US 12,011,259 B2
Systems and methods for fall detection
Anthony Dohrmann, Las Cruces, NM (US); David W. Keeley, Frisco, TX (US); Roberto Abel Salcido, Las Cruces, NM (US); and James Mitchell, Las Cruces, NM (US)
Assigned to ELECTRONIC CAREGIVER, INC., Las Cruces, NM (US)
Filed by Electronic Caregiver, Inc., Las Cruces, NM (US)
Filed on Sep. 4, 2020, as Appl. No. 17/013,357.
Application 17/013,357 is a continuation of application No. 15/530,185, filed on Dec. 9, 2016, granted, now 10,813,572.
Claims priority of provisional application 62/386,768, filed on Dec. 11, 2015.
Prior Publication US 2021/0007631 A1, Jan. 14, 2021
Int. Cl. A61B 5/00 (2006.01); A61B 5/103 (2006.01); A61B 5/11 (2006.01); A61B 5/1171 (2016.01); A61B 5/0205 (2006.01)
CPC A61B 5/1117 (2013.01) [A61B 5/0013 (2013.01); A61B 5/0077 (2013.01); A61B 5/1036 (2013.01); A61B 5/1127 (2013.01); A61B 5/1128 (2013.01); A61B 5/1176 (2013.01); A61B 5/4833 (2013.01); A61B 5/4866 (2013.01); A61B 5/7275 (2013.01); A61B 5/746 (2013.01); A61B 5/749 (2013.01); A61B 5/02055 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for automated fall detection and reporting via a virtual system, the virtual system comprising at least one processor configured to execute the method comprising:
receiving, at the at least one processor in the virtual system, from a depth camera configured to be pointed at a human, a first data set of virtual movement markers comprising a cluster of data points in a shape of a body of the human, the first data set of virtual movement markers comprising a first movement marker estimated to a head location of the human, a second movement marker estimated to a spine location of the human, and a third movement marker estimated to a joint location of the human;
receiving, at the at least one processor in the virtual system, from the depth camera a second data set of virtual movement markers indicating volume in an area of a location of the human:
detecting, at the at least one processor in the virtual system, a first irregular pattern of activity for the human based on the volume in the area of the location of the human over a prescribed period of time;
sending, at the at least one processor in the virtual system, a first alert to a reporting device indicating that the human has fallen based on the detection of the first irregular pattern of activity;
detecting, at the at least one processor in the virtual system, from an accelerometer, a rapid acceleration of at least two of the movement markers comprising the first data set of virtual movement markers, followed by a rapid deceleration of the at least two of the movement markers comprising the first data set of virtual movement markers, wherein at least one of the rapid acceleration and the rapid deceleration includes a rapid change in direction of a location of at least one of the movement markers comprising the first data set of virtual movement markers;
detecting, at the at least one processor in the virtual system, a second irregular pattern of activity for the human from changes in the first data set of virtual movement markers; and
sending, at the at least one processor in the virtual system, a second alert to the reporting device indicating that the human has fallen based on the second detected irregular pattern of activity.