Automated clinical documentation system and method

• US 10,809,970 B2
• Filed: 02/08/2019
• Issued: 10/20/2020
• Est. Priority Date: 03/05/2018
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Inventors: Almendro Barreda, Daniel Paulino, Sharma, Dushyant, Pinto, Joel Praveen, Jost, Uwe Helmut, Naylor, Patrick A.
• Primary Examiner(s): Holder, Regina N
• Application Number:
  US16/271,616
• Publication Number:
  US 20190272905A1
• Time in Patent Office: 620 Days
• CPC Class Codes: G06F 3/165 Management of the audio stream, e.g. setting of volume, audio stream path
• CPC Class Codes: G06F 40/117 Tagging; Marking up details of markup languages G06F40/143; Designating a block; Setting of attributes style sheets, e.g. eXtensible Stylesheet Language Transformation [XSLT], G06F40/154
• CPC Class Codes: G06F 40/151 Transformation
• CPC Class Codes: G06F 40/279 Recognition of textual entities
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/22 Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 15/30 Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
• CPC Class Codes: G10L 25/45 characterised by the type of analysis window
• CPC Class Codes: G10L 25/51 for comparison or discrimination
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 80/00 : ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• CPC Class Codes: H04R 1/406 : microphones
• CPC Class Codes: H04R 3/005 : for combining the signals of two or more microphones specially adapted for hearing aids H04R25/407

Abstract

A method, computer program product, and computing system for obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information; processing the machine vision encounter information to identify one or more humanoid shapes; and steering one or more audio recording beams toward the one or more humanoid shapes to capture audio encounter information.

Claims

1. A computer-implemented method, executed on a computing device, comprising:

obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information;

processing the machine vision encounter information to identify one or more humanoid shapes and monitoring trajectories of the one or more humanoid shapes; and

steering one or more audio recording beams toward the one or more humanoid shapes to capture audio encounter information.

2. The computer-implemented method of claim 1 wherein obtaining the encounter information of the patient encounter includes one or more of:

obtaining the encounter information from a medical professional;

obtaining the encounter information from a patient; and

obtaining the encounter information obtaining encounter information from a third party.

3. The computer-implemented method of claim 1 wherein the encounter information further includes audio encounter information.

4. The computer-implemented method of claim 1 wherein processing the machine vision encounter information to identify the one or more humanoid shapes includes:

tracking the movement of the one or more humanoid shapes within a monitored space.

5. The computer-implemented method of claim 4 wherein the one or more humanoid shapes are defined with one or more humanoid models.

6. The computer-implemented method of claim 4 wherein tracking the movement of the one or more humanoid shapes within the monitored space includes:

adding a new humanoid shape to the one or more humanoid shapes when the new humanoid shape enters the monitored space.

7. The computer-implemented method of claim 4 wherein tracking the movement of the one or more humanoid shapes within the monitored space includes:

removing an existing humanoid shape from the one or more humanoid shapes when the existing humanoid shape leaves the monitored space.

8. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information;

processing the machine vision encounter information to identify one or more humanoid shapes and monitoring trajectories of the one or more humanoid shapes; and

steering one or more audio recording beams toward the one or more humanoid shapes to capture audio encounter information.

9. The computer program product of claim 8 wherein obtaining the encounter information of the patient encounter includes one or more of:

obtaining the encounter information from a medical professional;

obtaining the encounter information from a patient; and

obtaining the encounter information obtaining encounter information from a third party.

10. The computer program product of claim 8 wherein the encounter information further includes audio encounter information.

11. The computer program product of claim 8 wherein processing the machine vision encounter information to identify the one or more humanoid shapes includes:

tracking the movement of the one or more humanoid shapes within a monitored space.

12. The computer program product of claim 11 wherein the one or more humanoid shapes are defined with one or more humanoid models.

13. The computer program product of claim 11 wherein tracking the movement of the one or more humanoid shapes within the monitored space includes:

adding a new humanoid shape to the one or more humanoid shapes when the new humanoid shape enters the monitored space.

14. The computer program product of claim 11 wherein tracking the movement of the one or more humanoid shapes within the monitored space includes:

removing an existing humanoid shape from the one or more humanoid shapes when the existing humanoid shape leaves the monitored space.

15. A computing system including a processor and memory configured to perform operations comprising:

obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information;

processing the machine vision encounter information to identify one or more humanoid shapes and monitoring trajectories of the one or more humanoid shapes; and

steering one or more audio recording beams toward the one or more humanoid shapes to capture audio encounter information.

16. The computing system of claim 15 wherein obtaining the encounter information of the patient encounter includes one or more of:

obtaining the encounter information from a medical professional;

obtaining the encounter information from a patient; and

obtaining the encounter information obtaining encounter information from a third party.

17. The computing system of claim 15 wherein the encounter information further includes audio encounter information.

18. The computing system of claim 15 wherein processing the machine vision encounter information to identify the one or more humanoid shapes includes:

tracking the movement of the one or more humanoid shapes within a monitored space.

19. The computing system of claim 18 wherein the one or more humanoid shapes are defined with one or more humanoid models.

20. The computing system of claim 18 wherein tracking the movement of the one or more humanoid shapes within the monitored space includes:

adding a new humanoid shape to the one or more humanoid shapes when the new humanoid shape enters the monitored space.

21. The computing system of claim 18 wherein tracking the movement of the one or more humanoid shapes within the monitored space includes:

removing an existing humanoid shape from the one or more humanoid shapes when the existing humanoid shape leaves the monitored space.