Patents by Inventor Vijay Anil Date

Vijay Anil Date 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).

  • Method and system for classifying phonocardiogram signal quality
    Patent number: 11373757
    Abstract: A system and method for classifying the phonocardiogram (PCG) signal quality has been described. The system is configured to identify the quality of the PCG signal recording and accepting only diagnosable quality recordings for further cardiac analysis. The system includes the derivation of plurality features of the PCG signal from the training dataset. The extracted features are preprocessed and are then ranked using mRMR algorithm. Based on the ranking the irrelevant and redundant features are rejected if their mRMR strength is less. A training model is generated using the relevant set of features. The PCG signal of the person under test is captured using a digital stethoscope and a smartphone. The PCG signal is preprocessed and only the relevant set of features are extracted. And finally the PCG signal is classified into diagnosable or non-diagnosable using the relevant set of features and a random forest classifier.
    Type: Grant
    Filed: March 6, 2018
    Date of Patent: June 28, 2022
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Deepan Das, Rohan Banerjee, Anirban Dutta Choudhury, Parijat Dilip Deshpande, Nital Shah, Vijay Anil Date, Arpan Pal, Kayapanda Muthana Mandana
  • METHOD AND SYSTEM FOR CLASSIFYING PHONOCARDIOGRAM SIGNAL QUALITY
    Publication number: 20190013102
    Abstract: A system and method for classifying the phonocardiogram (PCG) signal quality has been described. The system is configured to identify the quality of the PCG signal recording and accepting only diagnosable quality recordings for further cardiac analysis. The system includes the derivation of plurality features of the PCG signal from the training dataset. The extracted features are preprocessed and are then ranked using mRMR algorithm. Based on the ranking the irrelevant and redundant features are rejected if their mRMR strength is less. A training model is generated using the relevant set of features. The PCG signal of the person under test is captured using a digital stethoscope and a smartphone. The PCG signal is preprocessed and only the relevant set of features are extracted. And finally the PCG signal is classified into diagnosable or non-diagnosable using the relevant set of features and a random forest classifier.
    Type: Application
    Filed: March 6, 2018
    Publication date: January 10, 2019
    Applicant: Tata Consultancy Services Limited
    Inventors: Deepan Das, Rohan Banerjee, Anirban Dutta Choudhury, Parijat Dilip Deshpande, Nital Shah, Vijay Anil Date, Arpan Pal, Kayapanda Muthana Mandana