公开(公告)号：US20220344055A1

公开(公告)日：2022-10-27

申请号：US17653248

申请日：2022-03-02

Applicant: Tata Consultancy Services Limited

Inventor： AVIK GHOSE ,  AVIJIT SAMAL ,  NASIMUDDIN AHMED ,  SHIVAM SINGHAL ,  KARAN BHAVSAR ,  VIVEK CHANDEL ,  SUNDEEP KHANDELWAL ,  HARSH VISHWAKARMA ,  BHASKAR PAWAR

IPC: G16H50/30 ,  G06F16/25 ,  G16H40/67

Abstract: Non-communicable diseases (NCDs) are the pandemics of modern era and are generating huge impact in the modern society. Conventional methods are inaccurate due to a challenge in handling data from heterogenous sensors. The present disclosure is capable of tracking fitness parameters of a user even with heterogenous sensors. Initially, the system receives a raw data from a plurality of heterogenous sensors associated with the user. The raw data is further transformed into a metadata format associated with the corresponding sensor. The transformed data is temporally aligned based on a time based slotting. An algorithm pipeline corresponding to a disorder to be analyzed is selected from a Directed Acyclic Graph (DAG) based on a sensor metadata and a plurality of algorithm metadata corresponding to a plurality of algorithms stored in an algorithm database and an algorithm pipeline. The corresponding disorder is analyzed using the algorithm pipeline.

公开(公告)号：US20240120085A1

公开(公告)日：2024-04-11

申请号：US18480109

申请日：2023-10-03

Applicant: Tata Consultancy Services Limited

Inventor： VIVEK CHANDEL ,  AVIK GHOSE ,  MAYURI DUGGIRALA ,  ARNAB CHATTERJEE ,  SAKYAJIT BHATTACHARYA

IPC: G16H40/63

CPC classification number: G16H40/63

Abstract: Existing systems for behavioural tracking and identification have the disadvantage that they do not analyse data in behavioural aspects. As a result, they lack ability to pre-empt scenarios involving actions that adversely affect user health. The disclosure herein generally relates to behavior prediction, and, more particularly, to a method and system for identifying unhealthy behavior trigger and providing nudges. The system generates a casual inference model, which is a reverse causality model facilitating mapping of context with one or more behaviour of the user. The system further collects and processes real-time data using the casual inference model, to perform behavioral analysis of the user.

公开(公告)号：US20240160297A1

公开(公告)日：2024-05-16

申请号：US18465409

申请日：2023-09-12

Applicant: Tata Consultancy Services Limited

Inventor： VIVEK CHANDEL ,  AVIK GHOSE

IPC: G06F3/0346 ,  G06F1/16 ,  G06F3/01

CPC classification number: G06F3/0346 ,  G06F1/163 ,  G06F3/014

Abstract: Tracking motion using inertial sensors embedded in commercial grade wearables like smartwatches has proved to be a challenging task, especially if real-time tracking is a requirement. Present disclosure provides system and method wherein data from sensors are obtained and scaled. Further, Euler Rodrigues Matrix (ERM) is generated based delta value obtained using sensor data. The scaled sensor data and ERM are used for generating feature vectors. Windowing technique is applied for subsets of feature vectors to obtain label for each window and machine learning model is trained with the label and window. Further, during real-time, sensor data is obtained, and steps of ERM, feature vectors generation, and application of windowing technique are repeated, and coordinates are estimated for each window in real-time based on which trajectories are tracked in real-time for each window.