US 12,239,424 B2
Calibration of pulse-transit-time to blood pressure model using multiple physiological sensors and various methods for blood pressure variation
Alexandros A. Pantelopoulos, El Cerrito, CA (US); Thomas Samuel Elliot, San Francisco, CA (US); and Logan Niehaus, Colorado Springs, CO (US)
Assigned to FITBIT, INC., San Francisco, CA (US)
Filed by Fitbit, Inc., San Francisco, CA (US)
Filed on Feb. 27, 2023, as Appl. No. 18/174,931.
Application 18/174,931 is a division of application No. 15/414,425, filed on Jan. 24, 2017, granted, now 11,589,758.
Claims priority of provisional application 62/286,876, filed on Jan. 25, 2016.
Prior Publication US 2023/0293028 A1, Sep. 21, 2023
Int. Cl. A61B 5/021 (2006.01); A61B 5/00 (2006.01); A61B 5/024 (2006.01)
CPC A61B 5/02125 (2013.01) [A61B 5/7264 (2013.01); A61B 5/7278 (2013.01); A61B 5/002 (2013.01); A61B 5/02416 (2013.01); A61B 5/4812 (2013.01); A61B 5/681 (2013.01); A61B 5/7225 (2013.01); A61B 5/746 (2013.01); A61B 2503/10 (2013.01); A61B 2560/0223 (2013.01); A61B 2560/0252 (2013.01); A61B 2560/0257 (2013.01); A61B 2560/0261 (2013.01); A61B 2560/0462 (2013.01); A61B 2562/043 (2013.01); A61B 2562/16 (2013.01); A61B 2562/182 (2013.01); A61B 2562/185 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A method for calibrating a blood pressure measurement system, the method comprising:
determining, by one or more processors, based on inertial data obtained using one or more inertial sensors, whether a user associated with the blood pressure measurement system is stationary;
in response to the one or more processors determining the user associated with the blood pressure measurement system is stationary based on the inertial data and determining, by the one or more processors, a predetermined condition is satisfied, automatically initiating, by the blood pressure measurement system, a calibration operation during which a user holds a limb of the user at a plurality of positions, the calibration operation including the operations of:
obtaining, by the one or more processors:
a plurality of blood pressure measurements of the user using one or more blood pressure devices which determine the plurality of blood pressure measurements independently of a pulse transit time,
a plurality of hydrostatic pressure measurements based on altitude data obtained using the one or more inertial sensors and one or more altimeters, and
a plurality of pulse transit time (PTT) measurements based on proximal pulse wave data and distal pulse wave data obtained using a plurality of biometric sensors,
obtaining calibration data points corresponding to the plurality of blood pressure measurements, the plurality of pulse transit times measurements, and the plurality of hydrostatic pressure measurements, wherein
at least one first calibration data point among the calibration data points is obtained while the user holds the limb at a first position among the plurality of positions and at least one second calibration data point among the calibration data points is obtained while the user holds the limb at a second position among the plurality of positions, and
the one or more altimeters, the one or more inertial sensors, the plurality of biometric sensors, and the one or more blood pressure devices are attached to a same area of the limb of the user when the plurality of blood pressure measurements are obtained; and
training, by the one or more processors, a PTT-to-blood pressure machine-learned model based on the plurality of calibration data points to obtain a recalibrated PTT-to-blood pressure machine-learned model, the recalibrated PTT-to-blood pressure machine-learned model relating blood pressure to PTT and hydrostatic pressure; and
subsequent to the calibration operation, implementing the recalibrated PTT-to-blood pressure machine-learned model to predict a blood pressure value in response to measuring a PTT, associated with the user, using the plurality of biometric sensors.