Tata Consultancy Services Limited

Srinivasan Jayaraman

Balamuralidhar Purushothaman

Joshin Sahadevan

Midhun Parakkal Unni

Arpan Pal

Aniruddha Sinha

Sundeep Khandelwal

Kriti Kumar

Ramesh Kumar Ramakrishnan

Murali Poduval

Naveen Kumar Thokala

Venkatesh Narasimha Murthy

Harshad Chandrakant Kulkarni

Ponnuraj Kirthi Priya

Midhun P Unni

Continuous monitoring of subject's cardiac system using biological signal(s) (BS) during day-to-day activities is essential for managing personal cardiac health/disorders, etc. Conventional systems/methods lack in improvising overall classification results and configured for specific device/signal say ECG or PPG and so on. Present disclosure provides systems and methods for classifying BS obtained from users, wherein BS are preprocessed to obtain filtered signals (FS). Corresponding feature extraction module is utilized for feature set extraction based on features in FS. The feature set is reduced and segmented into test and training data. Biological signal classification model(s) are generated using training data and a BCM is applied on test data to classify biological signals (BS) as one of Atrial Fibrillation (AF), a non-AF, a cardiac arrythmia disorder, or ischemia. Accelerometer features of connected device associated with the users can be obtained to detect activities which in conjunction with the BCM's output improvises above classification.

Systems and methods for atrial fibrillation (AF) and cardiac disorders detection from biological signals

This disclosure relates generally to a system and method for shoulder proprioceptive analysis of the person. The present disclosure monitors the shoulder joint motion by quantitative measure of range of motion (ROM) and kinesthesia of shoulder using a smart watch, thereby assessing the limit of active motion and the ability to passively reposition the arm in space. The present disclosure estimates the ROM, velocity, quality of joint movement, direction of hand movement using the sensor data captured by the smart watch. Further, the present disclosure provides a performance metrics of the shoulder function by comparing the shoulder motion before and after a prosthesis procedure. The present disclosure implements a rule engine-based approach classifying the shoulder/arm movement which includes flexion, extension, abduction, and adduction, internal and external rotation.

System and method for shoulder proprioceptive analysis

A system and method for determining stress level of a person in real-time have been disclosed. In one aspect, the system captures physiological data associated to the person. In one embodiment, the physiological data may be captured by using a plurality of sensors attached at wrist or ankle or neck or waist or hip of the person, for a predetermined time interval. The plurality of sensors may include a wrist watch or a wristband or a textile material. The system further pre-processes the physiological data in order to extract one or more physiological parameters. In one aspect, the pre-processing may include performing an analysis on the physiological data. The system further determines the stress level of the person upon performing the statistical analysis on the one or more physiological parameters. According to another embodiment, a method for real time determination of stress level of the person has also been provided.

System and method for determining psychological stress of a person

A method and device is provided for the continuous estimation of the blood pressure using a noninvasive technique. The method involves sensing of the displacement signal generated by the palpation of the radial artery. The radial artery is modelled as a cylindrical voight type viscoelastic tissue for the estimation of the personalized blood pressure. The model includes the displacement signal and a set of parameters as an input. The set of parameters include a mean radius of the artery, a radius at zero mmHg, a viscoelastic damping parameter, an elasticity of the artery and a thickness of wall of artery. The method involves the optimization of the set of parameters using heuristic optimization techniques, which helps in the estimation of the systolic and diastolic blood pressure. The method and device can also be personalized for individualized monitoring and estimation of the blood pressure of the person.

Method and device for continuous blood pressure monitoring and estimation

The present subject matter relates to a computer implemented method for real time determination of stress levels of an individual. The method includes receiving at least one stream of physiological data from at least one primary sensor for a predetermined duration, and preprocessing the at least one stream of physiological data to extract physiological parameters, where the preprocessing includes performing a preliminary analysis on the at least one stream of physiological data. The method further includes determining a stress level of the individual based on at least the physiological parameters, wherein the determining comprises performing a statistical analysis on the physiological parameters.

Real-time stress determination of an individual

A system and method for determining a stress level of a person is provided. The system creates a numerical solution to mathematical model of a blood pressure (BP) regulation, lumped mathematical model of a radial artery and partial differential equation (PDE) model of the radial artery. These models are then used to generate an inference engine using the mathematical model of blood pressure (BP) regulation, the lumped mathematical model of the radial artery and the PDE model of the radial artery. The inference engine is trained using an artificial neural network technique. At the same time the PPG signal of the person is sensed and preprocessed. The preprocessed PPG signal is then given to the trained inference engine. The trained inference engine generates a stress parameter corresponding to the person based on the processed PPG signal.

Method and system for estimation of stress of a person using photoplethysmography

A device and method is provided for the detection of diabetes in a person using pulse palpation signals. The pulse palpation signal is captured from the radial artery of the person using a photo-plethysmograph (PPG) sensor. The PPG signal is then preprocessed by a processor. The preprocessed PPG signal is then analyzed by the processor to detect the peak in the PPG signal. The detected peaks are used to extract a first set of feature parameters. The first of feature parameters are compared with a second set of feature parameters, wherein the second set of feature parameters are extracted from the control group of individuals. Based on the comparison it is detected that the person is one of in normal condition, pre-diabetic condition or a diabetic condition. According to another embodiment, the invention also provides a method to determine the severity index and progression risk of diabetes in the person.

Device and method to detect diabetes in a person using pulse palpation signal

Systems and methods for determining an actual fatigue time (AFT) for an activity are provided. The method comprises receiving a standard fatigue time (SFT) representing a time duration. The SFT is indicative of an onset of fatigue in individuals upon continuously performing the activity. The method further comprises receiving at least one external parameter and a fatigue index corresponding to the at least one external parameter. The at least one external parameter and the fatigue index are associated with the activity. The method further comprises determining the AFT for the activity based upon the SFT and the fatigue index.

Fatigue time determination for an activity

A system and a method for secure data communication over a network are described. In one embodiment, a method comprises generating a visual flashing code containing encrypted data, wherein the visual flashing code is transmitted to a user on a user device. Further, the method comprises obtaining real time biometric data of the user from at least one biometric device connected to the user device. Furthermore, the method comprises authenticating the user based on the real time biometric data. Upon authentication, the encrypted data is decrypted at the user device based on electroencephalogram (EEG) data obtained from an EEG device, wherein the EEG data comprises brain signals indicative of brain activity of the user corresponding to the visual flashing code.

Growing community of inventors

Bengaluru, India

Srinivasan Jayaraman