Tata Consultancy Services Limited

Dhaval Satish Jani

Avik Ghose

Arpan Pal

Dibyanshu Jaiswal

Sundeep Khandelwal

Shalini Mukhopadhyay

Soma Bandyopadhyay

Arijit Ukil

Rohan Banerjee

Sakyajit Bhattacharya

Vivek Chandel

Kartik Muralidharan

Arijt Arijt

This disclosure relates generally to methods and systems for unobtrusive digital health assessment of high risk subjects, wherein bio-markers pertaining to a disease are identified automatically using physical activity and physiology monitoring on a continuous basis. Identification of bio-markers in the medical domain is conventionally dependent on insights derived from medical tests which are obtrusive in nature. Systems and methods of the present disclosure integrate physical characteristics, lifestyle habits and prevailing medical conditions with monitored physical activities and physiological measurements to assess health of high risk subjects. Systems and methods of the present disclosure also enable automatic generation of control class and treatment class that may be effectively used for health assessment.

Systems and methods for unobtrusive digital health assessment

A system and method for extracting breathing patterns from PPG signals are provided. The method includes designing a filter for extracting breathing patterns from PPG signals. Designing the filter includes defining filter specifications for extraction of breathing pattern from the PPG signals. Herein, the filter specifications includes a type, an order and a cut-off frequency of the filter. Designing the filter further includes generating a transfer function associated with the filter specifications, and computing a plurality of filter coefficients using filtfilt function for allowing filtering of the PPG signals. Using the filter comprising the plurality of filter coefficients, a filtered PPG signal is generated by removing DC component from PPG signals obtained from a wearable device being worn by a subject. The filtered PPG signal is indicative of the breathing pattern of the subject.

System and method for breathing pattern extraction from PPG signals

This disclosure relates generally to classification of cardiopulmonary fatigue. The method and system provides a longitudinal monitoring platform to classify cardiopulmonary fatigue of a subject using a wearable device worn by the subject. The activities of the subject is continuous monitored by plurality of sensors embedded in a wearable device. The received sensor signals are processed in multiple stages to classify cardiopulmonary fatigue as healthy or unhealthy based on respiratory, heart rate and recovery duration parameters extracted from the received sensor data. Further using the classified cardiopulmonary fatigue level, the C2P also performs longitudinal analysis to detect potential cardiopulmonary disorders.

System and method to classify cardiopulmonary fatigue

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Rockville, MD, United States of America

Dhaval Satish Jani