Patents by Inventor Mohammad A. Al-Abed

Mohammad A. Al-Abed 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).

  • Processing and analyzing physiological signals to detect a health condition
    Patent number: 7966061
    Abstract: Described herein is a method of developing a fuzzy logic system to detect a non-normal health condition. In particular, signal processing and transformation of electrocardiogram (EKG) signals for sleep disorder breathing are provided. The method includes: recording EKG measurements during sleep; clipping the measurements into clips of a consistent length; calculating heart rate and obtaining an evenly sampled discrete time series data clip; performing Short-Time Discrete Fourier Transform on each data clip generating STDFT respective matrices; encoding each STDFT matrix into a grey-level image; calculating Grey-Level Co-occurrence Matrices; extracting textural features; performing statistical analysis on the features to formulate rules; and employing the rules in a Fuzzy Logic system. The system and method described herein yields an accuracy of 75.88%, or better, in detection of sleep apnea.
    Type: Grant
    Filed: August 29, 2007
    Date of Patent: June 21, 2011
    Assignee: Board of Regents, The University of Texas System
    Inventors: Mohammad A. Al-Abed, Khosrow Behbehani, Michael T. Manry
  • PROCESSING AND ANALYZING PHYSIOLOGICAL SIGNALS TO DETECT A HEALTH CONDITION
    Publication number: 20080058659
    Abstract: Described herein is a method of developing a fuzzy logic system to detect a non-normal health condition. In particular, signal processing and transformation of electrocardiogram (EKG) signals for sleep disorder breathing are provided. The method includes: recording EKG measurements during sleep; clipping the measurements into clips of a consistent length; calculating heart rate and obtaining an evenly sampled discrete time series data clip; performing Short-Time Discrete Fourier Transform on each data clip generating STDFT respective matrices; encoding each STDFT matrix into a grey-level image; calculating Grey-Level Co-occurrence Matrices; extracting textural features; performing statistical analysis on the features to formulate rules; and employing the rules in a Fuzzy Logic system. The system and method described herein yields an accuracy of 75.88%, or better, in detection of sleep apnea.
    Type: Application
    Filed: August 29, 2007
    Publication date: March 6, 2008
    Applicant: Board of Regents, The University of Texas System
    Inventors: Mohammad A. Al-Abed, Khosrow Behbehani, Michael T. Manry