US 11,883,158 B2
Predicting occupant exit from support apparatus
Justin Bender, Cincinnati, OH (US); Kin Meng Choi, Batesville, IN (US); Anthony Cohn, Harrison, OH (US); Frederick Keith Schultz, Bringhurst, IN (US); Sridhar Karimpuzha Seshadri, Blue Ash, OH (US); and Thomas L. Simpson, Brookville, IN (US)
Assigned to Hill-Rom Services, Inc., Batesville, IN (US)
Filed by Hill-Rom Services, Inc., Batesville, IN (US)
Filed on May 17, 2021, as Appl. No. 17/322,031.
Claims priority of provisional application 63/035,196, filed on Jun. 5, 2020.
Prior Publication US 2021/0378551 A1, Dec. 9, 2021
Int. Cl. A61B 5/11 (2006.01); A61B 5/00 (2006.01); A61G 7/05 (2006.01)
CPC A61B 5/1115 (2013.01) [A61B 5/1126 (2013.01); A61B 5/7264 (2013.01); A61B 5/746 (2013.01); A61B 5/747 (2013.01); A61G 7/052 (2016.11); A61G 7/0524 (2016.11); A61G 2203/32 (2013.01); A61G 2203/44 (2013.01)] 13 Claims
OG exemplary drawing
 
1. An exit prediction system comprising:
a bed including:
a frame;
one or more force sensors positioned on the frame; and
a computing device included on the bed, the computing device including:
a processing unit; and
a memory in communication with the processing unit; the memory storing machine-readable instructions that, when executed by the processing unit, cause the processing unit to:
receive data inputs from the one or more force sensors, the data inputs being received without zeroing the one or more force sensors, wherein the data inputs are analog-to-digital (A/D) counts;
detect changes in the data inputs from the one or more force sensors, wherein the detected changes in the data inputs are detected changes in the A/D counts received from each of the force sensors individually;
store predefined changes in A/D counts associated with movement trends, wherein the movement trends are associated with movements performed by occupants in order to exit the bed;
determine whether the detected changes indicate a movement trend by comparing the detected changes to the predefined changes to determine whether the detected changes are indicative of the movement trend;
determine an exit prediction based at least partially on the movement trend, the exit prediction being determined without combining the data inputs from the one or more force sensors to determine a weight of an occupant of the bed; and
generate a notification based on the exit prediction, wherein the notification is generated on the bed.