US 12,133,717 B2
Systems and methods for patient fall detection
Ammar Al-Ali, San Juan Capistrano, CA (US); Cornelius Raths, Irvine, CA (US); and Mohammad Usman, Mission Viejo, CA (US)
Assigned to Masimo Corporation, Irvine, CA (US)
Filed by Masimo Corporation, Irvine, CA (US)
Filed on Jul. 5, 2021, as Appl. No. 17/305,325.
Application 17/305,325 is a continuation of application No. 17/075,510, filed on Oct. 20, 2020, granted, now 11,089,963.
Application 17/075,510 is a continuation of application No. 16/567,584, filed on Sep. 11, 2019.
Application 16/567,584 is a continuation of application No. 15/253,355, filed on Aug. 31, 2016, granted, now 10,448,844, issued on Oct. 22, 2019.
Claims priority of provisional application 62/212,484, filed on Aug. 31, 2015.
Claims priority of provisional application 62/212,467, filed on Aug. 31, 2015.
Claims priority of provisional application 62/212,472, filed on Aug. 31, 2015.
Claims priority of provisional application 62/212,480, filed on Aug. 31, 2015.
Prior Publication US 2021/0330200 A1, Oct. 28, 2021
Int. Cl. A61B 5/0205 (2006.01); A61B 5/00 (2006.01); A61B 5/01 (2006.01); A61B 5/0245 (2006.01); A61B 5/05 (2021.01); A61B 5/053 (2021.01); A61B 5/11 (2006.01); A61B 5/113 (2006.01); A61B 5/1455 (2006.01); A61B 5/25 (2021.01); A61B 5/318 (2021.01); A61B 5/08 (2006.01); A61G 7/057 (2006.01)
CPC A61B 5/02055 (2013.01) [A61B 5/0004 (2013.01); A61B 5/0015 (2013.01); A61B 5/002 (2013.01); A61B 5/0022 (2013.01); A61B 5/004 (2013.01); A61B 5/01 (2013.01); A61B 5/0205 (2013.01); A61B 5/0245 (2013.01); A61B 5/05 (2013.01); A61B 5/053 (2013.01); A61B 5/1113 (2013.01); A61B 5/1116 (2013.01); A61B 5/1117 (2013.01); A61B 5/1118 (2013.01); A61B 5/1121 (2013.01); A61B 5/1126 (2013.01); A61B 5/113 (2013.01); A61B 5/14552 (2013.01); A61B 5/25 (2021.01); A61B 5/318 (2021.01); A61B 5/447 (2013.01); A61B 5/6801 (2013.01); A61B 5/6823 (2013.01); A61B 5/6833 (2013.01); A61B 5/68335 (2017.08); A61B 5/7264 (2013.01); A61B 5/7275 (2013.01); A61B 5/7282 (2013.01); A61B 5/742 (2013.01); A61B 5/743 (2013.01); A61B 5/746 (2013.01); A61B 5/0816 (2013.01); A61B 5/14551 (2013.01); A61B 2560/0475 (2013.01); A61B 2562/0204 (2013.01); A61B 2562/0219 (2013.01); A61B 2562/0223 (2013.01); A61B 2562/0271 (2013.01); A61B 2562/029 (2013.01); A61G 7/057 (2013.01); A61G 2203/32 (2013.01); A61G 2203/36 (2013.01); A61G 2203/42 (2013.01); A61G 2203/46 (2013.01)] 24 Claims
OG exemplary drawing
 
1. A method comprising:
obtaining motion data originating from an accelerometer and a gyroscope of a wearable wireless device,
wherein said motion data is indicative of motion of a subject over a time period when the wearable wireless device is worn by the subject,
wherein said motion data is indicative of movement and orientation of the subject;
accessing a user-generated environment configuration generated via a graphical user interface and indicating user-configurable positions of one or more physical objects within the environment;
monitoring a spatial location of the subject within an environment relative to the user-configurable positions of the one or more physical objects as the subject walks throughout the environment based on said motion data originating from the accelerometer and the gyroscope of the wearable wireless device;
determining whether the subject has adhered to a movement prescription based on at least the spatial location of the subject relative to the user-configurable positions of the one or more physical objects,
wherein the movement prescription indicates an allowed movement type and a prohibited movement type for the subject relative to the user-configurable positions of the one or more physical objects;
correlating, with one or more processors of the wearable wireless device, at least a portion of said motion data with training data comprising a plurality of fall and non-fall scenarios;
determining, with said one or more processors of the wearable wireless device and based on at least said motion data, an impact experienced by the subject during a first portion of the time period;
determining, with said one or more processors of the wearable wireless device and based on at least said motion data, one or more first activity characteristics representative of the subject's motion during a second portion of the time period that is prior to said impact;
determining, with said one or more processors of the wearable wireless device and based on at least said motion data, rotation of the subject during at least a portion of the time period and comparing said rotation to a first threshold;
determining, with said one or more processors of the wearable wireless device and based on at least said motion data, one or more second activity characteristics representative of the subject's motion during a third portion of the time period that is after said impact;
determining, with said one or more processors of the wearable wireless device, that the subject experienced a fall based on at least said impact, said one or more first activity characteristics representative of the subject's motion during the second portion of the time period that is prior to said impact, said rotation exceeding said first threshold, and said one or more second activity characteristics representative of the subject's motion during the third portion of the time period that is after said impact;
and responsive to determining that the subject experienced said fall:
determining a spatial location of said fall within the environment;
and generating, with the wearable wireless device, an alert indicating that the subject experienced said fall and the spatial location of said fall.