The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 01, 2024

Filed:

Mar. 09, 2021
Applicant:

Tata Consultancy Services Limited, Mumbai, IN;

Inventors:

Sakyajit Bhattacharya, Kolkata, IN;

Oishee Muzumder, Kolkata, IN;

Aniruddha Sinha, Kolkata, IN;

Dibyendu Roy, Kolkata, IN;

Avik Ghose, Kolkata, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/10 (2019.01); G06F 18/2134 (2023.01); G06F 18/214 (2023.01); G06F 18/2321 (2023.01); G06F 18/243 (2023.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01);
U.S. Cl.
CPC ...
G06N 20/10 (2019.01); G06F 18/2134 (2023.01); G06F 18/2148 (2023.01); G06F 18/2321 (2023.01); G06F 18/24317 (2023.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G06F 2218/14 (2023.01);
Abstract

State of the art systems and methods attempting to generate synthetic biosignals such as PPG generate patient specific PPG signatures and do not correlate with pathophysiological changes. Embodiments herein provide a method and system for generating synthetic time domain signals to build a classifier. The synthetic signals are generated using statistical explosion. Initially, a parent dataset of actual sample data of class and non-class subjects is identified, and statistical features are extracted. Kernel density estimate (KDE) is used to vary the feature distribution and create multiple data template from a single parent signal. PPG signal is again reconstructed from the distribution pattern using non-parametric techniques. The generated synthetic data set is used to build the two stage cascaded classifier to classify CAD and Non CAD, wherein the classifier design enables reducing bias towards any class.


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