A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data from Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects
we propose a novel neurocomputing development system, called NeuCube that utilizes 3-D brain-like spiking Neural Networks (SNNs) for modelling, learning, classification and visualisation of spatiotemporal brain data for better understanding of brain functions. It is accurate in classifying EEG data and reveals new knowledge on brain functions as response to treatment of subjects addicted to drugs.
Detection Algorithm of Phase Singularity Using Phase Variance Analysis for Epicardial Optical Mapping Data
We proposed a novel detection method of cardiac spiral wave that finds the peaks in the phase variance distribution. We evaluated the proposed method in comparison with the conventional convolution method, using optical mapping data of both single spiral wave and multiple spiral waves……
A Novel Algorithm for Remote Photoplethysmography: Spatial Subspace Rotation
We propose a conceptually novel algorithm, namely “Spatial Subspace Rotation” (2SR), that improves the robustness of remote photoplethysmography. Based on the assumption of (1) spatially redundant pixel-sensors of a camera and (2) a well-defined skin mask, our core idea is to estimate a spatial subspace of skin-pixels and measure its temporal rotation for pulse extraction.
Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT
This work evaluates current 3-D image registration tools on clinically acquired abdominal computed tomography (CT) scans. Thirteen abdominal organs were manually labeled on a set of 100 CT images, and the 100 labeled images were pairwise registered based on intensity information with six registration tools (FSL, ANTS-CC, ANTS-QUICK-MI, IRTK, NIFTYREG, and DEEDS). The results suggest that DEEDS yielded the best registration performance. All data and source code are available.
Characterization of electrophysiological propagation by multichannel sensor
We evaluated the characterization of propagation of gastric slow waves recorded in multichannel biomagnetic sensors. Two analytic methods (second-order blind identification, SOBI and surface current density, SCD) were compared using a realistic abdominal model, an analytical half-layer volume conductor model and by direct magnetogastrogram measurements. We found that propagation velocity was best assessed in most situations using SOBI. SCD is more sensitive to external noise but provides increased accuracy in the case of deep sources.
Thalamic Visual Prosthesis
This review describes the advantages of creating a device that interfaces with the LGN of the thalamus for patients who have lost sight through glaucoma, the leading cause of blindness and for which no satisfactory medical treatment exists. We cover the unique advantages the structure of the LGN provides for a visual prosthesis, how neural degeneration progresses during glaucoma, and the challenge of interfacing to a structure deep in the brain.