Patents by Inventor Daniel Faul

Daniel Faul has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10433752
    Abstract: The present invention relates to a method for the real-time identification of seizures in an Electroencephalogram (EEG) signal. The method provides for patient-independent seizure identification by use of a multi-patient trained generic Support Vector Machine (SVM) classifier. The SVM classifier is operates on a large feature vector combining features from a wide variety of signal processing and analysis techniques. The method operates sufficiently accurately to be suitable for use in a clinical environment. The method may also be combined with additional classifiers, such a Gaussian Mixture Model (GMM) classifier, for improved robustness, and one or more dynamic classifiers such as an SVM using sequential kernels for improved temporal analysis of the EEG signal.
    Type: Grant
    Filed: April 7, 2010
    Date of Patent: October 8, 2019
    Assignee: National University of Ireland
    Inventors: Stephen Daniel Faul, Andriy Temko, William Peter Marnane, Gordon Lightbody, Geraldine Bernadette Boylan
  • Publication number: 20120101401
    Abstract: The present invention relates to a method for the real-time identification of seizures in an Electroencephalogram (EEG) signal. The method provides for patient-independent seizure identification by use of a multi-patient trained generic Support Vector Machine (SVM) classifier. The SVM classifier is operates on a large feature vector combining features from a wide variety of signal processing and analysis techniques. The method operates sufficiently accurately to be suitable for use in a clinical environment. The method may also be combined with additional classifiers, such a Gaussian Mixture Model (GMM) classifier, for improved robustness, and one or more dynamic classifiers such as an SVM using sequential kernels for improved temporal analysis of the EEG signal.
    Type: Application
    Filed: April 7, 2010
    Publication date: April 26, 2012
    Applicant: National University of Ireland
    Inventors: Stephen Daniel Faul, Andrly Temko, William Peter Marnane, Gordon Lightbody, Geraldine Bernadette Boylan
  • Publication number: 20060019074
    Abstract: A printed article including a substrate having a top surface and a bottom surface with a reflective layer printed on a surface of the substrate, a graphic design layer printed on the reflective layer, a textured pattern of transparent ink printed over the graphic design and reflective layer, and a transparent layer of uniform gloss printed over (or directly under the texture pattern if the gloss level of the transparent layer of uniform gloss matches the gloss level of the texture pattern) the textured pattern. This transparent layer of uniform gloss printed over the texture printing (or a matching gloss level under the texture printing) is such that the texture printing is not distinct from the non texture printed areas and the image appears to be embossed to the human eye. The textured pattern includes a plurality of light bending convex lines of transparent ink printed on and around the graphic image and reflective layers.
    Type: Application
    Filed: September 23, 2005
    Publication date: January 26, 2006
    Inventors: Joel Scarbrough, Daniel Faul