IP Library › Granted Patent US 12,279,994
Granted Patent B2
US 12,279,994 · App. 18/943,055 · Granted Apr 22, 2025

Relocation module and methods for surgical equipment

Inventors: Scott D. Augustine (Deephaven, MN); Susan D. Augustine (Deephaven, MN); Garrett J. Augustine (Deephaven, MN); Brent M. Augustine (Savage, MN); Ryan S. Augustine (Minneapolis, MN); Randall C. Arnold (Minnetonka, MN)
Assignee: Augustine Biomedical + Design, LLC
A61G13/108A61B50/13A61B50/15A61M16/06A61M16/18G06T7/70G06V10/00G16H10/60G16H20/40G16H30/20A61B46/10A61B2050/155A61B90/50A61M16/01B01D46/0093G06F16/10G06F16/48G06T2207/20081G06T2207/30004G06T2210/41G16H20/17G16H30/40
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Quick Facts
Patent No.
US 12,279,994
App. No.
18/943,055
Filed
Nov 11, 2024
Granted
Apr 22, 2025
Kind
B2
Art Unit
2666
USPC
382/128
Abstract

Module for housing electronic and electromechanical medical equipment including a portable digital camera and processing circuitry with machine vision and machine learning software for automatically documenting healthcare events and healthcare equipment operations in the electronic health record.

Claims (63)

1. An automated data consolidation module including a system to receive and record data produced by medical equipment, the automated data consolidation module comprising:

a module;

at least one digital camera configured to produce digital data; and

processing circuitry in wired or wireless electrical communication with the at least one digital camera to receive the digital data, wherein the digital data is automatically delivered to the processing circuitry and software, and wherein the processing circuitry and software is configured to interpret the digital data by performing at least one of machine learning (ML) and artificial intelligence (AI) analysis to:

identify specific visual elements of an image of the digital data by matching a subject image of the digital data to known images stored in an image library, to create matched identified specific visual elements of the image that show an operating parameter of a medical item or device performing a dose event or the specific visual elements of an image that show a measurement of a response event;

add time stamps or other indicators of time to the identified specific visual elements so that the digital data can be temporally correlated during subsequent big data or clinical decision support analysis; and

automatically save information provided by the matched identified specific visual elements of the image or the image itself to an electronic record or database;

wherein the at least one digital camera, processing circuitry and software are configured to photograph, analyze, and record an identifier including at least one of a quick response (QR) code, a barcode, or other identifier that is attached to a medical item or device, and wherein the QR code, barcode, or other identifier identifies at least one of a type of item or device, a manufacturer of the item or device, a model of the item or device, and a content of the item or device, narrowing the ML or AI analysis by directing the ML or AI analysis to a folder containing images of a specific type, manufacturer, model, or content of the item or device associated with the identifier.

2. The automated data consolidation module of claim 1 , wherein the QR code, barcode, or other identifier is attached to a subject medical item or device in a prescribed location on the medical item or device relative to the specific visual elements to be identified and the prescribed location of the QR code, barcode, or other identifier becomes a target for a laser pointer to standardize a scene and to orient the at least one digital camera to match similarly structured scenes and camera orientations of the known images stored in an image library.

3. The automated data consolidation module of claim 1 , wherein the QR code, barcode, or other identifier identifies an area or areas of interest within a scene so that the ML or AI analysis can focus on the area or areas of interest on the medical item or device that show desired information.

4. The automated data consolidation module of claim 1 , wherein the at least one digital camera, processing circuitry, and software includes machine vision capabilities for one or more of:

pill identification, pill counting, or observation of and verification of a patient taking pills.

5. The automated data consolidation module of claim 1 , wherein the medical item or device performing a dose event is a syringe and the quick response (QR) code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the syringe.

6. The automated data consolidation module of claim 1 , wherein the medical item or device performing a dose event is a IV bag and drip set and the quick response (QR) code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the IV bag and drip set.

7. The automated data consolidation module of claim 1 , wherein the medical item or device performing a dose event is a drug infusion pump and the quick response (QR) code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the drug infusion pump.

8. The automated data consolidation module of claim 1 , wherein the medical item or device performing a dose event is an anesthetic vaporizer and the quick response (QR) code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the anesthetic vaporizer.

9. The automated data consolidation module of claim 1 , wherein the medical item or device performing a dose event is a gas supply and the quick response (QR) code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the gas supply.

10. The automated data consolidation module of claim 1 , wherein the identified specific visual elements of the image constitute dose events or response events and the processing circuitry is configured to add time stamps or other indicators of time so that unrelated data can be temporally correlated during subsequent “big data” analysis.

11. The automated data consolidation module of claim 1 , wherein the processing circuitry includes artificial intelligence or machine learning algorithms that compare the response event to the dose event and provide immediate feedback via a display or alert device.

12. The automated data consolidation module of claim 1 , wherein the electronic record or database is configured to be accessed by artificial intelligence or machine learning algorithms to retrieve one or more temporally correlated dose-response event and compare the one or more temporally correlated dose-response event to other temporally correlated dose-response events across a population of patients and output big data correlation insights to at least one storage device or display.

13. The automated data consolidation module of claim 1 , wherein the processing circuitry and software can temporally correlate the dose event and the response event and artificial intelligence (AI) analytics can identify expected and unexpected physiologic responses to a given dose event.

14. An automated data consolidation module including a digital camera comprising:

a module;

at least one digital camera; and

processing circuitry in wired or wireless electrical communication with the at least one digital camera to receive and record digital data produced by the at least one digital camera, wherein the at least one digital camera and the processing circuitry and software are configured to photograph, analyze, and record an identifier including at least one of a QR code, a barcode or other identifier that is attached to a medical item or device, the QR code, barcode, or other identifier identifying at least one of a type of the medical item or device, a manufacturer of the medical item or device, a model of the medical item or device, and a content of a medical item or device;

wherein the digital data from the at least one digital camera includes an image of the medical item or device that is automatically delivered to the processing circuitry and software, and wherein the processing circuitry and software are configured to perform at least one of machine learning (ML) and artificial intelligence (AI) analysis to:

identify specific visual elements of the image by matching the image to known images stored in an image library to form matched specific visual elements of the image that show an operating parameter of a medical item or device performing a dose event or the specific visual elements of an image that show a measurement of a response event; and

automatically save information provided by the matched specific visual elements of the image or the image itself to an electronic record or database; and

wherein the QR code, barcode, or other identifier that is attached to the medical item or device narrows the ML and AI image analysis by directing a search of the ML or AI analysis to a folder containing images of the type, manufacturer, model, or content of the medical item or device.

15. The automated data consolidation module of claim 14 , wherein the QR code, barcode, or other identifier is attached to a subject medical item or device in a prescribed location on the medical item or device relative to the specific visual elements to be identified and the prescribed location of the QR code, barcode, or other identifier becomes a target for a laser pointer to standardize a scene and to orient the at least one digital camera to match similarly structured scenes and camera orientations of the known images stored in an image library.

16. The automated data consolidation module of claim 14 , wherein the QR code, barcode, or other identifier identifies an area or areas of interest within a scene so that the ML or AI analysis can focus on the area or areas of interest on the medical item or device that show desired information.

17. The automated data consolidation module of claim 14 , wherein the at least one digital camera, processing circuitry, and software includes machine vision capabilities for one or more of:

pill identification, pill counting, or observation of and verification of a patient taking pills.

18. The automated data consolidation module of claim 14 , wherein the medical item or device performing a dose event is a syringe and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the syringe.

19. The automated data consolidation module of claim 14 , wherein the medical item or device performing a dose event is a IV bag and drip set and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the IV bag and drip set.

20. The automated data consolidation module of claim 14 , wherein the medical item or device performing a dose event is a drug infusion pump and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the drug infusion pump.

21. The automated data consolidation module of claim 14 , wherein the medical item or device performing a dose event is a anesthetic vaporizer and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the anesthetic vaporizer.

22. The automated data consolidation module of claim 14 , wherein the medical item or device performing a dose event is a gas supply and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the gas supply.

23. The automated data consolidation module of claim 14 , wherein the identified specific visual elements of the image constitute the dose events or the response event and the processing circuitry is configured to add time stamps or other indicators of time so that unrelated data can be temporally correlated during subsequent “big data” analysis.

24. The automated data consolidation module of claim 14 , wherein the processing circuitry includes artificial intelligence or machine learning algorithms that compare the response event to the dose event and provide immediate feedback via a display or alert device.

25. The automated data consolidation module of claim 14 , wherein the electronic record or database is configured to be accessed by artificial intelligence or machine learning algorithms to retrieve one or more temporally correlated dose-response event and compare the one or more temporally correlated dose-response events to other temporally correlated dose-response events across a population of patients and output big data correlation insights to at least one storage device or display.

26. The automated data consolidation module of claim 14 , wherein the processing circuitry and software can temporally correlate the dose event and the response event and artificial intelligence (AI) analytics can identify expected and unexpected physiologic responses to a given dose event.

27. An automated data consolidation module including a digital camera comprising:

a module;

at least one digital camera; and

processing circuitry in wired or wireless electrical communication with the at least one digital camera to receive and record digital data produced by the at least one digital camera, wherein the at least one digital camera and the processing circuitry and software are configured to photograph, analyze, and record an identifier including at least one of a QR code, a barcode or other identifier that is attached to a medical item or device, the QR code, barcode, or other identifier identifying at least one of a type of the medical item or device, a manufacturer of the medical item or device, a model of the medical item or device, and a content of a medical item or device;

wherein the digital data from the at least one digital camera includes an image of the medical item or device that is automatically delivered to the processing circuitry and software, and wherein the processing circuitry and software are configured to perform at least one of machine learning (ML) and artificial intelligence (AI) analysis to:

identify specific visual elements of the image by matching the image to known images stored in an image library to form matched specific visual elements of the image that show an operating parameter of a medical item or device performing one or more dose event or the specific visual elements of an image that show a measurement of one or more response event; and

automatically save information provided by the matched specific visual elements of the image or the image itself to an electronic record or database;

wherein the QR code, barcode, or other identifier that is attached to the medical item or device narrows the ML and AI image analysis by directing a search of the analysis to a folder containing images of the type, manufacturer, model, or content of the medical item or device; and

wherein the QR code, barcode, or other identifier is attached to a subject medical item or device in a prescribed location on the medical item or device relative to the specific visual elements to be identified and the prescribed location of the QR code, barcode, or other identifier becomes a target for a laser pointer to standardize a scene and to orient the at least one digital camera to match similarly structured scenes and camera orientations of the known images stored in an image library.

28. The automated data consolidation module of claim 27 , wherein the QR code, barcode, or other identifier identifies an area or areas of interest within a scene so that the ML or AI analysis can focus on the area or areas of interest on the medical item or device that show desired information.

29. The automated data consolidation module of claim 27 , wherein the at least one digital camera, processing circuitry, and software includes machine vision capabilities for one or more of:

pill identification, pill counting, or observation of and verification of a patient taking pills.

30. The automated data consolidation module of claim 27 , wherein the medical item or device performing the one or more dose event is a syringe and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the syringe.

31. The automated data consolidation module of claim 27 , wherein the medical item or device performing the one or more dose event is a IV bag and drip set and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the IV bag and drip set.

32. The automated data consolidation module of claim 27 , wherein the medical item or device performing the one or more dose event is a drug infusion pump and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the drug infusion pump.

33. The automated data consolidation module of claim 27 , wherein the medical item or device performing the one or more dose event is a anesthetic vaporizer and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the anesthetic vaporizer.

34. The automated data consolidation module of claim 27 , wherein the medical item or device performing the one or more dose event is a gas supply and the QR code, barcode, or other identifier that is attached to the medical item or device identifies at least a content of the gas supply.

35. The automated data consolidation module of claim 27 , wherein the identified specific visual elements of the image constitute the one or more dose event or the one or more response event and the processing circuitry is configured to add time stamps or other indicators of time so that unrelated data can be temporally correlated during subsequent “big data” analysis.

36. The automated data consolidation module of claim 27 , wherein the processing circuitry includes artificial intelligence or machine learning algorithms that compare the one or more response event to the one or more dose event and provide immediate feedback via a display or alert device.

37. The automated data consolidation module of claim 27 , wherein the electronic record or database is configured to be accessed by artificial intelligence or machine learning algorithms to retrieve one or more temporally correlated dose-response event and compare the one or more temporally correlated dose-response event to other temporally correlated dose-response events across a population of patients and output big data correlation insights to at least one storage device or display.

38. The automated data consolidation module of claim 27 , wherein the processing circuitry and software can temporally correlate the one or more dose event and the one or more response event and artificial intelligence (AI) analytics can identify expected and unexpected physiologic responses to a given dose event.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 11, 2024
From: AUGUSTINE, SCOTT D.; AUGUSTINE, SUSAN D.; AUGUSTINE, GARRETT J.; AUGUSTINE, BRENT M.; AUGUSTINE, RYAN S.; ARNOLD, RANDALL C.
To: AUGUSTINE BIOMEDICAL + DESIGN, LLC
Reel/Frame 069201/0933 →
Continuity (20)
Continuation 18598110 · Mar 7, 2024
Continuation 18142787 · May 3, 2023
Continuation 18099074 · Jan 19, 2023
Continuation 17874963 · Jul 27, 2022
Continuation 17873857 · Jul 26, 2022
Continuation 17528832 · Nov 17, 2021
Continuation In Part 17376469 · Jul 15, 2021
Continuation In Part 17245942 · Apr 30, 2021
Continuation In Part 17245942 · Apr 30, 2021
Continuation In Part 17199722 · Mar 12, 2021
Continuation In Part 17167681 · Feb 4, 2021
Continuation 17092681 · Nov 9, 2020
Continuation In Part 17092681 · Nov 9, 2020
Continuation 16879406 · May 20, 2020
Continuation In Part 16601924 · Oct 15, 2019
Continuation 16593033 · Oct 4, 2019
Continuation 16364884 · Mar 26, 2019
Continuation In Part 15935524 · Mar 26, 2018
Provisional Application 62782901 · Dec 20, 2018
Related Publication 20250064660A1 · Feb 27, 2025
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“U.S. Appl. No. 17/862,971, Response filed Dec. 5, 2022 to Non Final Office Action mailed Nov. 15, 2022”, 11 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,857, Corrected Notice of Allowability mailed Apr. 13, 2023”, 2 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,857, Non Final Office Action mailed Nov. 14, 2022”, 7 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,857, Notice of Allowance mailed Dec. 21, 2022”, 9 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,857, Response filed Dec. 5, 2022 to Non Final Office Action mailed Nov. 14, 2022”, 13 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,857, Supplemental Notice of Allowability mailed Mar. 14, 2023”, 5 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,907, Final Office Action mailed Dec. 13, 2022”, 7 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,907, Non Final Office Action mailed Nov. 14, 2022”, 7 pgs. [cited by applicant]
“U.S. Appl. No. 17/873,907, Notice of Allowance mailed Jan. 25, 2023”, 9 pgs. [cited by applicant]
Cited By (2)
US 12,508,183 US 12,697,266