公开(公告)号：US11263450B2

公开(公告)日：2022-03-01

申请号：US16264786

申请日：2019-02-01

Applicant: Tata Consultancy Services Limited

Inventor： Soma Bandyopadhyay ,  Arijit Ukil ,  Chetanya Puri ,  Rituraj Singh ,  Arpan Pal ,  C A Murthy

IPC: G06K9/00 ,  G06K9/62 ,  A61B5/0452 ,  A61B5/349

Abstract: The present disclosure addresses the technical problem of information loss while representing a physiological signal in the form of symbols and for recognizing patterns inside the signal. Thus making it difficult to retain or extract any relevant information which can be used to detect anomalies in the signal. A system and method for anomaly detection and discovering pattern in a signal using morphology aware symbolic representation has been provided. The system discovers pattern atoms based on the strictly increasing and strictly decreasing characteristics of the time series physiological signal, and generate symbolic representation in terms of these pattern atoms. Additionally the method possess more generalization capability in terms of granularity. This detects discord/abnormal phenomena with consistency.

公开(公告)号：US11213210B2

公开(公告)日：2022-01-04

申请号：US16285519

申请日：2019-02-26

Applicant: Tata Consultancy Services Limited

Inventor： Rohan Banerjee ,  Sakyajit Bhattacharya ,  Soma Bandyopadhyay ,  Arpan Pal ,  Kayapanda Muthana Mandana

IPC: A61B5/02 ,  G16H50/30 ,  A61B5/00 ,  G16H50/20 ,  A61B5/024 ,  A61B7/04

Abstract: Non-invasive methods for accurately classifying Coronary Artery Disease (CAD) is a challenging task. In the present disclosure, a two stage classification is performed. In the first stage of classification, a metadata based rule engine is utilized to classify a subject into one of a confirmed CAD subject, a CAD subject and a non-CAD subject. Here, a set of optimal parameters are selected from a set of metadata associated with the subject based on a difference in frequency of occurrence of the CAD among a disease population and a non-disease population. Further, an optimal threshold associated with each optimal parameter is calculated based on an inflexion based correlation analysis. Further, the CAD subject, classified by the metadata based rule engine is further reclassified in a second stage by utilizing a set of cardiovascular signal into one of the CAD subject and the non-CAD subject.

公开(公告)号：US20210319046A1

公开(公告)日：2021-10-14

申请号：US17208395

申请日：2021-03-22

Applicant: Tata Consultancy Services Limited

Inventor： Soma Bandyopadhyay ,  Anish Datta ,  Arpan Pal

IPC: G06F16/28 ,  G06N3/04 ,  G06N3/08

Abstract: Conventional hierarchical time-series clustering is highly time consuming process as time-series are characteristically lengthy. Moreover, finding right similarity measure providing best possible hierarchical cluster is critical to derive accurate inferences from the hierarchical clusters. Method and system for Auto Encoded Compact Sequences (AECS) based hierarchical time-series clustering that enables compact latent representation of time-series using an undercomplete multilayered Seq2Seq LSTM auto encoder followed by generating of HCs using multiple similarity measures is disclosed. Further, provided is a mechanism to select the best HC among the multiple HCs on-the-fly, based on an internal clustering performance measure of Modified Hubert statistic τ. Thus, the method provides time efficient and low computational cost approach for hierarchical clustering for both on univariate and multivariate time-series. AECS approach provides a constant length sequence across diverse length series and hence provides a generalized approach.

公开(公告)号：US20170258342A1

公开(公告)日：2017-09-14

申请号：US15453479

申请日：2017-03-08

Applicant: Tata Consultancy Services Limited

Inventor： Arijit Ukil ,  Soma Bandyopadhyay ,  Chetanya Puri ,  Arpan Pal ,  Kayapanda Mandana

IPC: A61B5/024

CPC classification number: A61B5/02416 ,  A61B5/7221 ,  A61B5/725 ,  A61B5/7264 ,  A61B5/7275 ,  A61B5/7282 ,  G06F19/00

Abstract: A method and system of detecting arrhythmia using photoplethysmogram (PPG) signal is provided. The method is performed by extracting photoplethysmogram (PPG) signals from a patient, extracting cardiac parameter from the extracted photoplethysmogram (PPG) signals, identifying presence of cardiac abnormalities as reinforcement filtering of detecting premature ventricular contraction and ventricular flutter from the extracted cardiac parameters, analysing the extracted cardiac parameters to investigate statistical trend and to perform statistical closeness approximation of the extracted photoplethysmogram (PPG) signals and predicting and subsequently classifying type of arrhythmia.

公开(公告)号：US09479948B2

公开(公告)日：2016-10-25

申请号：US14310169

申请日：2014-06-20

Applicant: Tata Consultancy Services Limited

Inventor： Soma Bandyopadhyay ,  Abhijan Bhattacharyya ,  Arpan Pal

IPC: H04W24/02 ,  H04W84/18 ,  H04Q9/02

CPC classification number: H04W24/02 ,  H04Q9/02 ,  H04Q2213/092 ,  H04Q2213/166 ,  H04Q2213/332 ,  H04W84/18

Abstract: A system and method for resource utilization in a constrained sensor gateway for transfer of data in terms of the bandwidth and energy available to transfer data. The system includes a processor in communication with the constrained sensor gateway, which includes an application layer protocol and which is in communication with a communication network, and a memory coupled to the processor. The memory includes a network condition detection module configured to detect a network condition of the constrained sensor gateway, and an adaption module configured to determine a reliability score. The application layer protocol of the constrained sensor gateway adapts a reliability level based on the reliability score determined by the adaption module, which enables better utilization of the bandwidth and energy to transfer data. The reliability level may pertain to a reliable mode, or a non-reliable mode of communication for transferring data.

Abstract translation: 用于在受限传感器网关中资源利用的系统和方法，用于在传输数据的可用带宽和能量方面传输数据。 该系统包括与受限传感器网关通信的处理器，其包括应用层协议并且与通信网络通信，以及耦合到处理器的存储器。 存储器包括被配置为检测受限传感器网关的网络状况的网络条件检测模块，以及被配置为确定可靠性分数的适配模块。 受限传感器网关的应用层协议基于由适配模块确定的可靠性分数来适应可靠性水平，从而更好地利用带宽和能量来传输数据。 可靠性级别可能涉及可靠模式或用于传送数据的不可靠的通信模式。

公开(公告)号：US12210589B2

公开(公告)日：2025-01-28

申请号：US17477771

申请日：2021-09-17

Applicant: Tata Consultancy Services Limited

Inventor： Soma Bandyopadhyay ,  Anish Datta ,  Arpan Pal

IPC: G06F18/21 ,  G06F18/214 ,  G06F18/231 ,  G06N20/20

Abstract: This disclosure relates generally to method and system for time series classification. Conventional methods for time-series classification requires substantial amount of annotated data for classification and label generation. The disclosed method and system are capable of generating accurate labels for time-series data by utilizing a small amount of representative data for each class. In an embodiment, the disclosed method generates a time-series data synthetically and associated labels by using a portion of the representative time-series data in each iteration, and self-correcting the generated labels based on a determination of quality of the generated labels using label quality checker models.

公开(公告)号：US11887730B2

公开(公告)日：2024-01-30

申请号：US16526340

申请日：2019-07-30

Applicant: Tata Consultancy Services Limited

Inventor： Avik Ghose ,  Arpan Pal ,  Sundeep Khandelwal ,  Rohan Banerjee ,  Sakyajit Bhattacharya ,  Soma Bandyopadhyay ,  Arijit Ukil ,  Dhaval Satish Jani

IPC: G16H50/20 ,  G16H50/70 ,  G06N3/043 ,  G06N20/00

CPC classification number: G16H50/20 ,  G06N3/043 ,  G16H50/70 ,  G06N20/00

Abstract: This disclosure relates generally to methods and systems for unobtrusive digital health assessment of high risk subjects, wherein bio-markers pertaining to a disease are identified automatically using physical activity and physiology monitoring on a continuous basis. Identification of bio-markers in the medical domain is conventionally dependent on insights derived from medical tests which are obtrusive in nature. Systems and methods of the present disclosure integrate physical characteristics, lifestyle habits and prevailing medical conditions with monitored physical activities and physiological measurements to assess health of high risk subjects. Systems and methods of the present disclosure also enable automatic generation of control class and treatment class that may be effectively used for health assessment.

公开(公告)号：US11567974B2

公开(公告)日：2023-01-31

申请号：US17208395

申请日：2021-03-22

Applicant: Tata Consultancy Services Limited

Inventor： Soma Bandyopadhyay ,  Anish Datta ,  Arpan Pal

IPC: G06F16/28 ,  G06N3/04 ,  G06N3/08

Abstract: Conventional hierarchical time-series clustering is highly time consuming process as time-series are characteristically lengthy. Moreover, finding right similarity measure providing best possible hierarchical cluster is critical to derive accurate inferences from the hierarchical clusters. Method and system for Auto Encoded Compact Sequences (AECS) based hierarchical time-series clustering that enables compact latent representation of time-series using an undercomplete multilayered Seq2Seq LSTM auto encoder followed by generating of HCs using multiple similarity measures is disclosed. Further, provided is a mechanism to select the best HC among the multiple HCs on-the-fly, based on an internal clustering performance measure of Modified Hubert statistic τ. Thus, the method provides time efficient and low computational cost approach for hierarchical clustering for both on univariate and multivariate time-series. AECS approach provides a constant length sequence across diverse length series and hence provides a generalized approach.

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：US10268836B2

公开(公告)日：2019-04-23

申请号：US14618280

申请日：2015-02-10

Applicant: Tata Consultancy Services Limited

Inventor： Arijit Ukil ,  Soma Bandyopadhyay ,  Arpan Pal

IPC: G06F21/62 ,  H04L29/06 ,  G01D4/00

Abstract: A system and method for detecting sensitivity content in time-series data is disclosed. The method comprises receiving the time-series data from a source. The data is received for one or more instances. The method further comprises detecting the sensitivity content in the time-series data. The sensitivity content indicates presence of an anomaly. The detecting comprises determining a kurtosis value corresponding to the time-series data. The detecting further comprises comparing the kurtosis value with a reference value. The detecting further comprises processing the data using a first filtering means or a second filtering means. The first filtering means is used when the data distribution of the time-series data is either of a platykurtic distribution or a mesokurtic distribution. The second filtering means is used when the data distribution of the time-series data is a leptokurtic distribution.