Medical environment event parsing system

• US 10,475,206 B1
• Filed: 01/04/2018
• Issued: 11/12/2019
• Est. Priority Date: 01/04/2017
• Status: Active Grant

• Current Assignee: Ocuvera Co.
• Original Assignee: Ocuvera Co.
• Inventors: Rush, Benjamin D., Brown-Kramer, Joshua M., Sabalka, Lucas A., Gansemer, Brian S., Upton, Clay T., Bauer, Paul B., Unterseher, Andrew R., Origas, Benjamin J., Durham, Douglas W.
• Primary Examiner(s): Couso, Jose L
• Application Number:
  US15/862,239
• Time in Patent Office: 677 Days
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/254 involving subtraction of images
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/44 Event detection
• 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: G08B 21/02 Alarms for ensuring the safety of persons
• CPC Class Codes: G08B 21/0476 Cameras to detect unsafe condition, e.g. video cameras

Abstract

A system and a method are described for identifying (e.g., parsing images) images pertaining to an event. The method also includes identifying a first subset of pixels from the plurality of potential locations as representing a bed and/or a seating platform. The method also includes identifying a second subset of pixels within the field of view of the camera as representing an object proximal to the bed and/or seating platform. The method also includes determining an orientation of the object with respect to the bed and/or seating platform, and determining changes in the orientation and/or position of the object over a period of time. In implementations, the method further includes generating state data pertaining to an event and associating the state data with corresponding image frame data.

Claims

1. A 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;

a computing device in communication with the imaging device, the computing device including;

a memory configured to store a patient monitoring module;

a processor coupled to the memory, the processor configured by the patient monitoring module to cause the processor to;

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

identify a first set of pixels of the plurality of pixels as representing at least one of a bed or a seating platform;

identify a second set of 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 seating platform;

process, via a first processing technique, the second set of pixels to generate a first possible orientation of the portion of the body with respect to the imaging plane, the first possible orientation representing a position of the portion of the body with respect to the at least one of the bed or the seating platform;

process, via a second processing technique, the second set of pixels to generate a second possible orientation of the portion of the body with respect to the imaging plane, the second possible orientation representing the position of the portion of the body with respect to the at least one of the bed or the seating platform;

determine whether the subject has changed positions based upon the first possible orientation and the second possible orientation;

generate state data representing an event associated with the determination of whether the subject has changed positions; and

associate the state data with corresponding depth frame images of the plurality of depth frame images.

2. The system as recited in claim 1, wherein the processor is configured by the patient monitoring module to cause the processor to receive a query comprising state characteristics;

identify at least one depth frame image based upon the state data and the state characteristics; and

retrieve the at least one depth frame image in response to the query.

3. The system as recited in claim 1, wherein the processor is further configured by the patient monitoring module to cause the processor to identify at least one of a plurality of potential bed locations or a plurality of potential seating platform locations.

4. The system as recited in claim 3, wherein the processor is further configured by the patient monitoring module to cause the processor to model the first set of pixels based upon a gradient ascent of the first set of pixels;

and select the at least one of the plurality of potential bed locations or the plurality of potential seating platform locations based upon the gradient ascent.

5. The system as recited in claim 1, wherein the processor is further configured by the patient monitoring module to cause the processor to receive feedback corresponding to a validity of an electronic communication alert.

6. The system as recited in claim 1, wherein the processor is further configured by the patient monitoring module to cause the processor to determine a probability distribution based upon the first possible orientation, the second possible orientation, and at least one characteristic of the subject.

7. The system as recited in claim 1, wherein the processor is further configured by the patient monitoring module to cause the processor to determine an electronic communication alert sensitivity level associated with the subject based upon at least one characteristic of the subject.

8. The system as recited in claim 1, further comprising one or more sensors configured to detect a pressure associated with the portion of the body.

9. A method comprising:

receiving, at a processor, a plurality of depth frame images comprising a plurality of pixels captured by an imaging device having an imaging plane, the plurality of depth frame images representing a three-dimensional environment corresponding to a physical space;

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

identifying a first set of pixels of the plurality of pixels as representing at least one of a bed or a seating platform;

identifying a second set of 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 seating platform;

processing, via a first processing technique, the second set of pixels to generate a first possible orientation of the portion of the body with respect to the imaging plane, the first possible orientation representing a position of the portion of the body with respect to the at least one of the bed or the seating platform;

processing, via a second processing technique, the second set of pixels to generate a second possible orientation of the portion of the body with respect to the imaging plane, the second possible orientation representing the position of the portion of the body with respect to the at least one of the bed or the seating platform;

determining whether the subject has changed positions based upon the first possible orientation and the second possible orientation;

generating state data representing an event associated with the determination of whether the subject has changed positions; and

associating the state data with corresponding depth frame images of the plurality of depth frame images.

10. The method as recited in claim 9, further comprising receiving a query comprising state characteristics;

identifying at least one depth frame image based upon the state data and the state characteristics; and

retrieving the at least one depth frame image in response to the query.

11. The method as recited in claim 9, further comprising identifying at least one of a plurality of potential bed locations or a plurality of potential seating platform locations.

12. The method as recited in claim 11, further comprising modeling the first set of pixels based upon a gradient ascent of the first set of pixels;

and selecting the at least one of the plurality of potential bed locations or the plurality of potential seating platform locations based upon the gradient ascent of the set of pixels.

13. The method as recited in claim 9, further comprising receiving feedback corresponding to a validity of an electronic communication alert.

14. The method as recited in claim 9, further comprising determining a probability distribution based upon the first possible orientation, the second possible orientation, and at least one characteristic of the subject.

15. The method as recited in claim 9, further comprising determining an electronic communication alert sensitivity level associated with the subject based upon at least one characteristic of the subject.

16. A method comprising:

receiving, at a processor, a plurality of depth frame images comprising a plurality of pixels captured by an imaging device having an imaging plane, the plurality of depth frame images representing a three-dimensional environment corresponding to a physical space;

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

identifying a first set of pixels of the plurality of pixels as representing at least one of a bed or a seating platform;

identifying a second set of 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 seating platform;

processing, via a first processing technique, the second set of pixels to generate a first possible orientation of the portion of the body with respect to the imaging plane, the first possible orientation representing a position of the portion of the body with respect to the at least one of the bed or the seating platform;

processing, via a second processing technique, the second set of pixels to generate a second possible orientation of the portion of the body with respect to the imaging plane, the second possible orientation representing the position of the portion of the body with respect to the at least one of the bed or the seating platform;

determining whether the subject has changed positions based upon the first possible orientation and the second possible orientation;

generating state data representing an event associated with the determination of whether the subject has changed positions;

associating the state data with corresponding depth frame images of the plurality of depth frame images;

receiving a query comprising state characteristics;

identifying at least one depth frame image based upon the state data and the state characteristics; and

retrieving the at least one depth frame image in response to the query.

17. The method as recited in claim 16, further comprising identifying at least one of a plurality of potential bed locations or a plurality of potential seating platform locations.

18. The method as recited in claim 17, further comprising modeling the first set of pixels based upon a gradient ascent of the first set of pixels;

and selecting the at least one of the plurality of potential bed locations or the plurality of potential seating platform locations based upon the gradient ascent of the set of pixels.

19. The method as recited in claim 16, further comprising receiving feedback corresponding to a validity of an electronic communication alert.

20. The method as recited in claim 16, further comprising determining a probability distribution based upon the first possible orientation, the second possible orientation, and at least one characteristic of the subject.