公开(公告)号：US11668621B2

公开(公告)日：2023-06-06

申请号：US17453031

申请日：2021-11-01

Applicant: Tata Consultancy Services Limited

Inventor： Arijit Sinharay ,  Gitesh Kulkarni ,  Abhijeet Gorey ,  Chirabrata Bhaumik ,  Tapas Chakravarty ,  Arpan Pal

IPC: G01M3/24 ,  F17D5/06 ,  G01S19/01

CPC classification number: G01M3/243 ,  G01S19/01

Abstract: Fluids are normally transported from one place to another through pipelines. It is essential to monitor the pipeline to avoid leakage or theft. It is expensive and not feasible to install cameras and sensors along the whole length of the pipeline. A system and method for inspecting and detecting fluid leakage in a pipeline has been provided. The system is using vibration sensors along with pressure sensors to detect the leakage or theft along with the exact location of the leakage or theft. The pressure sensors are mounted on the pipeline so that the fluid touches the diaphragm of the pressure sensors to sense the wave generated due to leakage. The vibration sensors are mounted on top of the pipeline surface and on the nearby ground to eliminate general noise conditions. Moreover, two pressure sensors are also installed at opposite sides to pinpoint the leakage location.

公开(公告)号：US20210022713A1

公开(公告)日：2021-01-28

申请号：US16827743

申请日：2020-03-24

Applicant: Tata Consultancy Services Limited

Inventor： Anwesha Khasnobish ,  Raj Rakshit ,  Arijit Sinharay ,  Tapas Chakravarty

IPC: A61B8/08 ,  A61B8/02 ,  G01S15/89 ,  G01S7/52 ,  G01N29/46

Abstract: This disclosure relates generally to bio-signal detection, and more particularly to method and system for non-contact bio-signal detection using ultrasound signals. In an embodiment, the method includes acquiring an in-phase I(t) baseband signal and a quadrature Q(t) baseband signal associated with an ultrasound signal directed from the sensor assembly towards the target. Magnitude and phase signals are calculated from the in-phase and quadrature baseband signals, and are filtered by passing through a band pass filter associated with a predefined frequency range to obtain filtered magnitude and phase signals. Fast Fourier Transformation (FFT) of the filtered magnitude and phase signals is performed to identify frequency of dominant peaks of spectrum of the magnitude and phase signals in the ultrasound signal. Value of the bio-signal associated with the target is determined based on weighted values of the frequency of the dominant peaks of the magnitude and phase signals.

公开(公告)号：USD838845S1

公开(公告)日：2019-01-22

申请号：US29608639

申请日：2017-06-23

Applicant: Tata Consultancy Services Limited

Designer： Arijit Sinharay ,  Deb Kumar Ghosh ,  Sanjoy Debnath ,  Raj Rakshit

公开(公告)号：US20180220934A1

公开(公告)日：2018-08-09

申请号：US15809403

申请日：2017-11-10

Applicant: Tata Consultancy Services Limited

Inventor： Raj RAKSHIT ,  Arijit Sinharay ,  Parijat Dilip Deshpande ,  Tapas Chakravarty ,  Arpan Pal ,  Deb Kumar Ghosh ,  Shreyasi Datta

IPC: A61B5/097 ,  A61B5/087 ,  A61B5/091 ,  A61B5/00 ,  A61B5/08

CPC classification number: A61B5/097 ,  A61B5/0004 ,  A61B5/0803 ,  A61B5/087 ,  A61B5/091 ,  A61B5/7203 ,  A61B5/7242 ,  A61B5/725 ,  A61B5/7267 ,  A61B5/7275 ,  A61B5/7278 ,  A61B2562/0204

Abstract: A pulmonary health monitoring system aims at assessing pulmonary health of subjects. Conventional techniques used for pulmonary health monitoring are not convenient to the subjects and needs considerable cooperation from the subjects. But, there is a challenge in utilizing the conventional devices to the subjects not capable of providing considerable cooperation. The present disclosure includes a blow device applicable to all kind of subjects and doesn't need cooperation from the subjects. Further, in the present disclosure, the blow device generates a phase shifted signal corresponding to a breathe signal and the phase shifted signal is further processed to extract a set of physiological features. Further, pulmonary health of a subject is analyzed by processing the set of physiological features based on a ridge regression based machine learning technique.

公开(公告)号：US20160242699A1

公开(公告)日：2016-08-25

申请号：US15023314

申请日：2014-09-12

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Diptesh Das ,  Debatri Chatterjee ,  Arijit Sinharay ,  Aniruddha Sinha

IPC: A61B5/00 ,  A61B5/0476 ,  A61B5/048

Abstract: System and method for evaluating a cognitive load on a user, corresponding to a stimulus is disclosed. Electroencephalogram (EEG) data corresponding to the stimulus of a user is received. The stimulus corresponds to a mental task performed by the user. The EEG data is split into a plurality of slots. A slot of the plurality of slots comprises a subset of the EEG data. One or more EEG features are extracted from the subset of the EEG data. The one or more EEG features are represented in one of a frequency domain and a time domain. A plurality of data points present in the one or more EEG features is grouped into two or more clusters using an unsupervised learning technique. The two or more clusters comprise one or more data points of the plurality of data points. The one or more data points correspond to a level of the cognitive load.

Abstract translation: 公开了用于评估对应于刺激的用户的认知负荷的系统和方法。 接收与用户的刺激对应的脑电图（EEG）数据。 刺激对应于用户执行的心理任务。 EEG数据被分成多个时隙。 多个时隙中的时隙包括EEG数据的子集。 从EEG数据的子集中提取一个或多个EEG特征。 一个或多个EEG特征在频域和时域之一中表示。 存在于一个或多个EEG特征中的多个数据点使用无监督学习技术被分组为两个或更多个簇。 两个或更多个簇包括多个数据点中的一个或多个数据点。 一个或多个数据点对应于认知负荷的水平。

公开(公告)号：US20160128593A1

公开(公告)日：2016-05-12

申请号：US14665476

申请日：2015-03-23

Applicant: Tata Consultancy Services Limited

Inventor： Arijit Sinharay ,  Aniruddha Sinha ,  Diptesh Das ,  Debatri Chatterjee

IPC: A61B5/04 ,  A61B5/00 ,  A61B5/0476

CPC classification number: A61B5/04014 ,  A61B5/0006 ,  A61B5/0476 ,  A61B5/165 ,  A61B5/4088 ,  A61B5/7221 ,  A61B2560/0475

Abstract: Disclosed is a method and system for selection of Electroencephalography (EEG) channels valid for determining cognitive load of subject. According to one embodiment, EEG signals are obtained from EEG channels associated with subject performing cognitive tasks are received. Time-frequency features of EEG signals are extracted for a frequency band comprise maximum energy value, minimum energy value, average energy value, maximum frequency value, minimum frequency value, and average frequency value. Weight of an EEG channel associated with time-frequency feature is derived using statistical learning technique. Binary values for EEG channels corresponding to time-frequency feature are assigned using weight of EEG channel associated with time-frequency feature. Intersections of binary values of EEG channels corresponding to maximum energy value and average energy value, minimum energy value and average energy value, maximum frequency value and average frequency value, and minimum frequency value and average frequency value are computed. Unions of intersections are computed, wherein the unions represent EEG channels valid to determine cognitive load of subject.

Abstract translation: 公开了用于选择有效用于确定受试者的认知负荷的脑电图（EEG）通道的方法和系统。 根据一个实施例，从接收到执行认知任务的对象相关联的EEG信道获得EEG信号。 为包括最大能量值，最小能量值，平均能量值，最大频率值，最小频率值和平均频率值的频带提取EEG信号的时频特征。 使用统计学习技术导出与时频特征相关的脑电信道的权重。 对应于时频特征的EEG频道的二进制值使用与时频特征相关的EEG频道的权重来分配。 计算与最大能量值和平均能量值，最小能量值和平均能量值，最大频率值和平均频率值以及最小频率值和平均频率值对应的EEG频道的二进制值的交点。 计算交叉点的联合，其中工会代表有效确定受试者的认知负荷的EEG通道。