DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Li et al. (US 2023/0409749).
In regard to claim 1, Li disclosed a computer-implemented method for de-identifying data captured in medical facility rooms, the method comprising:
receiving, at one or more edge devices operating within a security boundary of a medical facility, a set of streams of sensor data captured in a set of medical facility rooms in the medical facility; Li [0061]-[0063]
for each stream of the set of streams of sensor data,
generating, at the one or more edge devices, a de-identified data stream at least based on redacting from the stream information that identifies one or more persons, and Li [0063]
generating, at the one or more edge devices, identity-neutral metadata associated with the de-identified data stream at least based on extracting from the stream information that describes the identified persons in a manner that does not reveal the identity of the identified persons; and Li [0254]
transmitting the de-identified data streams and the associated identity-neutral metadata for further processing outside of the security boundary of the medical facility. Li [0061]
In regard to claim 2, Li disclosed the computer-implemented method of claim 1, wherein each stream of the set of streams of sensor data is captured using one of the following sensors: a visual sensor, an audio sensor, a temperature sensor, a humidity sensor, a vibration sensor, or an ambient light sensor. Li [0062]
In regard to claim 3, Li disclosed the computer-implemented method of claim 1, wherein a stream of the set of streams of sensor data comprises a video stream captured by a visual sensor in a medical facility room of the set of operation rooms, and wherein generating a de-identified data stream is further based on redacting from the stream sensitive information related to a human body. Li [0065]
In regard to claim 4, Li disclosed the computer-implemented method of claim 1, wherein a stream of the set of streams of sensor data comprises a video stream captured by a visual sensor in a medical facility room of the set of operation rooms, and wherein redacting from the stream information that identifies one or more persons comprises redacting images of the identified persons. Li [0069]
In regard to claim 5, Li disclosed the computer-implemented method of claim 1, wherein a stream of the set of streams of sensor data comprises an audio stream captured by an audio sensor in a medical facility room of the set of operation rooms, and wherein redacting from the stream information that identifies one or more persons comprises redacting personal identifying information (PII) information from identified text in the stream. Li [0097]
In regard to claim 6, Li disclosed the computer-implemented method of claim 1, wherein a stream of the set of streams of sensor data comprises a video stream captured by a visual sensor in a medical facility room of the set of operation rooms, and wherein extracting from the stream information that describes the identified persons in a manner that does not reveal the identity of the identified persons comprises detecting events related to the identified persons in one or more video frames of the stream. Li [0069]
In regard to claim 7, Li disclosed the computer-implemented method of claim 1, wherein a stream of the set of streams of sensor data comprises a video stream captured by a visual sensor in a medical facility room of the set of operation rooms, and wherein extracting from the stream information that describes the identified persons in a manner that does not reveal the identity of the identified persons comprises extracting a skeleton body structure for each of the identified persons in each video frame of the stream. Li [0153]-[0155]
In regard to claim 8, Li disclosed the computer-implemented method of claim 1, wherein a stream of the set of streams of sensor data comprises an audio stream captured by an audio sensor in a medical facility room of the set of operation rooms, and wherein extracting from the stream information that describes the identified persons in a manner that does not reveal the identity of the identified persons comprises extracting from the stream non-person specific voiceprints. Li [0097]
In regard to claim 9, Li disclosed the computer-implemented method of claim 1, the method further comprising: for each stream of the set of streams of sensor data, generating identity-specific metadata based on extracting from the stream information that identifies a specific person. Li [0254]
In regard to claim 10, Li disclosed the computer-implemented method of claim 9, wherein the stream comprises a video stream captured by a visual sensor in a medical facility room of the set of operation rooms, and wherein extracting from the stream information that identifies a specific person comprises generating a de-identified visual model of the person based on images of the person. Li [0069]
In regard to claim 11, Li disclosed the computer-implemented method of claim 9, wherein the stream comprises an audio stream captured by an audio sensor in a medical facility room of the set of operation rooms, and wherein extracting from the stream information that identifies a specific person comprises generating a person-specific voiceprint of the person. Li [0097]
Claim 12 is rejected for substantially the same reasons as claim 1.
Claim 13 is rejected for substantially the same reasons as claim 3.
Claim 14 is rejected for substantially the same reasons as claim 4.
Claim 15 is rejected for substantially the same reasons as claim 5.
Claim 16 is rejected for substantially the same reasons as claim 6.
Claim 17 is rejected for substantially the same reasons as claim 7.
Claim 18 is rejected for substantially the same reasons as claim 8.
Claim 19 is rejected for substantially the same reasons as claim 9.
Claim 20 is rejected for substantially the same reasons as claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hastings et al. US 2024/0244315
Stoyanov US 2023/0315905
Prevrhal et al. US 2024/0386140
Chen et al. US 2023/0352133
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jeffrey R. Swearingen whose telephone number is (571)272-3921. The examiner can normally be reached M-F 8:00 am - 5:00 pm.
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Jeffrey R. Swearingen
Primary Examiner
Art Unit 2445
/Jeffrey R Swearingen/Primary Examiner, Art Unit 2445