US 12,453,482 B2
Continuous monitoring of a user's health with a mobile device
Alexander Vainius Valys, Sunnyvale, CA (US); Frank Losasso Petterson, Los Altos Hills, CA (US); Conner Daniel Cross Galloway, Sunnyvale, CA (US); David E. Albert, Oklahoma City, OK (US); Ravi Gopalakrishnan, San Francisco, CA (US); Lev Korzinov, San Franicsco, CA (US); Fei Wang, San Francisco, CA (US); Euan Thomson, Los Gatos, CA (US); Nupur Srivastava, San Francisco, CA (US); Omar Dawood, San Francisco, CA (US); and Iman Abuzeid, San Francisco, CA (US)
Assigned to ALIVECOR, INC., Mountain View, CA (US)
Filed by AliveCor, Inc.
Filed on Nov. 9, 2018, as Appl. No. 16/186,244.
Application 16/186,244 is a continuation in part of application No. 16/153,403, filed on Oct. 5, 2018, abandoned.
Application 16/153,403 is a continuation in part of application No. 15/393,077, filed on Dec. 28, 2016, granted, now 10,159,415.
Application 15/393,077 is a continuation of application No. 14/730,122, filed on Jun. 3, 2015, granted, now 9,572,499, issued on Feb. 21, 2017.
Application 14/730,122 is a continuation of application No. 14/569,513, filed on Dec. 12, 2014, granted, now 9,420,956, issued on Aug. 23, 2016.
Claims priority of provisional application 61/915,113, filed on Dec. 12, 2013.
Claims priority of provisional application 61/953,616, filed on Mar. 14, 2014.
Claims priority of provisional application 61/969,019, filed on Mar. 21, 2014.
Claims priority of provisional application 61/970,551, filed on Mar. 26, 2014.
Claims priority of provisional application 62/014,516, filed on Jun. 19, 2014.
Claims priority of provisional application 62/589,477, filed on Nov. 21, 2017.
Prior Publication US 2019/0076031 A1, Mar. 14, 2019
Int. Cl. A61B 5/0205 (2006.01); A61B 5/00 (2006.01); A61B 5/021 (2006.01); A61B 5/024 (2006.01); A61B 5/0245 (2006.01); A61B 5/11 (2006.01); A61B 5/349 (2021.01); A61B 5/361 (2021.01); G16H 10/60 (2018.01); G16H 15/00 (2018.01); G16H 40/63 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16Z 99/00 (2019.01)
CPC A61B 5/02055 (2013.01) [A61B 5/0022 (2013.01); A61B 5/02405 (2013.01); A61B 5/0245 (2013.01); A61B 5/349 (2021.01); A61B 5/361 (2021.01); A61B 5/681 (2013.01); A61B 5/6898 (2013.01); A61B 5/7264 (2013.01); A61B 5/7275 (2013.01); A61B 5/746 (2013.01); G16H 40/63 (2018.01); G16H 50/20 (2018.01); G16Z 99/00 (2019.02); A61B 5/021 (2013.01); A61B 5/02416 (2013.01); A61B 5/02438 (2013.01); A61B 5/1118 (2013.01); G16H 10/60 (2018.01); G16H 15/00 (2018.01); G16H 50/30 (2018.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus, comprising:
a processing device;
a low-fidelity heath-indicator data sensor operatively coupled to the processing device;
a high-fidelity health-indicator data sensor operatively coupled to the processing device; and
a memory having instructions stored thereon that, when executed by the processing device, cause the processing device to:
continuously receive measured low-fidelity health-indicator data at a first time, wherein the measured low-fidelity health-indicator data is obtained by the low-fidelity health-indicator data sensor;
input a set of data comprising the measured low-fidelity health-indicator data into a trained high-fidelity machine learning model, wherein the trained high-fidelity machine learning model is configured to utilize the measured low-fidelity health-indicator data to predict health-indicator data of the user at a future time, based on a low-fidelity health-indicator threshold and a first time threshold;
in response to the predicted health-indicator data of the user at the future time being outside a normal range: receive measured high-fidelity health-indicator data obtained by the high-fidelity health-indicator data sensor at the future time; and
in response to a determination that the measured high-fidelity health-indicator data obtained at the future time is inside the normal range: modify the low-fidelity health-indicator threshold in real-time to decrease a notification sensitivity.