User Training with Error Augmentation for Electromyogram-based Gesture Classification

We designed and tested a system for real-time control of a user interface by extracting surface electromyographic (sEMG) activity from eight electrodes in a wrist-band configuration. sEMG data were streamed into a machine-learning algorithm that classified hand gestures in real-time. After an initial model calibration, participants were presented with one of three types of feedback during a human-learning stage: veridical feedback, in which predicted probabilities from the gesture classification algorithm were displayed without alteration, modified feedback, in which we applied a hidden augmentation of error to these probabilities, and no feedback. User performance was then evaluated in a series of minigames, in which subjects were required to use eight gestures to manipulate their game avatar to complete a task. Experimental results indicated that, relative to baseline, the modified feedback condition led to significantly improved accuracy and improved gesture class separation. These findings suggest that real-time feedback in a gamified user interface with manipulation of feedback may enable intuitive, rapid, and accurate task acquisition for sEMG-based gesture recognition applications.Comment: 10 pages, 10 figure

Long-Distance Signals Are Required for Morphogenesis of the Regenerating Xenopus Tadpole Tail, as Shown by Femtosecond-Laser Ablation

tadpoles has recently emerged as an important model for these studies; we explored the role of the spinal cord during tadpole tail regeneration.Using ultrafast lasers to ablate cells, and Geometric Morphometrics to quantitatively analyze regenerate morphology, we explored the influence of different cell populations. For at least twenty-four hours after amputation (hpa), laser-induced damage to the dorsal midline affected the morphology of the regenerated tail; damage induced 48 hpa or later did not. Targeting different positions along the anterior-posterior (AP) axis caused different shape changes in the regenerate. Interestingly, damaging two positions affected regenerate morphology in a qualitatively different way than did damaging either position alone. Quantitative comparison of regenerate shapes provided strong evidence against a gradient and for the existence of position-specific morphogenetic information along the entire AP axis.We infer that there is a conduit of morphology-influencing information that requires a continuous dorsal midline, particularly an undamaged spinal cord. Contrary to expectation, this information is not in a gradient and it is not localized to the regeneration bud. We present a model of morphogenetic information flow from tissue undamaged by amputation and conclude that studies of information coming from far outside the amputation plane and regeneration bud will be critical for understanding regeneration and for translating fundamental understanding into biomedical approaches

Anisotropic nanomaterials: structure, growth, assembly, and functions

Comprehensive knowledge over the shape of nanomaterials is a critical factor in designing devices with desired functions. Due to this reason, systematic efforts have been made to synthesize materials of diverse shape in the nanoscale regime. Anisotropic nanomaterials are a class of materials in which their properties are direction-dependent and more than one structural parameter is needed to describe them. Their unique and fine-tuned physical and chemical properties make them ideal candidates for devising new applications. In addition, the assembly of ordered one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) arrays of anisotropic nanoparticles brings novel properties into the resulting system, which would be entirely different from the properties of individual nanoparticles. This review presents an overview of current research in the area of anisotropic nanomaterials in general and noble metal nanoparticles in particular. We begin with an introduction to the advancements in this area followed by general aspects of the growth of anisotropic nanoparticles. Then we describe several important synthetic protocols for making anisotropic nanomaterials, followed by a summary of their assemblies, and conclude with major applications

Applications of Magnetic Particle Imaging to Brain Imaging

Magnetic Particle Imaging is a novel imaging modality with many applications in the preclinical, and soon, clinical space. In particular, MPIshows promise for imaging of various brain related pathologies, such as stroke, hemmorhage, and traumatic brain injury. In this thesis, wedemonstrate a series of first-in-animal proof-of-concept experiments that MPI could soon be superior to our conventional imaging technologies, including X-ray CT, MRI, ultrasounds and nuclear medicine for particular neuroimaging applications. In the process, we will develop algorithmic enhancements to the image reconstruction of MPI signals in order to achieve real time interventional imaging, much like X-ray fluoroscopic imaging, but without ionizing radiation and significant risksof catheter and iodinated contrast media

Applications of Magnetic Particle Imaging to Brain Imaging

Magnetic Particle Imaging is a novel imaging modality with many applications in the preclinical, and soon, clinical space. In particular, MPIshows promise for imaging of various brain related pathologies, such as stroke, hemmorhage, and traumatic brain injury. In this thesis, wedemonstrate a series of first-in-animal proof-of-concept experiments that MPI could soon be superior to our conventional imaging technologies, including X-ray CT, MRI, ultrasounds and nuclear medicine for particular neuroimaging applications. In the process, we will develop algorithmic enhancements to the image reconstruction of MPI signals in order to achieve real time interventional imaging, much like X-ray fluoroscopic imaging, but without ionizing radiation and significant risksof catheter and iodinated contrast media

Data from: A convex formulation for magnetic particle imaging x-space reconstruction

Magnetic Particle Imaging (MPI) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications

HYPER localized hyperthermia – early results

In magnetic fluid hyperthermia (MFH), Magnetic Nanoparticles (MNPs) dissipate heat when exposed to alternating magnetic fields (AMF). MFH is used for targeted energy deposition for targeted drug-delivery or cancer therapy. To avoid heat deposition in all areas with high particle concentration, a gradient field featuring a field-free area (FFR) can be utilized to isolate heating a target region. In this work, we present preliminary results with a localized hyperthermia system, HYPER, that features a mechanically actuated gradient that enables adjusting the heating region’s size and position. The size of the heating region in our prototype is verified by measuring the full width at half maximum (FWHM) of the specific absorption rate (SAR) point spread function (PSF) and compared to a theoretical heating model.   Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009061, DOI: 10.18416/IJMPI.2020.200906

A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.

Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications

Novel 18650 lithium-ion battery surrogate cell design with anisotropic thermophysical properties for studying failure events

Cylindrical 18650-type surrogate cells were designed and fabricated to mimic the thermophysical properties and behavior of active lithium-ion batteries. An internal jelly roll geometry consisting of alternating stainless steel and mica layers was created, and numerous techniques were used to estimate thermophysical properties. Surrogate cell density was measured to be 1593 ± 30 kg/m3, and heat capacity was found to be 727 ± 18 J/kg-K. Axial thermal conductivity was determined to be 5.1 ± 0.6 W/m- K, which was over an order of magnitude higher than radial thermal conductivity due to jelly roll anisotropy. Radial heating experiments were combined with numerical and analytical solutions to the time-dependent, radial heat conduction equation, and from the numerical method an additional estimate for heat capacity of 805 ± 23 J/kg-K was found. Using both heat capacities and analysis techniques, values for radial thermal conductivity were between 0.120 and 0.197 W/m-K. Under normal operating conditions, relatively low radial temperature distributions were observed; however, during extreme battery failure with a hexagonal cell package, instantaneous radial temperature distributions as high as 43-71 degrees C were seen. For a vertical cell package, even during adjacent cell failure, similar homogeneity in internal temperatures were observed, demonstrating thermal anisotropy