US 12,251,210 B2
Respiration rate measurement system
Tam Ngoc Vu, Boulder, CO (US); Robin Deterding, Boulder, CO (US); Hoang Truong, Boulder, CO (US); and Nam Ngoc Bui, Broomfield, CO (US)
Assigned to The Regents of the University of Colorado, Denver, CO (US)
Appl. No. 17/284,066
Filed by The Regents of the University of Colorado, Denver, CO (US)
PCT Filed Oct. 9, 2019, PCT No. PCT/US2019/055467
§ 371(c)(1), (2) Date Apr. 9, 2021,
PCT Pub. No. WO2020/077002, PCT Pub. Date Apr. 16, 2020.
Claims priority of provisional application 62/744,062, filed on Oct. 10, 2018.
Prior Publication US 2021/0401322 A1, Dec. 30, 2021
Int. Cl. A61B 5/08 (2006.01); A61B 5/00 (2006.01); A61B 5/087 (2006.01); G16H 40/67 (2018.01); G16H 50/70 (2018.01); G16H 50/20 (2018.01)
CPC A61B 5/0816 (2013.01) [A61B 5/0004 (2013.01); A61B 5/0878 (2013.01); A61B 5/6898 (2013.01); A61B 5/7246 (2013.01); A61B 5/7278 (2013.01); A61B 5/7435 (2013.01); A61B 5/7475 (2013.01); G16H 40/67 (2018.01); G16H 50/70 (2018.01); A61B 5/0803 (2013.01); A61B 2562/0204 (2013.01); A61B 2562/0247 (2013.01); A61B 2562/0271 (2013.01); G16H 50/20 (2018.01)] 15 Claims
OG exemplary drawing
 
1. A respiratory rate measurement apparatus, comprising:
a respiratory air temperature sensor adapted to sense respiratory air temperature in a respiratory air flow, said respiratory air temperature sensor generating respiratory air temperature data varying based on sensed change in said respiratory air temperature;
a respiratory air acoustic sensor adapted to sense respiratory air acoustic energy in said respiratory air flow, said respiratory air acoustic sensor generating respiratory air acoustic energy data varying based on sensed change in said respiratory air acoustic energy;
a respiratory air pressure sensor adapted to sense respiratory air pressure in said respiratory air flow, said respiratory air pressure sensor generating respiratory air pressure data varying based on sensed change in respiratory air pressure;
a processor unit operable to:
determine whether each of said respiratory air temperature data, said respiratory air acoustic energy data, and said respiratory air pressure data has a signal condition level sufficient to pre-process;
pre-process each of said respiratory air temperature data, said respiratory air acoustic energy data, and said respiratory air pressure data to remove noise and dielectric data trends;
discretely analyze variability in intervals between successive breaths in each of said respiratory air temperature data, said respiratory air acoustic energy data, and said respiratory air pressure data collected over a time period;
determine confidence metrics based on said variability in said intervals between successive breaths in each of said respiratory air temperature data, said respiratory air acoustic energy data, and said respiratory air pressure data by comparison to a pre-selected variable rate threshold;
determine correlation coefficients based on said confidence metrics of each of said respiratory air temperature data, said respiratory air acoustic energy data, and said respiratory air pressure data collected over said time period;
measure covariance of said correlation coefficients of each of said respiratory airflow temperature data, said respiratory airflow pressure data and said respiratory airflow acoustic energy data;
generate fusion respiratory rate data of said respiratory air temperature data, said respiratory air acoustic energy data, and said respiratory air pressure data collected over said time as a weighted average based on measured covariance between said correlation coefficients; and
calculate a respiratory rate based on said fusion respiratory rate data.