardiograms(MCG) for the normal subject and the patient with myocardial infarction (MI). In order to discuss the activities of the heart between the normal subject and the patient with MI, we have presented the isoenergy contour maps to evaluate the spatial energy distribution (SED) of the QRS complex at different scale. Being different from the normal subject, the patient with MI represented different the pattern of the SED in various frequency band for the ST segment of the QRS complexof Bx , By , and Bz components. It is helpful to evaluate the patient with MI using the isoenergy contour maps of 3-D MCG.
Performing closed-loop modifications of a brain-machine interface (BMI) decoder is a technique that shows great promise for improving performance. We compare two algorithms for implementing adaptations that update dec...
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ISBN:
(纸本)9781424441211
Performing closed-loop modifications of a brain-machine interface (BMI) decoder is a technique that shows great promise for improving performance. We compare two algorithms for implementing adaptations that update decoder parameters on different time-scales (discrete batches vs. online), and present experimental results of a non-human primate performing a standard center-out BMI task. To ensure that our experimental training models are representative of a broad range of paralyzed patients, our decoders were initially trained using neural activity recorded during subject observation of cursor movement. We find that both closed-loop adaptation algorithms can be used to boost BMI performance from 20-30% to 80%, yielding movement kinematics similar to natural arm movements. Based on insights derived from the performance of each algorithm, we propose that a hybrid of batch and online decoder adaptation may be the best approach.
Many animals are known to maintain an internal estimate of their orientation in the environment. In the absence of external sensory cues, this estimate inevitably exhibits drift. When sensory information is available,...
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Many animals are known to maintain an internal estimate of their orientation in the environment. In the absence of external sensory cues, this estimate inevitably exhibits drift. When sensory information is available, associations between sensory landmarks and the internal estimate can be used to correct for drift. In this paper we present a neuromorphic system to model such associations between sensory landmarks in the environment (as provided by sonar) and the activity of a hardware-based head direction cell system (HDS) that continuously integrates angular velocity signals to maintain an estimate of the orientation. These associations are shown to correct for drift errors that are encountered in the HDS.
Brain-Machine Interface (BMI) decoding algorithms are often trained offline, but this paradigm ignores both the non-stationarity of neural signals and the feedback that exists in online, closed-loop control. To addres...
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Brain-Machine Interface (BMI) decoding algorithms are often trained offline, but this paradigm ignores both the non-stationarity of neural signals and the feedback that exists in online, closed-loop control. To address these problems, we have developed an Adaptive Kalman Filter (AKF), a Kalman filter variant that adaptively updates its model parameters during training. For a Kalman filter decoder, batch retraining methods require completely re-estimating the parameter matrices from sufficient data to perform regression accurately, even if only small changes are necessary. Conversely, the AKF is designed to update the decoder parameters continuously and more intelligently. We simulated a population of 41 neurons learning to control a 2D computer cursor. The AKF yielded significantly faster skill acquisition and better robustness to perturbation and neuron loss than a standard Kalman filter with periodic batch retraining.
Enhanced rates of oxide growth have been observed on silicon when exposed to high-energy x-ray irradiation. This observed effect could potentially be utilized for remote total ionizing dose-sensing applications.
Enhanced rates of oxide growth have been observed on silicon when exposed to high-energy x-ray irradiation. This observed effect could potentially be utilized for remote total ionizing dose-sensing applications.
We have investigated the MOVPE growth of InxGa1-xAs metamorphic buffer layer (MBL) structures with a focus on techniques to improve the surface morphology and determine the influence of morphology on subsequently grow...
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Wireless sensor networks can be used in habitat monitoring for detecting fire, in disaster for helping rescue teams and in agriculture for sensing humidity. Node localization is essential for some important sensor net...
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Wireless sensor networks can be used in habitat monitoring for detecting fire, in disaster for helping rescue teams and in agriculture for sensing humidity. Node localization is essential for some important sensor network applications. Despite the high relative accuracy of some localization algorithms, node localization is still an opened research area, due to the physical phenomena such as attenuation, reflection, diffraction, scattering and so forth. The current developed algorithms have different accuracy when are tested under dissimilar environments. We propose to use Smart Beacon Nodes (SBNs) to infer the Obstruction Level Indicator over an occupied area, then, use this indicator for estimating the distance among nodes. In our experimental simulation, SBNs decrease the node localization error of Triangular Centroid Localization and Weighted Centroid Localization up to 18%.
Poly(Ε-caprolactone) (PCL) films have been applied for vascular tissue engineering. However, few studies studied the effects of fabrication process of PCL film on vascular cell proliferation. In this study, we used d...
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ISBN:
(纸本)9781424492763
Poly(Ε-caprolactone) (PCL) films have been applied for vascular tissue engineering. However, few studies studied the effects of fabrication process of PCL film on vascular cell proliferation. In this study, we used different processing methods, incorporating stretching, to fabricate various PCL films. Thickness of films before and after stretch and proliferation ability of human fetal mesenchymal stem cells (hfMSCs) on these films were investigated. Our results showed that stretching significantly reduces the thickness of solvent cast, heat press and cast stretch films (0.22, 0.59, 0.60, p
In this paper we report for the first time the design, fabrication and characterization of an optically transparent electrode array for micro-electrocorticography. We present a 49-channel μECoG array with an electrod...
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ISBN:
(纸本)9781424441211
In this paper we report for the first time the design, fabrication and characterization of an optically transparent electrode array for micro-electrocorticography. We present a 49-channel μECoG array with an electrode pitch of 800 μm and a 16-channel linear μECoG array with an electrode pitch of 200 μm. The backing material was Parylene C. Transparent, sputtered indium tin oxide (ITO) was used in conjunction with e-beam evaporated gold to fabricate the electrodes. We provide electrochemical impedance characterization and light transmission data for the fabricated devices.
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