IP Library › Granted Patent US 11,497,417
Granted Patent B2
US 11,497,417 · App. 16/339,152 · Granted Nov 15, 2022

Measuring patient mobility in the ICU using a novel non-invasive sensor

Inventors: Suchi Saria (New York, NY); Andy Jinhua Ma (Baltimore, MD); Austin Reiter (Severna Park, MD)
Assignee: The Johns Hopkins University
A61B5/1128A61B5/1115A61B5/1116A61B5/1118A61B5/1171G06T7/0012G06T7/215G06V40/103G06V40/25G08B21/04G08B21/043G08B21/0415G08B21/0476G16H30/20G16H30/40G16H40/63
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Quick Facts
Patent No.
US 11,497,417
App. No.
16/339,152
Granted
Nov 15, 2022
Kind
B2
Abstract

An embodiment in accordance with the present invention includes a technology to continuously measure patient mobility automatically, using sensors that capture color and depth images along with algorithms that process the data and analyze the activities of the patients and providers to assess the highest level of mobility of the patient. An algorithm according to the present invention employs the following five steps: 1) analyze individual images to locate the regions containing every person in the scene (Person Localization), 2) for each person region, assign an identity to distinguish ‘patient’ vs. ‘not patient’ (Patient Identification), 3) determine the pose of the patient, with the help of contextual information (Patient Pose Classification and Context Detection), 4) measure the degree of motion of the patient (Motion Analysis), and 5) infer the highest mobility level of the patient using the combination of pose and motion characteristics (Mobility Classification).

Claims (32)

1. A method of measuring patient mobility comprising:

analyzing individual images from an RGB-D sensor to locate a region containing each person including a patient;

assigning an identity for each person in the region, to distinguish ‘patient’ vs. ‘not patient’;

determining a pose of the patient, with contextual information;

measuring a degree of motion of the patient; and

inferring a highest mobility level of the patient using the combination of pose and motion characteristics.

2. The method of claim 1 further comprising generating a volumetric representation of patient mobility.

3. The method of claim 1 further comprising generating a heatmap of patient mobility.

4. The method of claim 1 further comprising generating a heatmap of movement of regions of the patient's body.

5. The method of claim 1 further comprising classifying the pose of the patient into 4 discrete categories: (1) lying in bed, (2) sitting in bed, (3) sitting in chair, and (4) standing.

6. The method of claim 1 further comprising classifying patient motion as “in-bed activity” if a total body speed signature of the patient exceeds a threshold.

7. The method of claim 1 further comprising classifying patient motion as “nothing in bed” if a total body speed signature of the patient is below a threshold.

8. The method of claim 1 further comprising executing the method with a non-transitory computer readable medium.

9. The method of claim 1 further comprising defining a predetermined area for measuring patient mobility.

10. The method of claim 9 further comprising defining the predetermined area for measuring patient mobility as the patient room.

11. A system for measuring patient mobility comprising:

an RGB-D sensor;

a non-transitory computer readable medium programmed for:

analyzing individual images from the RGB-D sensor to locate a region containing each person, including the patient;

assigning an identity for each person in the region, to distinguish ‘patient’ vs. ‘not patient’;

determining a pose of the patient, with contextual information;

measuring a degree of motion of the patient; and

inferring the highest mobility level of the patient using the combination of pose and motion characteristics.

12. The system of claim 11 further comprising generating a volumetric representation of patient movement.

13. The system of claim 11 further comprising generating a heatmap of patient movement.

14. The system of claim 11 further comprising generating a heatmap of movement of regions of the patient's body.

15. The system of claim 11 further comprising classifying the pose of the patient into 4 discrete categories: (1) lying in bed, (2) sitting in bed, (3) sitting in chair, and (4) standing.

16. The system of claim 11 further comprising classifying patient motion as “in-bed activity” if a total body speed signature of the patient exceeds a threshold.

17. The system of claim 11 further comprising classifying patient motion as “nothing in bed” if a total body speed signature of the patient is below a threshold.

18. The system of claim 11 further comprising assigning a numerical mobility value to the patient mobility.

19. The system of claim 11 further comprising defining a predetermined area for measuring patient mobility.

20. The system of claim 19 further comprising defining the predetermined area for measuring patient mobility as the patient room.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 11, 2022
From: SARIA, SUCHI; MA, ANDY JINHUA; REITER, AUSTIN
To: THE JOHNS HOPKINS UNIVERSITY
Reel/Frame 061380/0526 →
Continuity (2)
Provisional Application 62403890 · Oct 4, 2016
Related Publication 20190231231A1 · Aug 1, 2019