公开(公告)号：US20240079140A1

公开(公告)日：2024-03-07

申请号：US18227480

申请日：2023-07-28

Applicant: Tata Consultancy Services Limited

Inventor： Arijit UKIL ,  Jayavardhana Rama Gubbi Lakshminarasimha ,  Arpan Pal ,  Trisrota Deb ,  Sai Chander Racha ,  Ishan Sahu ,  Sundeep Khandelwal

IPC: G16H50/20

CPC classification number: G16H50/20 ,  G16H40/67

Abstract: Portable ECG monitors available in market have the disadvantage that the ECG data they provide as input aren't directly interpretable and requires medical knowledge for the users. The disclosure herein generally relates to Electrocardiogram (ECG), and, more particularly, to a method and system for generating 2d representation of electrocardiogram (ECG) signals. The system provides a mechanism for determining variability between a plurality of segments of an ECG data measured, and uses the information on the determined variability to generate the 2D representation corresponding to the ECG signal. The system further provides means to generate a data model that can be further used for processing real-time ECG data for generating corresponding interpretations. This allows a user to obtain the interpretations as output.

公开(公告)号：US11494415B2

公开(公告)日：2022-11-08

申请号：US16421372

申请日：2019-05-23

Applicant: Tata Consultancy Services Limited

Inventor： Ishan Sahu ,  Ayan Mukherjee ,  Arijit Ukil ,  Soma Bandyopadhyay ,  Chetanya Puri ,  Rituraj Singh ,  Arpan Pal ,  Rohan Banerjee

IPC: G06V10/771 ,  G06F16/28 ,  G06F16/245 ,  G06K9/62 ,  G06V30/19

Abstract: A method and system for a feature subset-classifier pair for a classification task. The classification task corresponds to automatically classifying data associated with a subject(s) or object(s) of interest into an appropriate class based on a feature subset selected among a plurality of features extracted from the data and a classifier selected from a set of classifier types. The method proposed includes simultaneously determining the feature subset-classifier pair based on a relax-greedy {feature subset, classifier} approach utilizing sub-greedy search process based on a patience function, wherein the feature subset-classifier pair provides an optimal combination for more accurate classification. The automatic joint selection is time efficient solution, effectively speeding up the classification task.

公开(公告)号：US11475341B2

公开(公告)日：2022-10-18

申请号：US16179771

申请日：2018-11-02

Applicant: Tata Consultancy Services Limited

Inventor： Ishan Sahu ,  Snehasis Banerjee ,  Tanushyam Chattopadhyay ,  Arpan Pal ,  Utpal Garain

IPC: G06N7/00 ,  G06F17/14 ,  G06N20/00 ,  G06F17/18 ,  G06K9/62

Abstract: Systems and methods for obtaining optimal mother wavelets for facilitating machine learning tasks. The traditional systems and methods provide for selecting a mother wavelet and signal classification using some traditional techniques and methods but none them provide for selecting an optimal mother wavelet to facilitate machine learning tasks. Embodiments of the present disclosure provide for obtaining an optimal mother wavelet to facilitate machine learning tasks by computing values of energy and entropy based upon labelled datasets and a probable set of mother wavelets, computing values of centroids and standard deviations based upon the values of energy and entropy, computing a set of distance values and normalizing the set of distance values and obtaining the optimal mother wavelet based upon the set of distance values for performing a wavelet transform and further facilitating machine learning tasks by classifying or regressing, a new set of signal classes, corresponding to a new set of signals.