Patents by Inventor Deepan Das

Deepan Das has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11419542
    Abstract: Monitoring the quality of sleep of an individual is essential for ensuring one's overall well-being. The existing methods for non-apnea sleep arousal detection are manual. A system and method for the non-apnea sleep arousal detection has been provided. The method uses a feature engineering based binary classification approach for distinguishing non-apnea arousal and non-arousal. A training data set is prepared using a plurality of physiological signals. A plurality of features are derived from the training data set. Out of those only a set of features are selected for training a plurality of random forest classifier models. A test sample is then provided to the plurality of random forest classifier models in the instances of fixed duration. This results in generation of prediction probabilities for each instances. The prediction probabilities are then used to predict the probabilities of non-apnea sleep arousal in the test sample.
    Type: Grant
    Filed: September 20, 2019
    Date of Patent: August 23, 2022
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Tanuka Bhattacharjee, Deepan Das, Shahnawaz Alam, Rohan Banerjee, Anirban Dutta Choudhury, Arpan Pal, Achuth Rao Melavarige Venkatagiri, Prasanta Kumar Ghosh, Ayush Ranjan Lohani
  • Patent number: 11373757
    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.
    Type: Grant
    Filed: March 6, 2018
    Date of Patent: June 28, 2022
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Deepan Das, Rohan Banerjee, Anirban Dutta Choudhury, Parijat Dilip Deshpande, Nital Shah, Vijay Anil Date, Arpan Pal, Kayapanda Muthana Mandana
  • Patent number: 11354339
    Abstract: A method and system for clustering users using cognitive stress report for classifying stress levels is provided. Detection and monitoring of cognitive stress experienced by users while performing a task is very crucial. The method includes receiving, user evaluated cognitive stress reports and the physiological signals of the user during the performance of the task. A normalized cognitive report is generated from the user evaluated cognitive stress report by computing mode and range value. The normalized cognitive stress reports of the users are used to cluster the users into a primary cluster and a secondary cluster. Feature sets are extracted from the physiological signals of the said users associated with the primary cluster. Using the said feature sets a classifier model is trained to classify the cognitive stress levels of the users as stressful class or stressless class.
    Type: Grant
    Filed: July 9, 2019
    Date of Patent: June 7, 2022
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Deepan Das, Shreyasi Datta, Tanuka Bhattacharjee, Anirban Dutta Choudhury, Arpan Pal
  • Patent number: 11045136
    Abstract: Traditionally arousal classification has been broadly done in multiple classes but have been insufficient to provide information about how arousal level of user changes over time. Present disclosure propose a continuous and unsupervised approach of monitoring the arousal trend of individual from his/her heart rate by obtaining instantaneous HR for time windows from a resampled time series of RR intervals obtained from ECG signal. A measured average heart rate (a measured HR) is computed from instantaneous HR specific to user for each time window thereby estimating apriori state based on a last instance of an aposteriori state initialized and observation of a state space model of Kalman Filter is determined for computing error and normalizing thereof which gets compared with a threshold for continuous monitoring of arousal trend of the user. The aposterior state is further updated using Kalman gain computed based on measurement noise determined for state space model.
    Type: Grant
    Filed: November 14, 2018
    Date of Patent: June 29, 2021
    Assignee: Tata Consultancy Services Limited
    Inventors: Tanuka Bhattacharjee, Shreyasi Datta, Deepan Das, Anirban Dutta Choudhury, Arpan Pal, Prasanta Kumar Ghosh
  • Patent number: 10716501
    Abstract: This disclosure relates generally to stress classification and quantification, and more particularly to system and method for classification and quantitative estimation of cognitive stress from analysis of keystrokes and signals derived from physiological sensors. In one embodiment, a method includes obtaining, while a user is engaged in performance of a task, physiological signals from physiological sensors accessible to the user. Feature sets are identified from the physiological signals which correlate with cognitive stress experienced by the user. Using a regression model, a stress indicator metric comprising a quantitative estimate of the cognitive stress is predicted. The regression model is trained using the feature sets and independently determined quantitative estimates of cognitive stress used as a ground truth to output the value of the stress indicator metric.
    Type: Grant
    Filed: March 6, 2018
    Date of Patent: July 21, 2020
    Assignee: Tata Consultancy Services Limited
    Inventors: Deepan Das, Tanuka Bhattacharjee, Shreyasi Datta, Anirban Dutta Choudhury, Pratyusha Das, Arpan Pal
  • Publication number: 20200093425
    Abstract: Monitoring the quality of sleep of an individual is essential for ensuring one's overall well-being. The existing methods for non-apnea sleep arousal detection are manual. A system and method for the non-apnea sleep arousal detection has been provided. The method uses a feature engineering based binary classification approach for distinguishing non-apnea arousal and non-arousal. A training data set is prepared using a plurality of physiological signals. A plurality of features are derived from the training data set. Out of those only a set of features are selected for training a plurality of random forest classifier models. A test sample is then provided to the plurality of random forest classifier models in the instances of fixed duration. This results in generation of prediction probabilities for each instances. The prediction probabilities are then used to predict the probabilities of non-apnea sleep arousal in the test sample.
    Type: Application
    Filed: September 20, 2019
    Publication date: March 26, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: Tanuka BHATTACHARJEE, Deepan DAS, Shahnawaz ALAM, Rohan BANERJEE, Anirban DUTTA CHOUDHURY, Arpan PAL, Achuth RAO MELAVARIGE VENKATAGIRI, Prasanta Kumar GHOSH, Ayush Ranjan LOHANI
  • Publication number: 20200012665
    Abstract: A method and system for clustering users using cognitive stress report for classifying stress levels is provided. Detection and monitoring of cognitive stress experienced by users while performing a task is very crucial. The method includes receiving, user evaluated cognitive stress reports and the physiological signals of the user during the performance of the task. A normalized cognitive report is generated from the user evaluated cognitive stress report by computing mode and range value. The normalized cognitive stress reports of the users are used to cluster the users into a primary cluster and a secondary cluster. Feature sets are extracted from the physiological signals of the said users associated with the primary cluster. Using the said feature sets a classifier model is trained to classify the cognitive stress levels of the users as stressful class or stressless class.
    Type: Application
    Filed: July 9, 2019
    Publication date: January 9, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: Deepan DAS, Shreyasi DATTA, Tanuka BHATTACHARJEE, Anirban DUTTA CHOUDHURY, Arpan PAL
  • Publication number: 20200000360
    Abstract: Traditionally arousal classification has been broadly done in multiple classes but have been insufficient to provide information about how arousal level of user changes over time. Present disclosure propose a continuous and unsupervised approach of monitoring the arousal trend of individual from his/her heart rate by obtaining instantaneous HR for time windows from a resampled time series of RR intervals obtained from ECG signal. A measured average heart rate (a measured HR) is computed from instantaneous HR specific to user for each time window thereby estimating apriori state based on a last instance of an aposteriori state initialized and observation of a state space model of Kalman Filter is determined for computing error and normalizing thereof which gets compared with a threshold for continuous monitoring of arousal trend of the user. The aposterior state is further updated using Kalman gain computed based on measurement noise determined for state space model.
    Type: Application
    Filed: November 14, 2018
    Publication date: January 2, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: Tanuka BHATTACHARJEE, Shreyasi DATTA, Deepan DAS, Anirban DUTTA CHOUDHURY, Arpan PAL, Prasanta Kumar GHOSH
  • Publication number: 20190175091
    Abstract: This disclosure relates generally to stress classification and quantification, and more particularly to system and method for classification and quantitative estimation of cognitive stress from analysis of keystrokes and signals derived from physiological sensors. In one embodiment, a method includes obtaining, while a user is engaged in performance of a task, physiological signals from physiological sensors accessible to the user. Feature sets are identified from the physiological signals which correlate with cognitive stress experienced by the user. Using a regression model, a stress indicator metric comprising a quantitative estimate of the cognitive stress is predicted. The regression model is trained using the feature sets and independently determined quantitative estimates of cognitive stress used as a ground truth to output the value of the stress indicator metric.
    Type: Application
    Filed: March 6, 2018
    Publication date: June 13, 2019
    Applicant: Tata Consultancy Services Limited
    Inventors: Deepan DAS, Tanuka BHATTACHARJEE, Shreyasi DATTA, Anirban Dutta CHOUDHURY, Pratyusha DAS, Arpan PAL
  • Publication number: 20190013102
    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.
    Type: Application
    Filed: March 6, 2018
    Publication date: January 10, 2019
    Applicant: Tata Consultancy Services Limited
    Inventors: Deepan Das, Rohan Banerjee, Anirban Dutta Choudhury, Parijat Dilip Deshpande, Nital Shah, Vijay Anil Date, Arpan Pal, Kayapanda Muthana Mandana