A resistor mesh model (RMM) has been implemented to describe the electrical properties of the head and the configuration of the intracerebral current sources by simulation of forward and inverse problems in electroencephalogram/event related potential (EEG/ERP) studies. For this study, the RMM representing the three basic tissues of the human head (brain, skull and scalp) was superimposed on a spherical volume mimicking the head volume: it included 43 102 resistances and 14 123 nodes. The validation was performed with reference to the analytical model by consideration of a set of four dipoles close to the cortex. Using the RMM and the chosen dipoles, four distinct families of interpolation technique (nearest neighbour, polynomial, splines and lead fields) were tested and compared so that the scalp potentials could be recovered from the electrode potentials. The 3D spline interpolation and the inverse forward technique (IFT) gave the best results. The IFT is very easy to use when the lead-field matrix between scalp electrodes and cortex nodes has been calculated. By simple application of the Moore-Penrose pseudo inverse matrix to the electrode cap potentials, a set of current sources on the cortex is obtained. Then, the forward problem using these cortex sources renders all the scalp potentials.
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Micromachines (Basel)
December 2024
Department of Materials, Loughborough University, Loughborough LE11 3TU, UK.
Diabetic foot complications pose significant health risks, necessitating innovative approaches in orthotic design. This study explores the potential of additive manufacturing in producing functional footwear components with lattice-based structures for diabetic foot orthoses. Five distinct lattice structures (gyroid, diamond, Schwarz P, Split P, and honeycomb) were designed and fabricated using stereolithography (SLA) with varying strand thicknesses and resin types.
View Article and Find Full Text PDFInsects
April 2023
Department of Entomology & Plant Pathology, College of Agriculture and Life Sciences, NC State University, Raleigh, NC 27695, USA.
Mosquito vector-borne diseases such as malaria and dengue pose a major threat to human health. Personal protection from mosquito blood feeding is mostly by treating clothing with insecticides and the use of repellents on clothing and skin. Here, we developed a low-voltage, mosquito-resistant cloth (MRC) that blocked all blood feeding across the textile and was flexible and breathable.
View Article and Find Full Text PDFPhys Rev E
February 2023
Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
The mechanical properties of a thin, planar material, perfused by an embedded flow network, have been suggested to be potentially changeable locally and globally by fluid transport and storage, which can result in both small- and large-scale deformations such as out-of-plane buckling. In these processes, fluid absorption and storage eventually cause the material to locally swell. Different parts can hydrate and swell unevenly, prompting a differential expansion of the surface.
View Article and Find Full Text PDFPhotonic spiking neural networks (PSNNs) potentially offer exceptionally high throughput and energy efficiency compared to their electronic neuromorphic counterparts while maintaining their benefits in terms of event-driven computing capability. While state-of-the-art PSNN designs require a continuous laser pump, this paper presents a monolithic optoelectronic PSNN hardware design consisting of an MZI mesh incoherent network and event-driven laser spiking neurons. We designed, prototyped, and experimentally demonstrated this event-driven neuron inspired by the Izhikevich model incorporating both excitatory and inhibitory optical spiking inputs and producing optical spiking outputs accordingly.
View Article and Find Full Text PDFFront Comput Neurosci
August 2020
Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States.
Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn't an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution.
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