公开(公告)号：US11988568B2

公开(公告)日：2024-05-21

申请号：US17014554

申请日：2020-09-08

Applicant: Tata Consultancy Services Limited

Inventor： Avik Ghose ,  Parama Pal ,  Murali Poduval

IPC: G01L1/24 ,  A41D1/00 ,  A61B5/00 ,  A61B5/11 ,  A41B11/00 ,  A41D1/089 ,  A41D19/00 ,  A44C5/00 ,  A61B34/20

CPC classification number: G01L1/246 ,  A41D1/002 ,  A61B5/0002 ,  A61B5/1121 ,  A61B5/6804 ,  A61B5/742 ,  A61B5/746 ,  A41B11/00 ,  A41B2400/32 ,  A41D1/089 ,  A41D19/0027 ,  A41D2400/32 ,  A44C5/0015 ,  A44C5/0023 ,  A61B2034/2061

Abstract: This disclosure relates generally to a sensor based wearable fabric design for identifying distortion in movements and quantifying range of motion. Accurate quantification of multi-axial range of motion involved in complex movements of human body parts is challenging. The disclosure discloses a system and method providing a wearable fabric comprising a plurality of honey-comb structure with a plurality of adjacently placed hexagon structures. An optical sensor unit is placed on each side of each hexagon structure comprised in the plurality of honey-comb structures. A deformation of the plurality of sides of hexagon structure is determined to generate signatures of movement patterns of one or more body parts of a subject. Further, a comparison of generated signatures with stored signatures of the movement patterns is performed to determine an error indicative of a distortion in the movement patterns. The system and method accurately quantify range of motion with increased measurement accuracy.

公开(公告)号：US11966674B2

公开(公告)日：2024-04-23

申请号：US17219204

申请日：2021-03-31

Applicant: Tata Consultancy Services Limited

Inventor： Parama Pal ,  Prajith Pillai ,  Rinu Chacko ,  Deepak Shyamsunder Jain ,  Beena Rai

IPC: G06F30/27 ,  G06N3/045 ,  G06N3/08

CPC classification number: G06F30/27 ,  G06N3/045 ,  G06N3/08

Abstract: Artificially structured materials are created artificially and offer customizable properties. They are being used in various fields. A system and method for designing artificially structured materials have been provided. The system and method is based on neural networks for approximating the electromagnetic (EM) responses of the artificially structured materials. By treating the EM spectral data as time-varying sequences and the inverse problem as a single-input, multi-output model, the architecture is forced to learn the geometry of the designs from the training data as opposed to abstract features thereby addressing both the forward and the inverse design problems. The system is configured to provide end-to-end workflow from collating the requirement specifications from the user (based on the intended use case such as solar energy harvesting, biological sensing, thermos-photovoltaics, photo-detection, creation of imaging devices, absorption filtering and stealth technology) to generating a device design for the intended functionality.

公开(公告)号：US20230177327A1

公开(公告)日：2023-06-08

申请号：US17970710

申请日：2022-10-21

Applicant: Tata Consultancy Services Limited

Inventor： Prajith PILLAI ,  Anirban Chaudhuri ,  Parama Pal ,  Beena Rai

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Conventionally, design methodologies employed deep learning model based on physics which considers only real (permittivity) term and ignores the imaginary (conductivity) term in complex loss function which fail to help in design of complex structures and limit their applications to scenarios such as array of metamaterial structures. Present application provides systems and method implement apply a Physics-Informed Neural Network (PINN) for inversely calculating the effective material parameters of a multi-dimensional metamaterial from its scattered field(s). By employing a loss function based on the Helmholtz wave equation, performance of a metamaterial is modeled by the system the dependance of resonant behavior on the homogenized electric permittivity distribution profile generated by the PINN is demonstrated.

公开(公告)号：US20240257399A1

公开(公告)日：2024-08-01

申请号：US18421030

申请日：2024-01-24

Applicant: Tata Consultancy Services Limited

Inventor： Renju PARAPPILLIL BABY ,  Parama Pal ,  Beena Rai

IPC: G06T7/90 ,  G06T5/50 ,  G06T7/194 ,  G06V10/25 ,  G06V10/56 ,  G06V10/762

CPC classification number: G06T7/90 ,  G06T5/50 ,  G06T7/194 ,  G06V10/25 ,  G06V10/56 ,  G06V10/762 ,  G06T2207/10024 ,  G06T2207/10036 ,  G06T2207/20221

Abstract: Multispectral laser speckle analysis techniques have been widely used for applications such as the analysis of seed qualities, detection of fungal infections in fresh produce, estimation of blood flow velocities, and the like. However, the conventional methods fail to address color bias in images which is a major concern in terms of accuracy in applications like activity prediction. and the present disclosure provides a novel image processing algorithm which performs activity prediction without any color bias. Here, an RGB input image is segmented, and mask is generated. Distance based clustering is performed on the masked image to obtain cluster map. Simultaneously, color coded activity map is generated for each color component of the image. Further, the color coded activity map is multiplied with cluster contrast values and thereby an optimal color coded activity region is selected for activity map generation.

公开(公告)号：US20230130329A1

公开(公告)日：2023-04-27

申请号：US17952715

申请日：2022-09-26

Applicant: Tata Consultancy Services Limited

Inventor： Renju PARAPPILLIL BABY ,  Parama Pal ,  Beena Rai

IPC: G02B27/48 ,  G01N21/47 ,  G06T5/50

Abstract: This disclosure relates to portable speckle imaging system and method for automated speckle activity map based dynamic speckle analysis. The embodiments of present disclosure herein address unresolved problem of capturing variations in speckle patterns where noise is completely removed and dependency on intensity of variations in speckle patterns is eliminated. The method of the present disclosure provides a correlation methodology for analyzing laser speckle images for applications such as seed viability, fungus detection, surface roughness analysis, and/or the like by capturing temporal variation from frame to frame and ignoring the intensity of speckle data after denoising, thereby providing an effective mechanism to study speckle time series data. The system and method of the present disclosure performs well in terms of time efficiency and visual cues and requires minimal human intervention.

公开(公告)号：US20220343510A1

公开(公告)日：2022-10-27

申请号：US17687889

申请日：2022-03-07

Applicant: Tata Consultancy Services Limited

Inventor： Parama Pal ,  Earu Banoth

IPC: G06T7/174 ,  G06T3/40

Abstract: This disclosure relates generally to speckle image analysis, and, more particularly, to a system and method for imaging of localized and heterogenous dynamics using laser speckle. Existing speckle analysis techniques do not offer the capability to achieve both the dynamic phenomenon which carries over a specific time duration and localizing the extent of the activity at a single, chosen instant of time simultaneously. The present disclosure records an image stack consisting of N speckle images sequentially over a period, divides the image stack into a spatial window and a temporal window, converts the speckle intensity data comprised in the spatial window into a column vector. Construct a diagonal matrix and extract a singular value from the diagonal matrix, then defines a speckle intensity correlation metric using the plurality of singular values, defines a speckle activity and generates a speckle contrast image by graphically plotting the speckle activity values.