Relocation module and methods for surgical equipment

Patent metadata

Field	Value
Publication number	US-12178759-B2
Application number	US-202418598110-A
Country	US
Kind code	B2
Filing date	Mar 7, 2024
Priority date	Mar 26, 2018
Publication date	Dec 31, 2024
Grant date	Dec 31, 2024

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.

First claim

What is claimed is:

1. An automated data consolidation module including a system to receive and record data produced by electronic and electromechanical medical equipment, the automated data consolidation module comprising:
a module;
at least one handheld digital camera configured to produce digital data; and
processing circuitry in wired or wireless electrical communication with the at least one handheld 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 handheld digital camera, processing circuitry and software are configured to photograph, analyze, and record at least one of a quick response (QR) code, a barcode, or other identifier that is attached to the 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, and a model 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, or model of the item or device associated with the identifier.

2. The automated data consolidation module of claim 1 , wherein the at least one handheld digital camera includes a pistol grip that is user graspable to aim the at least one handheld digital camera at a subject item or device.

3. The automated data consolidation module of claim 1 , wherein the at least one handheld digital camera includes a laser pointer to assist in aiming the at least one handheld digital camera at a subject item or device.

4. The automated data consolidation module of claim 1 , wherein the at least one handheld digital camera includes a liquid crystal display (LCD) projector, a laser projector, or a cluster of lasers configured to project an indicator image onto the medical item or device after an image of the medical item or device is successfully acquired by the at least one handheld digital camera.

5. The automated data consolidation module of claim 1 , wherein the QR code, barcode, or other identifier is attached to the 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 handheld digital camera to match similarly structured scenes and camera orientations of the known images stored in an image library.

6. 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.

7. The automated data consolidation module of claim 1 , wherein the at least one handheld 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.

8. An automated data consolidation module including a handheld digital camera comprising:
a module;
at least one handheld digital camera; and
processing circuitry in wired or wireless electrical communication with the at least one handheld digital camera to receive and record digital data produced by the at least one handheld digital camera, wherein the at least one handheld digital camera and the processing circuitry and software are configured to photograph, analyze, and record 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, and a model of the medical item or device;
wherein the digital data from the at least one handheld 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 the 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 analysis to a folder containing images of the type, manufacturer, or model of the medical item or device.

9. The automated data consolidation module of claim 8 , wherein the at least one handheld digital camera includes a pistol grip that is user graspable to aim the at least one handheld digital camera at a subject item or device.

10. The automated data consolidation module of claim 8 , wherein the at least one handheld digital camera includes a laser pointer to assist in aiming the at least one handheld digital camera at a subject item or device.

11. The automated data consolidation module of claim 8 , wherein the at least one handheld digital camera includes a liquid crystal display (LCD) projector, a laser projector, or a cluster of lasers configured to project an acquisition image onto an item or device after an image of the item or device is successfully acquired by the at least one handheld digital camera.

12. The automated data consolidation module of claim 8 , wherein the QR code, the barcode, or the other identifier is connected to the medical item or device in a prescribed location on the medical item or device relative to the specific visual elements to be identified and wherein the prescribed location of the QR code, the barcode, or the other identifier becomes a target for a laser pointer so that a scene is standardized and the at least one handheld digital camera is oriented to match similarly structured scenes and camera orientations of the known images stored in the image library.

13. The automated data consolidation module of claim 8 , wherein the QR code, the barcode, or the other identifier is configured to identifies an area or areas of interest within a scene so that the ML or AI analysis can focus on the area or areas o

Assignees

• Augustine Biomedical Design Llc

Inventors

• Augustine Scott D
• Augustine Susan D
• Augustine Garrett J
• Augustine Brent M
• Augustine Ryan S
• Arnold Randall C

Classifications

• G06T2210/41

  Medical · CPC title

• G06T2207/30004

  Biomedical image processing · CPC title

• G06F16/48

  Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually · CPC title

• G06F16/10

  File systems; File servers · CPC title

• G06V10/00

  Arrangements for image or video recognition or understanding (character recognition in images or video G06V30/10) · CPC title