Medical environment monitoring system

• US 9,538,158 B1
• Filed: 10/16/2013
• Issued: 01/03/2017
• Est. Priority Date: 10/16/2012
• Status: Active Grant

• Current Assignee: Ocuvera LLC
• Original Assignee: Ocuvera LLC
• Inventors: Gansemer, Brian S., Bauer, Paul B., Unterseher, Andrew R., Origas, Benjamin J., Durham, Douglas W., Rush, Benjamin D., Brown-Kramer, Joshua M., Sabalka, Lucas A., Upton, Clay T.
• Primary Examiner(s): Hoekstra, Jeffrey G
• Assistant Examiner(s): Leedy, Megan
• Application Number:
  US14/055,139
• Time in Patent Office: 1,175 Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• CPC Class Codes: A61B 5/1115 Monitoring leaving of a patient support, e.g. a bed or a wheelchair
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/1128 using image analysis A61B5/1127 takes precedence
• CPC Class Codes: A61B 5/4815 Sleep quality
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G08B 21/0476 Cameras to detect unsafe condition, e.g. video cameras
• CPC Class Codes: H04N 13/207 using a single 2D image sensor

Abstract

A system and a method are described for monitoring a medical care environment. In one or more implementations, a method includes identifying a first subset of pixels within a field of view of a camera as representing a bed. The method also includes identifying a second subset of pixels within the field of view of the camera as representing an object (e.g., a subject, such as a patient, medical personnel; bed; chair; patient tray; medical equipment; etc.) proximal to the bed. The method also includes determining an orientation of the object within the bed.

Claims

1. A system for monitoring a medical care environment, the system comprising:

an imaging device having an imaging plane, the imaging device configured to receive a plurality of depth frame images comprising a plurality of pixels, the plurality of depth frame images representing a three-dimensional environment corresponding to a physical space, the physical space including at least one of a bed or a chair;

at least one computing device in communication with the imaging device, the at least one computing device including;

a memory configured to store one or more modules;

a processor coupled to the memory, the processor configured by a fusion engine and the one or more modules to cause the processor to;

generate a depth mask representing the physical space based upon the plurality of depth frame images;

identify one or more first pixels of the plurality of pixels as representing the at least one of the bed or the chair based upon the depth mask;

identify one or more second pixels of the plurality of pixels as representing a portion of a body of a subject proximate to the at least one of the bed or the chair;

process, via a first processing technique, the one or more second pixels to generate a first possible orientation signal of the portion of the body with respect to the image plane, the first possible orientation signal representing a position of the portion of the body with respect to the at least one of the bed or the chair;

process, via a second processing technique via the fusion engine, the one or more second pixels to generate a second possible orientation signal of the portion of the body with respect to the image plane, the second possible orientation signal representing the position of the portion of the body with respect to the at least one of the bed or the chair;

determine a probability distribution based upon the first possible orientation signal and the second possible orientation signal via the fusion engine;

determine a transitional state of the subject based upon the probability distribution; and

issue an electronic communication based upon the determined transitional state of the subject, the electronic communication comprising an alert indicating the transitional state of the subject.

2. The system as recited in claim 1, wherein the processor is further configured to execute the one or more modules to cause the processor to process, via at least one of the first processing technique or the second processing technique, the depth frame image to identify a position of at least one of a second subject or an object relative to the subject.

3. The system as recited in claim 1, wherein the processor is further configured to execute the one or more modules to cause the processor to process the depth frame image to detect at least one of a presence or an absence of a gesture;

and provide an indication associated with the at least one of the presence or the absence of the gesture.

4. The system as recited in claim 1, wherein the processor is further configured to execute the one or more modules to cause the processor to track the one or more second pixels through the plurality of depth frame images;

determine an activity parameter of the subject based upon the tracked one or more second pixels; and

issue an activity electronic communication indicating the activity parameter when the activity parameter is outside of an activity threshold.

5. The system as recited in claim 1, wherein the processor is further configured to execute the one or more modules to cause the processor to process, via a third processing technique via the fusion engine, the one or more second pixels to generate a third possible orientation signal of the portion of the body, the third possible orientation signal representing the position of the portion of the body with respect to the at least one of the bed or the chair;

and

determine the probability distribution based upon the first possible orientation signal, the second possible orientation signal, and the third possible orientation signal via the fusion engine.

6. The system as recited in claim 1, wherein the processor is further configured to execute the one or more modules to cause the processor to determine the probability distribution based upon the first possible orientation signal, the second possible orientation signal, and at least one characteristic of the subject via the fusion engine.

7. The system as recited in claim 6, wherein the characteristic comprises at least one of age, gender, weight, body type, body dimensions, diagnoses, time of day, gait characteristics, mental status, physical restrictions, facial deformalities, sleeping abnormalities, angle of bed, dimensions of bed, fall risk score, patient schedule, subject ethnicity, subject skin tone, and bed characteristics.

8. A method for monitoring a subject within a medical care environment, the method comprising:

generating, via a processor configured by a fusion engine, a depth mask representing the physical space based upon a plurality of depth frame images received from an imaging device, the plurality of depth frame images representing a three-dimensional environment corresponding to a physical space, the physical space including at least one of a bed or a chair;

identifying, via the processor, one or more first pixels of the plurality of pixels as representing the at least one of the bed or the chair based upon the depth mask;

identifying, via the processor, one or more second pixels of the plurality of pixels as representing a portion of a body of a subject proximate to the at least one of the bed or the chair;

processing, via a first processing technique, the one or more second pixels to generate a first possible orientation signal of the portion of the body with respect to the image plane, the first possible orientation signal representing a position of the portion of the body with respect to the at least one of the bed or the chair;

processing, via a second processing technique via the fusion engine, the one or more second pixels to generate a second possible orientation signal of the portion of the body with respect to the image plane, the second possible orientation signal representing the position of the portion of the body with respect to the at least one of the bed or the chair;

determining a probability distribution based upon the first possible orientation signal and the second possible orientation signal via the fusion engine;

determining a transitional state of the subject based upon the probability distribution; and

issuing an electronic communication based upon the determined transitional state of the subject, the electronic communication comprising an alert indicating the transitional state of the subject.

9. The method as recited in claim 8, further comprising identifying a presence of a gesture based upon the one or more second pixels;

and providing an indication associated with the presence of the gesture.

10. The method as recited in claim 8, further comprising:

tracking the one or more second pixels through the plurality of depth frame images;

determining an activity parameter of the subject based upon the tracked one or more second pixels; and

issuing an activity electronic communication indicating the activity parameter when the activity parameter is outside of an activity threshold.

11. The method as recited in claim 8, further comprising:

processing, via a third processing technique via the fusion engine, the one or more second pixels to generate a third possible orientation signal of the portion of the body, the third possible orientation signal representing the position of the portion of the body with respect to the at least one of the bed or the chair; and

determining the probability distribution based upon the first possible orientation signal, the second possible orientation signal, and the third possible orientation signal via the fusion engine.

12. The method as recited in claim 8, wherein determining the probability distribution further comprises determining the probability distribution based upon the first possible orientation signal, the second possible orientation signal, and at least one characteristic of the subject via the fusion engine.

13. The method as recited in claim 12, wherein the characteristic comprises at least one of age, gender, weight, body type, body dimensions, diagnoses, time of day, gait characteristics, mental status, physical restrictions, facial deformalities, sleeping abnormalities, angle of bed, dimensions of bed, fall risk score, patient schedule, subject ethnicity, subject skin tone, and bed characteristics.

14. A method for monitoring a medical care environment, the method comprising:

receiving a plurality of depth frame images, each depth frame image of the plurality of depth frame images comprising a plurality of pixels the plurality of depth frame images captured by an imaging device having an image plane, the plurality of depth frame images representing a three-dimensional environment corresponding to a physical space, the physical space including at least one of a bed or a chair;

generating, via a processor configured by a fusion engine, a depth mask representing the physical space based upon a plurality of depth frame images received from an imaging device;

identifying, via the processor, one or more first pixels of the plurality of pixels as representing the at least one of the bed or the chair based upon the depth mask;

identifying, via the processor, one or more second pixels of the plurality of pixels as representing a body part of a subject proximate to the at least one of the bed or the chair;

processing, via a first processing technique, the one or more second pixels to generate a first possible orientation signal of the body part with respect to the image plane, the first possible orientation signal representing a position of the body part with respect to the at least one of the bed or the chair;

processing, via a second processing technique via the fusion engine, the one or more second pixels to generate a second possible orientation signal of the body part with respect to the image plane, the second possible orientation signal representing the position of the body part with respect to the at least one of the bed or the chair;

determining, via the processor, a probability distribution based upon the first possible orientation signal and the second possible orientation signal via the fusion engine;

determining a transitional state of the subject based upon the probability distribution; and

issuing an electronic communication based upon the determined transitional state of the subject, the electronic communication comprising an alert indicating the transitional state of the subject.

15. The method as recited in claim 14, further comprising:

processing, via a third processing technique via the fusion engine, the one or more second pixels to generate a third possible orientation signal of the body part with respect to the image plane, the third possible orientation signal representing the position of the body part with respect to the at least one of the bed or the chair;

processing, via a fourth processing technique via the fusion engine, the one or more second pixels to generate a fourth possible orientation signal of the body part with respect to the image plane, the fourth possible orientation signal representing the position of the body part with respect to the at least one of the bed or the chair; and

determine the probability distribution based upon the first possible orientation signal, the second possible orientation signal, the third possible orientation signal, and the fourth possible orientation signal via the fusion engine.

16. The method as recited in claim 14, wherein determining a transitional state of the subject based upon the probability distribution comprises determining an activity level associated with the subject.

17. The method as recited in claim 14, wherein determining a transitional state of the subject based upon the probability distribution comprises determining a transitional state of the subject within the bed based upon the probability distribution.

18. The method as recited in claim 14, further comprising identifying one or more third pixels of the plurality of pixels as representing at least one of a second subject or an object relative to the subject.

19. The method as recited in claim 14, further comprising tracking the one or more second pixels through the plurality of depth frame images;

determining whether the one or more second pixels corresponds to a gesture; and

causing issuance of an electronic communication indicating a gesture has been performed upon determination that the tracked one or more second pixels corresponds to the gesture.