US 11,793,426 B2
System and a method for determining breathing rate as a biofeedback
Gaurav Parchani, Bengaluru (IN); and Mudit Dandwate, Bengaluru (IN)
Assigned to Turtle Shell Technologies Private Limited
Filed by Turtle Shell Technologies Private Limited, Bengaluru (IN)
Filed on Aug. 26, 2020, as Appl. No. 17/3,213.
Claims priority of application No. 201941034439 (IN), filed on Aug. 27, 2019.
Prior Publication US 2021/0059539 A1, Mar. 4, 2021
Int. Cl. A61B 5/113 (2006.01); A61B 5/0205 (2006.01); A61B 5/00 (2006.01); A61B 5/024 (2006.01); G06F 18/23 (2023.01); A61B 5/16 (2006.01)
CPC A61B 5/113 (2013.01) [A61B 5/0205 (2013.01); A61B 5/02405 (2013.01); A61B 5/486 (2013.01); A61B 5/7246 (2013.01); A61B 5/7257 (2013.01); A61B 5/742 (2013.01); A61B 5/7405 (2013.01); A61B 5/7455 (2013.01); G06F 18/23 (2023.01); A61B 5/165 (2013.01)] 42 Claims
OG exemplary drawing
 
1. A system for regulating breathing rate of a subject during a meditation session or an exercise session, the system comprising:
a memory storing program instructions; and
a processor executing program instructions stored in the memory and configured to:
compute a first biomarker from micro-voltage datasets corresponding to physiological parameters associated with a subject received from a contactless sensor device;
derive a second biomarker and a third biomarker from a selected element of the first biomarker and derive a fourth biomarker from the derived third biomarker, wherein the second biomarker and the third biomarker are derived by applying machine learning clustering to extract maximas and minimas of signal waveforms into multiple templates, segregate the multiple templates into template clusters, and select a first principal template and a second principal template from the template clusters which are representative of a maximum number of instances of the second biomarker and the third biomarker respectively;
compute a first value in real-time as a function of the derived second biomarker, the derived third biomarker, and the derived fourth biomarker, wherein the first value is indicative of a stress level of the subject;
determine a correlation between the first value and a time domain Standard Deviation of Normal-to-Normal intervals (SDNN) parameter of the fourth biomarker and a frequency domain Low Frequency/High Frequency (LF/HF) parameter of the fourth biomarker, wherein the correlation is representative of an inverse relationship between the first value and the time domain parameter of the fourth biomarker and a direct relationship between the first value and the frequency domain parameter of the fourth biomarker;
compute a second value by regulating the computed first value, wherein the first value is regulated by maximizing the SDNN parameter of the fourth biomarker and minimizing the LF/HF parameter of the fourth biomarker, wherein the maximization of the SDNN parameter and the minimization of the LF/HF parameter result in reduction of the first value based on the determined correlation, the reduced first value is the computed second value which is indicative of a reduced stress level of the subject; and
transmit a biofeedback in real-time to a cue generation unit, the biofeedback is representative of a quantified data that is determined based on the second value, wherein the quantified data is indicative of a modified second biomarker for optimizing a meditation or exercise session of a subject to a relaxed and stress-free state based on a cue generated by the cue generation unit in the form of an audio, a video and a haptic feedback.