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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
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.
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公开(公告)号：US10420527B2
公开(公告)日：2019-09-24
申请号：US15098254
申请日：2016-04-13
Applicant: Tata Consultancy Services Limited
Inventor： Aditi Misra , Aniruddha Sinha , Avik Ghose , Anirban Dutta Choudhury , Rohan Banerjee
Abstract: System and method for determining a heart rate and a heart rate variability of an individual is disclosed. An audio signal of heart sound is amplified. Subsequently, an envelope of the amplified audio signal is detected by squaring of the amplified audio signal to obtain emphasized high amplitude components and diminished low amplitude components of the audio signal, applying a band pass filter on the audio signal upon squaring and applying a Teager-Kaiser Energy Operator (TKEO) on the filtered audio signal. Peaks in the envelope of the audio signal are detected by calculating difference in magnitude of a point in the audio signal with an average of magnitude of earlier points in the audio signal from the last detected peak or the initial sample value in the processing window when no peak is detected. Based on the peaks detected, heart rate and heart rate variability for the individual are determined.
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公开(公告)号：US09955880B2
公开(公告)日：2018-05-01
申请号：US14665657
申请日：2015-03-23
Applicant: Tata Consultancy Services Limited
Inventor： Aishwarya Visvanathan , Arpan Pal , Aniruddha Sinha , Rohan Banerjee , Anirban Dutta Choudhury , Aditi Mishra , Avik Ghose
IPC: G06K9/00 , A61B5/024 , A61B5/1455 , A61B5/00
CPC classification number: A61B5/02416 , A61B5/0082 , A61B5/02438 , A61B5/14551 , A61B2560/0238
Abstract: A physiological parameter measurement device comprising a processor and a video processing module coupled to the processor to divide each of a plurality of frames of a video into a plurality of blocks, where the video is of a body part of a subject whose physiological parameter is to be determined. The video processing module further is to select a block having highest peak signal to noise ratio (PSNR) from amongst the plurality of blocks. Further, the video processing module is to extract a photoplethysmogram (PPG) signal from the video based on a block identifier associated with the block. The physiological parameter measurement device further comprises a signal enhancement module coupled to the processor, to process the PPG signal to obtain an enhanced PPG signal for determining a value of the physiological parameter for the subject.
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公开(公告)号：US20150031965A1
公开(公告)日：2015-01-29
申请号：US14444745
申请日：2014-07-28
Applicant: TATA CONSULTANCY SERVICES LIMITED
Inventor： Aishwarya Visvanathan , Arpan Pal , Anirban Dutta Choudhury , Tanushyam Chattopadhyay , Anurag Kumar , Rohan Banerjee , Aniruddha Sinha
IPC: A61B5/00 , A61B5/1455 , A61B5/0402 , A61B5/0205
CPC classification number: A61B5/0059 , A61B5/0205 , A61B5/021 , A61B5/02416 , A61B5/02438 , A61B5/04028 , A61B5/08 , A61B5/14551 , A61B5/6898 , A61B5/7267 , A61B2505/07 , G06F19/00
Abstract: A method for monitoring physiological parameters associated with a subject using a hand held device is described herein. In an implementation, the method includes obtaining a plurality of sample photoplethysmographic (PPG) features associated with a sample subject, from a video of a body part of the sample subject. From among the plurality of sample PPG features, at least one relevant sample PPG feature associated with the physiological parameter, is selected based on a ground truth value of the physiological parameter for the subject. Further, based on the at least one relevant sample PPG feature and the ground truth value of the physiological parameter, a mathematical model indicative of a correlation between the relevant sample PPG feature and the physiological parameter, is determined. The mathematical model can be deployed for monitoring the physiological parameter in real time.
Abstract translation: 本文描述了使用手持式装置监测与受试者相关的生理参数的方法。 在一个实现中，该方法包括从样本对象的身体部分的视频获得与样本对象相关联的多个样本光体积描记图（PPG）特征。 从多个样本PPG特征中，基于对象的生理参数的基本真值，选择与生理参数相关联的至少一个相关样本PPG特征。 此外，基于至少一个相关样本PPG特征和生理参数的基本真值，确定指示相关样本PPG特征和生理参数之间的相关性的数学模型。 可以部署数学模型，实时监测生理参数。
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公开(公告)号：US11373757B2
公开(公告)日：2022-06-28
申请号：US15913682
申请日：2018-03-06
Applicant: Tata Consultancy Services Limited
Inventor： Deepan Das , Rohan Banerjee , Anirban Dutta Choudhury , Parijat Dilip Deshpande , Nital Shah , Vijay Anil Date , Arpan Pal , Kayapanda Muthana Mandana
Abstract: A system and method for classifying the phonocardiogram (PCG) signal quality has been described. The system is configured to identify the quality of the PCG signal recording and accepting only diagnosable quality recordings for further cardiac analysis. The system includes the derivation of plurality features of the PCG signal from the training dataset. The extracted features are preprocessed and are then ranked using mRMR algorithm. Based on the ranking the irrelevant and redundant features are rejected if their mRMR strength is less. A training model is generated using the relevant set of features. The PCG signal of the person under test is captured using a digital stethoscope and a smartphone. The PCG signal is preprocessed and only the relevant set of features are extracted. And finally the PCG signal is classified into diagnosable or non-diagnosable using the relevant set of features and a random forest classifier.
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Patent Agency Ranking
公开(公告)号：US11357410B2
公开(公告)日：2022-06-14
申请号：US14643333
申请日：2015-03-10
Applicant: TATA CONSULTANCY SERVICES LIMITED
Inventor： Rohan Banerjee , Anirban Dutta Choudhury , Aniruddha Sinha
IPC: A61B5/0205 , A61B5/021 , A61B5/00 , A61B5/02 , A61B5/024 , G16H50/50 , A61B5/022 , G16H50/20 , G16H40/67
Abstract: A method for measuring blood pressure of a subject is described herein. In an implementation, the method includes obtaining a plurality of photoplethysmogram (PPG) features associated with the subject. The method further includes ascertaining one or more latent parameters associated with the subject based on the plurality of PPG features and a reference model, wherein the reference model indicates a correlation between the plurality of PPG features and the one or more latent parameters. Further, blood pressure of the subject is determined based on the one or more latent parameters and the plurality of PPG features.
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公开(公告)号：US20160113531A1
公开(公告)日：2016-04-28
申请号：US14665657
申请日：2015-03-23
Applicant: Tata Consultancy Services Limited
Inventor： Aishwarya Visvanathan , Arpan Pal , Aniruddha Sinha , Rohan Banerjee , Anirban Dutta Choudhury , Aditi Mishra , Avik Ghose
IPC: A61B5/024 , A61B5/1455 , A61B5/00 , A61B5/021
CPC classification number: A61B5/02416 , A61B5/0082 , A61B5/02438 , A61B5/14551 , A61B2560/0238
Abstract: A physiological parameter measurement device comprising a processor and a video processing module coupled to the processor to divide each of a plurality of frames of a video into a plurality of blocks, where the video is of a body part of a subject whose physiological parameter is to be determined. The video processing module further is to select a block having highest peak signal to noise ratio (PSNR) from amongst the plurality of blocks. Further, the video processing module is to extract a photoplethysmogram (PPG) signal from the video based on a block identifier associated with the block. The physiological parameter measurement device further comprises a signal enhancement module coupled to the processor, to process the PPG signal to obtain an enhanced PPG signal for determining a value of the physiological parameter for the subject.
Abstract translation: 一种生理参数测量装置，包括处理器和视频处理模块，所述处理器和视频处理模块耦合到所述处理器，以将视频的多个帧中的每一个划分成多个块，其中所述视频是其生理参数为 确定。 视频处理模块还要从多个块中选择具有最高峰值信噪比（PSNR）的块。 此外，视频处理模块基于与该块相关联的块标识符从视频提取光电容积图（PPG）信号。 生理参数测量装置还包括耦合到处理器的信号增强模块，以处理PPG信号以获得用于确定对象的生理参数的值的增强的PPG信号。
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公开(公告)号：US20160021237A1
公开(公告)日：2016-01-21
申请号：US14772928
申请日：2014-03-13
Applicant: TATA CONSULTANCY SERVICES LIMITED
Inventor： Rohan Banerjee , Aniruddha Sinha , Arindam Saha
CPC classification number: H04M1/72569 , H04W4/02 , H04W4/027 , H04W4/046 , H04W4/38 , H04W4/50 , H04W52/0254 , Y02D70/164
Abstract: Disclosed is a method and system enabling power effective participatory sensing. The hand held device of the system is equipped with plurality of sensors, and is configured to enable the power effective sensor to monitor operation of the power intensive sensors. In one embodiment, a participatory sensing approach is used for traffic condition. A methodology for triggering power hungry sensors (audio) with the help of low power sensors (accelerometer) is presented which is able to reduce the overall power consumption of the mobile device. Further, a decision tree based approach is used to classify the level of congestion by measuring the horn density in a particular location.
Abstract translation: 公开了一种能够进行功率有效的参与式感测的方法和系统。 系统的手持式装置配备有多个传感器，并且被配置为使得功率有效传感器能够监测功率密集型传感器的操作。 在一个实施例中，参与式感测方法用于交通状况。 提出了一种借助于低功率传感器（加速度计）来触发电力饥饿传感器（音频）的方法，可以降低移动设备的整体功耗。 此外，基于决策树的方法被用于通过测量特定位置的喇叭密度来分类拥挤水平。
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公开(公告)号：US12274536B2
公开(公告)日：2025-04-15
申请号：US16946718
申请日：2020-07-01
Applicant: Tata Consultancy Services Limited
Inventor： Sanjay Madhukar Kimbahune , Sujit Raghunath Shinde , Arpan Pal , Sundeep Khandelwal , Tanuka Bhattacharjee , Shalini Mukhopadhayay , Rohan Banerjee , Avik Ghose , Tapas Chakravarty
Abstract: Embodiments herein provide a system and method for screening and monitoring of cardiac diseases by analyzing acquired physiological signals. Unlike state of art approaches that consider only synchronized ECG and PPG signals for cardiac health analysis and do not consider PCG which is a critical signal for CAD analysis, the system synchronously captures physiological signals such as photo plethysmograph (PPG), phonocardiogram (PCG) and electrocardiogram (ECG) from subject(s) and builds an analytical model in the cloud for analyzing heart conditions from the captured physiological signals. The system and method provides a fusion based approach of combining the captured physiological signals such as PPG, PCG and ECG along with other details such as subject clinical information, demography information and so on. The analytical model is pretrained using ECG. PPG and PCG along with metadata associated with the subject such as demography and clinical information.
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10.发明授权公开(公告)号：US11571162B2
公开(公告)日：2023-02-07
申请号：US16827812
申请日：2020-03-24
Applicant: Tata Consultancy Services Limited
Inventor： Rohan Banerjee , Avik Ghose , Sundeep Khandelwal
Abstract: Conventionally, Atrial Fibrillation (AF) has been detected using atrial analyses which is vulnerable to background noise. Again there is a dependency on statistical features which are extracted from R-R intervals of long ECG recordings. The present disclosure addresses AF detection from single lead short ECG recordings of less than one minute wherein automatic detection of P-R and P-Q intervals is difficult, which introduces error in feature computing from the segregated intervals and compromises the performance of the classifier. In the present disclosure, a Recurrent Neural Network (RNN) based architecture comprising two Long Short Term Memory (LSTM) networks is provided for temporal analysis of R-R intervals and P wave regions in an ECG signal respectively. Output sates of the two LSTM networks are merged at a dense layer along with a set of hand-crafted statistical features to create a composite feature set for classification of the AF.
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