Patents by Inventor Debatri CHATTERJEE

Debatri CHATTERJEE 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).

  • Publication number: 20180310851
    Abstract: A method and system is provided for pre-processing of an electroencephalography (EEG) signal for cognitive load measurement. The present application provides a method and system for pre-processing of electroencephalography signal for cognitive load measurement of a user, comprises of capturing the electroencephalography signal from the head of the user, detecting the plurality of system artifacts in the captured electroencephalography signal, detecting and removing noisy window from the captured electroencephalography signal, detecting an eye blink region and filtering out said detected eye blink region from the captured electroencephalography signal, utilizing the filtered electroencephalography signal for measuring the cognitive load of the user and subsequently computing different levels of mental workloads on the user using variation of spatial distribution of frontal scalp EEG electrodes for measured cognitive load.
    Type: Application
    Filed: October 4, 2016
    Publication date: November 1, 2018
    Applicant: Tata Consultancy Services Limited
    Inventors: Rajat Kumar DAS, Aniruddha SINHA, Debatri CHATTERJEE, Shreyasi DATTA, Rahul Dasharath GAVAS
  • Publication number: 20180098710
    Abstract: A method and system for determining cognitive load of a person using a modified baseline is provided. The person is asked to perform a series of activities including staying in eye closed rest state and baseline state and performing a trial state. Simultaneously, EEG signal and GSR signal of the person are captured. The EEG signal and the GSR signal are preprocessed and segmented. The EEG and GSR signals are then used to determine a first set and a second set of inactive states from the baseline interval and the rest interval. The most inactive window is then identified out of the first set of inactive states. The most inactive window is determined from the rest interval of the person. The inactive window is used as the modified baseline to measure the cognitive load of the person.
    Type: Application
    Filed: October 6, 2017
    Publication date: April 12, 2018
    Applicant: Tata Consultancy Services Limited
    Inventors: Rahul Dasharath GAVAS, Rajat Kumar Das, Pratyusha Das, Debatri Chatterjee, Aniruddha Sinha
  • Publication number: 20180014768
    Abstract: The present disclosure envisages a computer implemented system and method to derive a relationship between Elementary Cognitive Tasks (ECTs) and the underlying cognitive skills of individuals through Electroencephalogram (EEG) analysis. The aim is to evaluate or improve the perceptual-cognitive traits of a subject that comprises disintegrating a given task into elementary task that are further mapped to identified cognitive categories of Bloom's Taxonomy, upon which a cluster analysis is performed. The separation index between the clusters thereafter establishes that individuals have different thinking process which is characteristics of that subject.
    Type: Application
    Filed: April 7, 2016
    Publication date: January 18, 2018
    Applicant: Tata Consultancy Services Limited
    Inventors: DEBATRI CHATTERJEE, ANIRUDDHA SINHA, RAJAT KUMAR DAS, SHREYASI DATTA
  • Publication number: 20170103668
    Abstract: A method and system is provided for assessing the learning experience of the person by monitoring the mental state of the person. The method involves measuring the brain signal, skin conductance using GSR device, and heart rate variability using the pulse oximeter. These physiological signals are measured when the person is performing an activity such as the modified Stroop test. Once the activity is performed, an offline questionnaire is also filled by the person. Based on the comparison of the offline questionnaire and the physiological signals, a model is generated. This model is used to assess the learning experience of the person. According to another embodiment, a method is also provided for maintaining the steady flow state of a person while performing any activity.
    Type: Application
    Filed: October 5, 2016
    Publication date: April 13, 2017
    Applicant: Tata Consultancy Services Limited
    Inventors: Debatri CHATTERJEE, Aniruddha SINHA, Rahul Dasharath GAVAS, Rajat Kumar DAS, ARIJIT SINHARAY
  • Publication number: 20160242699
    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.
    Type: Application
    Filed: September 12, 2014
    Publication date: August 25, 2016
    Applicant: Tata Consultancy Services Limited
    Inventors: Diptesh Das, Debatri Chatterjee, Arijit Sinharay, Aniruddha Sinha
  • Patent number: 9411426
    Abstract: Disclosed are methods and systems for evaluating onscreen keyboards. The method comprises receiving a first set of parameters and a second set of parameter associated with a first onscreen keyboard and a second onscreen keyboard, respectively. The method further comprises determining a first cognitive score for the first onscreen keyboard using the first set of parameters. The method further comprises determining a second cognitive score for the second onscreen keyboard using the second set of parameters. The method further comprises validating the first cognitive score and the second cognitive score using an Electroencephalography (EEG) signal of the user. The EEG signal of the user is captured while the user is using the first onscreen keyboard and the second onscreen keyboard.
    Type: Grant
    Filed: June 23, 2014
    Date of Patent: August 9, 2016
    Assignee: Tata Consultancy Services Limited
    Inventors: Debatri Chatterjee, Arijit Sinharay, Aniruddha Sinha, Arpan Pal
  • Publication number: 20160128593
    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.
    Type: Application
    Filed: March 23, 2015
    Publication date: May 12, 2016
    Inventors: Arijit Sinharay, Aniruddha Sinha, Diptesh Das, Debatri Chatterjee
  • Publication number: 20160113539
    Abstract: Disclosed is a method and system for determining a cognitive load of a subject from Electroencephalography (EEG) signals. EEG signals are received from EEG channels associated with a left-frontal brain lobe. EEG signals are associated with a subject performing cognitive task. EEG signals are received from a low resolution EEG device. EEG channels comprise four EEG channels associated with the left-frontal brain lobe. EEG signals are preprocessed using a Hilbert-Huang Transform (HHT) filter to remove a noise corresponding to one or more non-cerebral artifacts to generate preprocessed EEG signals. Features comprising Fast Fourier Transform (FFT) based alpha and theta band power are extracted from the preprocessed EEG signals. Feature vector is generated from the features. The feature vector is classified using a Support Vector Machine (SVM) classifier to determine the cognitive load of the subject.
    Type: Application
    Filed: February 20, 2015
    Publication date: April 28, 2016
    Inventors: Arijit SINHARAY, Debatri CHATTERJEE, Arpan PAL
  • Publication number: 20150128185
    Abstract: Disclosed is a system and method for personalizing an appliance's functioning remotely in real-time. The user profile and set of parameters affecting the functionality of the appliance are received by a computing device by, for example, communication module and are matched by a data delivery device to pre-defined parameters stored therein, for the profile categorization. An output profile is generated and is defined by matched parameters. The appliance is remotely controlled by modifying the functioning of the appliance in accordance with the output profile defined by the matched parameters.
    Type: Application
    Filed: May 16, 2013
    Publication date: May 7, 2015
    Inventors: Kingshuk Chakravarty, Debatri Chatterjee, Somnath Ghosh Dastidar, Aniruddha Sinha
  • Publication number: 20140375567
    Abstract: Disclosed are methods and systems for evaluating onscreen keyboards. The method comprises receiving a first set of parameters and a second set of parameter associated with a first onscreen keyboard and a second onscreen keyboard, respectively. The method further comprises determining a first cognitive score for the first onscreen keyboard using the first set of parameters. The method further comprises determining a second cognitive score for the second onscreen keyboard using the second set of parameters. The method further comprises validating the first cognitive score and the second cognitive score using an Electroencephalography (EEG) signal of the user. The EEG signal of the user is captured while the user is using the first onscreen keyboard and the second onscreen keyboard.
    Type: Application
    Filed: June 23, 2014
    Publication date: December 25, 2014
    Inventors: Debatri CHATTERJEE, Arijit SINHARAY, Aniruddha SINHA, Arpan PAL