DETAILED ACTION
Applicant' s arguments, filed 04/30/2026, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed 11/17/2023, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1-19 are the current claims hereby under examination.
Examiner’s Note: All references to Applicant’s specification are made using the paragraph numbers assigned in the US publication of the present application US 20240215861 A1.
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 Objections
Claims 1 and 12 are objected to because of the following informalities:
Claims 1 and 12 it appears that “YOLO” should read “You Only Look Once (YOLO)”
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
a communication component of claim 11
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
A communication component of claim 11 is described in purely functional language in paragraphs 0035-0036 as communicating via wires, wireless, network connection, or access point. No particular structure or device has been described.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Examiner’s Note: it would seem that amending the limitation “communication component” to “communication circuitry”, “wireless communication circuitry” or some other limitation that includes the physical description of “circuitry” would be sufficient to avoid 112f interpretation and would be considered to be supported by the recitations of communication components in the specification. Such an amendment would further need to clarify the relationship between the communication circuitry and the access point as described in the below presented 35 USC 112(b) rejection of claim 11.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim limitation “a communication component” of claim 11 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function, as described in the above presented claim interpretation section. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim 1 recites “a real-time YOLO object detection model to: …” but it is unclear if the model is carrying out all of, or a subset of the following steps. In particular, the limitation “identify, in the one or more current thermal images, a nostril region of interest corresponding to a nasal area by applying a neural network that …” which indicates that the identify step is carried out by a seemingly separate and distinct neural network from the YOLO model. It is thus unclear which of the receive, identify, determine, identify, extract, generate, and determine steps as recited in the claim are carried out by the YOLO model, as the level of indentation would appear to suggest, or if some portion is carried out with the Neural Network. Alternatively, it is unclear if the “neural network” of the identify a nostril region of an image step is a subset of or has some other relation to the YOLO model. For the purposes of this examination, the limitations will be interpreted as all being performed by some model which may include a neural network. This rejection and interpretation is similarly applied to claim 12 which includes the YOLO model and a separate neural network.
Claim 1 recites “determine whether the face region in the one or more current thermal images is identifiable” and then further recites “when the face region in the one or more current visible images is determined to be not identifiable” which makes it unclear whether the determination is carried out on the visible images, the thermal images, or both. For the purposes of this examination, the limitation is interpreted as “determine whether the face region in the one or more current visible images is identifiable” to better align with the following limitations and the specification.
Claim 1 recites “determine whether the face region in the one or more current visible (as interpreted in light of the 35 USC 112(b) rejection presented above) images is identifiable” but it is unclear what such a determination entails. It is unclear what metrics or parameters constitute an “identifiable” face image. For the purposes of this examination, the limitation will be interpreted as the facial features being visible in the visible images. This rejection and interpretation are similarly applied to claim 12.
Claim 1 recites “identify a face region in the one or more current visible images; determine whether the face region in the one or more current visible (as interpreted in light of the 35 USC 112(b) rejection presented above) images is identifiable; when the face region in the one or more current visible images is determined to be not identifiable …” it is unclear how the face region is identified in the visible images as required by line 9 but may also be determined to be unidentifiable as recited in lines 10-14. It is unclear if the identification of line 9 is distinct from the determination that the face region cannot be identified. For the purposes of this examination, the identification if the face region of line 9 will be interpreted as the generic locating of a user’s face in an image and the determination if the face region is identifiable will be interpreted as a separate determination of if the face region is visible or clear to a requisite degree for further processing. This rejection and interpretation are similarly applied to claim 12.
Claims 2-11 are rejected by virtue of their dependance on claim 1.
Claims 13-19 are rejected by virtue of their dependance on claim 12.
Claim 6 recites “extract a photoplethysmography signal from brightness changes of the forehead region of interest” but it is unclear if the PPG signal is being extracted from the brightness changes in the thermal or visible images. For the purposes of this examination, the limitation will be interpreted as brightness changes in the visible images since the forehead region is identified in the visible images. This rejection and interpretation are similarly applied to claim 17.
Claim 7 recites “compute an average pixel-intensity value within the forehead region of interest” but it is unclear if this intensity value is being calculated from the visible or thermal images. For the purposes of this examination, the limitation will be interpreted as being determined from the visible images.
Claim 8 recites “notify the abnormal respiratory information when the at least one of the mouth region of interest or the nasal region of interest is determined to be not obscured” but it is unclear what this limitation is meant to convey. It is unclear if the limitation is meant to convey that the abnormal respiratory information is notified upon detection that either the mouth, nose, or both are not covered, i.e. one or both are visible to the visible camera and upon such a detection the alarm is generated, or if the limitation is meant to convey that the process of claim 1 is only carried out when it is determined that at least one of the nose or mouth is visible. Both interpretations appear to contradict claim 1 as the first interpretation seemingly negates the process of determining an abnormal respiratory condition as described in claim 1 and the second interpretation indicates that the process of claim 1 can be carried out when only the mouth is visible and the nose is secured. The claim presently conveys that upon detection that the face is identifiable in the visible images, the system will always notify abnormal respiratory information unless both the nose and mouth of the patient are covered. However if these areas are covered then it would seem that the face region is not identifiable based on the above presented interpretations of what such a determination of identifiable face region entails. It is unclear what the scope of the claim entails and how it related to the system of claim 1. The claim has not been rejected over the prior art as it is unclear what teachings would serve to anticipate it. This rejection and interpretation are similarly applied to claim 18.
Claim 11 recites “wherein the processor is configured to transmit at least one of the respiratory information and the abnormal respiratory information to a user equipment via an Access Point” but it is unclear what an “Access Point” entails and if the “Access Point” is intended to be conveyed as a physical part of the system or if the “Access Point” is merely the interaction between the communication component and the user equipment. If the “Access Point” is meant to entail a physical device in the system then it is unclear if it is the same as, related to, or different from the “communication component. For the purposes of this examination, the communication component will be interpreted as any type of wireless communication circuitry and the access point will be interpreted as the connection between the system and the user equipment.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 1 and 11-12 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites “determine whether the face region in the one or more current visible (as interpreted in light of the 35 USC 112(b) rejection presented above) images is identifiable”. This limitation encompasses any known and as of yet unknown method of determining a face region in a visible image is “identifiable”. It would seem that the specification is required to describe how such a determination takes place such as what features, parameters, or other metrics of the visible images are considered and how they are processed to produce the output that the face region is identifiable or not. The specification describes this step in purely functional language in paragraph 0040 and Fig. 4A. The particular inputs and how they are considered to produce the recited output are not seemingly disclosed. The specification does not disclose any species of how such a determination may be carried out to support the claimed genus of any method of making such a determination and it thus considered to lack sufficient written description for the claimed determination. This rejection is similarly applied to the similar recitations of claim 12.
Claim 11 the limitation “a communication component” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function, as described in the above presented claim interpretation section. Therefore, the claim lacks sufficient written description and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-19 are directed to a method of processing visible and thermal signals using a computational algorithm, which is an abstract idea. Claims 1-19 do not include additional elements that integrate the exception into a practical application or that are sufficient to amount to significantly more than the judicial exception for the reasons provided below which are in line with the 2014 Interim Guidance on Patent Subject Matter Eligibility (Federal Register, Vol. 79, No. 241, p 74618, December 16, 2014), the July 2015 Update on Subject Matter Eligibility (Federal Register, Vol. 80, No. 146, p. 45429, July 30, 2015), the May 2016 Subject Matter Eligibility Update (Federal Register, Vol. 81, No. 88, p. 27381, May 6, 2016), and the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 4, page 50, January 7, 2019) and the 2024 Update on Subject Matter Eligibility (Federal Register, Vol 89, No. 137, page 58128, July 17, 2024).
The analysis of claim 1 is as follows:
Step 1: Claim 1 is drawn to a machine.
Step 2A – Prong One: Claim 1 recites an abstract idea. In particular, claim 1 recites the following limitations:
[A1] identify a face region in the one or more current visible images
[B1] determine whether the face region in the one or more current visible images is identifiable
[C1] when the face region in the one or more current visible images is determined to be not identifiable, identify, in the one or more current thermal images, a nostril region of interest corresponding to a nasal area by dividing each current thermal image into a grid and predicts bounding boxes and probabilities for sections of the grid
[D1] extract a pixel-intensity time-series representing brightness changes of the nostril region of interest in the one or more current thermal images
[E1] obtain temperature readings of the nostril region of interest during inhalation and exhalation from the thermal imaging sensor
[F1] generate respiratory information by detecting and counting cycles of exhalation and inhalation through the nostril region of interest based on the brightness changes and the temperature readings
[G1] determine abnormal respiratory information by comparing the cycles of exhalation and inhalation with a normal respiratory standard that includes completing one inhalation followed by one exhalation within a predetermined time period
[H1] notify the abnormal respiratory information
These elements [A1]-[H1] of claim 1 are drawn to an abstract idea since they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 1 recites the following limitations that are beyond the judicial exception:
[A2] a detector, comprising a visible light sensor, configured to capture one or more current visible images within a target area, and a thermal imaging sensor, configured to capture one or more current thermal images within the target area
[B2] a host computer comprising a processor
[C2] a real-time YOLO object detection model
[D2] receive the one or more current visible images and the one or more current thermal images from the detector
[E2] a neural network
[F2] an alarm component comprising at least one of a buzzer and an indicator light
These elements [A2]-[F2] of claim 1 do not integrate the exception into a practical application of the exception. In particular, the elements [A2], [D2], and [F2] are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). Furthermore, the element [B2] is merely an instruction to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f). Additionally, the elements [C2] and [E2] are nothing more than the computer implementation/automation of an abstract mental process of screening a patient, which is what a physician typically does with a patient in a diagnostic setting
Step 2B: Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “a detector, comprising a visible light sensor, configured to capture one or more current visible images within a target area, and a thermal imaging sensor, configured to capture one or more current thermal images within the target area” is merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. In particular, the data acquirer is nothing more than a visible light imaging sensor and a thermal imaging sensor for imaging the patient’s face. Such sensors are conventional as evidenced by Applicant’s lack of a particular description in the specification. In particular paragraphs 0022-0024, 0028, and 0036 recite that the visible imaging sensor “can be a Charge-coupled Device (CCD) or a CMOS to constantly detect the plurality of visible images (VSI) for a period of time” and that the thermal imaging sensor “can be thermocouples, thermopiles, optical arrays, and the like”. Applicant’s lack of a particular description of the sensors indicates that they are well-known, routine, and/or conventional sensors. Additionally the components of the alarm component “at least one of a buzzer and an indicator light” are each well-known, routine, and/or conventional components as indicated by Applicant’s lack of a particular description as to their structure and function such as in paragraph 0034. The sensors and alarms in combination with the computing elements do not amount to significantly more than the abstract idea because each element is used in its conventional manner and does not amount to significantly more when considered as a whole.
Further, the element [B2] does not qualify as significantly more because this limitation is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
Finally the elements [C2] and [E2] do not amount to significantly more than the abstract idea because they are nothing more than the computer implementation/automation of an abstract mental process of screening a patient, which is what a physician typically does with a patient in a diagnostic setting. These elements are considered a computer implementation of the human mind’s decision making / judgment process and the functions they perform can be practically performed in the human mind using nothing more than pen and paper.
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claims 2-11 depend from claim 1, and recite the same abstract idea as claim 1. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm), with the following exceptions:
Claim 11: a communication component; and
Claim 11: a user equipment
Claim 11: an Access Point
Each of these claim limitations does not integrate the exception into a practical application. In particular, each of these limitations does not recite additional elements that amount to significantly more than the judicial exception itself because they are merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements.
The limitations from claim 11 is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions (that is, one of wireless communication to another computer) that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claim 12 recites substantially the same abstract idea as claim 1 and only recites additional elements which have already been addressed in the above rejection of claim 1. Thus, Claim 12 is rejected on the same basis as presented with respect to claim 1 above
Claims 13-19 depend from claim 12, and recite the same abstract idea as claim 12. Claims 13-19 recite only additional limitations that further limit the abstract idea and are thus rejected on the same basis as claim 12.
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 9-14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Lewis US Patent Application Publication Number US 20130342691 A1 hereinafter Lewis in view of Xu US Patent Application Publication Number US 20120289850 A1 hereinafter Xu further in view of Gupta “Thermal Nostril Tracking Using YOLOv4-Tiny” published by IEEE on April 11th 2022, pages 1-6 hereinafter Gupta.
Regarding claim 1, Lewis teaches a facial recognition system (Abstract, Paragraph 0169: track the facial area), comprising:
a detector, comprising a visible light sensor, configured to capture one or more current visible images within a target area, and a thermal imaging sensor, configured to capture one or more current thermal images within the target area (Paragraphs 0161, 0163, and 0170: the infrared and visible light cameras; Fig. 12: the scene of field of view 1230); and
a host computer, coupled to the detector and comprising a processor configured to execute instructions (Paragraphs 0160-0161: the infant monitoring system, or host computer, comprises a processor, memory and display; Fig. 12 reference 1200 and 1208) to:
receive the one or more current visible images and the one or more current thermal images from the detector (Paragraph 0169 and 0176: the processor receives and processes the visible and infrared light);
identify a face region in the one or more current visible images (Paragraph 0176: the visible light images may be used for face tracking algorithms in certain light conditions);
determine whether the face region in the one or more current visible images is identifiable (Paragraph 0176: the visible light images may be beneficial in certain light conditions thus when conditions are not favorable, or when it is determined that the face region is not identifiable in the visible light images, the thermal images and/or a fusion of visible and thermal images may be used);
when the face region in the one or more current visible images is determined to be not identifiable (Paragraph 0176: the visible light images may be beneficial in certain light conditions thus when conditions are not favorable, or when it is determined that the face region is not identifiable in the visible light images, the thermal images and/or a fusion of visible and thermal images may be used),
identify, in the one or more current thermal images, a nostril region of interest corresponding to a nasal area (Paragraphs 0175 and 0177: identifying the nose using appropriate detection and tracking operations for thermal images);
extract a pixel-intensity time-series representing brightness changes of the nostril region of interest in the one or more current thermal images and obtain temperature readings of the nostril region of interest during inhalation and exhalation from the thermal imaging sensor (Paragraphs 0177-0179 identifying pixels in the oro-nasal region using the thermal images having characteristics of exhaled breathing including temperature being slightly lower than body temperature. The processor detects periodic alterations of slightly higher and lower temperatures in the nostrils; Paragraph 0183: the thermal images can be converted to user-viewable grey scale where temperature corresponds to a certain color and/or intensity. The generation of user-viewable thermal images with color/intensity corresponding to measured temperature is considered to at least suggest the generation of pixel-intensity time-series and the identification of inhalation and exhalation therefrom since paragraphs 0177-0179 discuss that there are a variety of method of identifying inhalation and exhalation including temperature fluctuations around the nose and such fluctuations would necessarily be present and identifiable in the user-viewable brightness format of the thermal images. This logic is applied throughout the claims where limitations are drawn towards the detection of brightness changes);
generate respiratory information by detecting cycles of exhalation and inhalation through the nostril region of interest based on the brightness changes and the temperature readings (Paragraphs 0177-0179 and 0183: the patient inhalations and exhalations are detected by temperature fluctuations in the nostril area and the detection is at least suggested to be based on the brightness changes of the visible projection of the infrared data which conveys the same temperature information); and
determine abnormal respiratory information by comparing the cycles of exhalation and inhalation with a normal respiratory standard (Paragraph 0177: abnormal breathing conditions are detected by comparing durations between breaths); and
an alarm component, coupled to the processor, comprising at least one of a buzzer and an indicator light (Paragraph 0195: the alarm may be a warning light and/or a speaker),
wherein the processor is configured to activate the alarm component to notify the abnormal respiratory information (Paragraph 0174: the alarm is generated when abnormal breathing is detected).
Lewis fails to further teach the system wherein the process is executed by a real-time YOLO object detection model, identifying the nostril region of interest by applying a neural network that divides each current thermal image into a grid and predicts bounding boxes and probabilities for sections of the grid; counting cycles of inhalation and exhalation; and the normal respiratory standard including completing one inhalation followed by one exhalation within a predetermined time period
Xu teaches a system and method for monitoring respiration of a subject or subject of interest using a thermal imaging system with single or multiple spectral bands set to a temperature range of a facial region of that person. Temperatures of extremities of the head and face are used to locate facial features in the captured thermal images, i.e., nose and mouth, which are associated with respiration. The RGB signals obtained from the camera are plotted to obtain a respiration pattern. From the respiration pattern, a rate of respiration is obtained. The system includes display and communication interfaces wherein alerts can be activated if the respiration rate falls outside a level of acceptability. The teachings hereof find their uses in an array of devices such as, for example, devices which monitor the respiration of an infant to signal the onset of a respiratory problem or failure (Abstract). Thus, Xu falls within the same field of endeavor as Applicant’s invention.
Xu teaches a system which includes generating a pixel-intensity time-series representing brightness changes of the nostril region for counting cycles of inhalation and exhalation; and the normal respiratory standard including completing one inhalation followed by one exhalation within a predetermined time period (Paragraphs 0035, 0040-0041, 0045: the thermal camera values are converted into RBG pixels, the system may detect and count the peaks in the RBG curves over time to count the number of inhales and exhales to determine a respiration rate and compare this number to a normal rate to identify abnormal breathing)
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to implement the conversion of thermal values into RBG pixels and to count the inhalations and exhalations based on the time varying signal of the RBG values and compare the determined respiration rate to a normal respiration rate to identify abnormal breathing as taught by Xu into the system of Lewis because determining the respiration rate by monitoring breaths over time as taught by Xu may provide a more consistent measurement of respiration rate and better indication of normal breathing than the method of Lewis which uses durations between detected breaths to identify abnormal breathing and is more susceptible to variability than the measurement method of Xu since the measurement method of Lewis takes place over a shorter timeframe.
Lewis in view of Xu fails to further disclose the system wherein the process is executed by a real-time YOLO object detection model, identifying the nostril region of interest by applying a neural network that divides each current thermal image into a grid and predicts bounding boxes and probabilities for sections of the grid.
Gupta teaches a method for determining respiration rate by plotting infrared signals across the nostrils (Abstract). Thus, Gupta falls within the same field of endeavor as Applicant’s invention.
Gupta teaches a system wherein the process is executed by a real-time YOLO object detection model, identifying the nostril region of interest by applying a neural network that divides each current thermal image into a grid and predicts bounding boxes and probabilities for sections of the grid (Pages 3-4 section C. Nostril tracking: You Only Look Once [YOLOv4-Tiny]: the YOLO algorithm overlays a grid on the thermal image, predicts bounding boxes, generates a probability map, and determines confidence values for sections of the grid to identify the region of interest. The algorithm includes a neural network).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to configure the system of modified Lewis to be carried out using the YOLO algorithm as taught by Gupta because Gupta teaches that such an algorithm is fast and capable of identifying context-based information in the images to rapidly determine the regions of interest and thus may improve the speed and/or accuracy of the algorithm.
Regarding claim 12, Lewis teaches a generative method for physiological information, executed by a processor in a facial recognition system (Abstract, Paragraphs 0160-0161 and 0169: track the facial area using the system), the generative method comprising:
receiving one or more current visible images and one or more current thermal images from a detector comprising a visible light sensor and a thermal imaging sensor (Paragraphs 0161, 0163, and 0170: the infrared and visible light cameras; Fig. 12: the scene of field of view 1230; Paragraph 0169 and 0176: the processor receives and processes the visible and infrared light);
executing, by the processor (Paragraphs 0160-0161: the infant monitoring system, or host computer, comprises a processor, memory and display; Fig. 12 reference 1200 and 1208), instructions to identify a face region in the one or more current visible images (Paragraph 0176: the visible light images may be used for face tracking algorithms in certain light conditions);
determining whether the face region in the one or more current visible images is identifiable (Paragraph 0176: the visible light images may be beneficial in certain light conditions thus when conditions are not favorable, or when it is determined that the face region is not identifiable in the visible light images, the thermal images and/or a fusion of visible and thermal images may be used);
when the face region in the one or more current visible images is determined to be not identifiable (Paragraph 0176: the visible light images may be beneficial in certain light conditions thus when conditions are not favorable, or when it is determined that the face region is not identifiable in the visible light images, the thermal images and/or a fusion of visible and thermal images may be used), identifying, in the one or more current thermal images, a nostril region of interest corresponding to a nasal area (Paragraphs 0175 and 0177: identifying the nose using appropriate detection and tracking operations for thermal images);
extracting a pixel-intensity time-series representing brightness changes of the nostril region of interest in the one or more current thermal images and obtaining temperature readings of the nostril region of interest during inhalation and exhalation from the thermal imaging sensor ((Paragraphs 0177-0179 identifying pixels in the oro-nasal region using the thermal images having characteristics of exhaled breathing including temperature being slightly lower than body temperature. The processor detects periodic alterations of slightly higher and lower temperatures in the nostrils; Paragraph 0183: the thermal images can be converted to user-viewable grey scale where temperature corresponds to a certain color and/or intensity. The generation of user-viewable thermal images with color/intensity corresponding to measured temperature is considered to at least suggest the generation of pixel-intensity time-series and the identification of inhalation and exhalation therefrom since paragraphs 0177-0179 discuss that there are a variety of method of identifying inhalation and exhalation including temperature fluctuations around the nose and such fluctuations would necessarily be present and identifiable in the user-viewable brightness format of the thermal images. This logic is applied throughout the claims where limitations are drawn towards the detection of brightness changes);
generating respiratory information by detecting cycles of exhalation and inhalation through the nostril region of interest based on the brightness changes and the temperature readings (Paragraphs 0177-0179 and 0183: the patient inhalations and exhalations are detected by temperature fluctuations in the nostril area and the detection is at least suggested to be based on the brightness changes of the visible projection of the infrared data which conveys the same temperature information);
determining abnormal respiratory information by comparing the cycles of exhalation and inhalation with a normal respiratory standard (Paragraph 0177: abnormal breathing conditions are detected by comparing durations between breaths); and
notifying the abnormal respiratory information by activating an alarm component (Paragraph 0174: the alarm is generated when abnormal breathing is detected) comprising at least one of a buzzer and an indicator light (Paragraph 0195: the alarm may be a warning light and/or a speaker).
Lewis fails to further teach the method wherein the process is executed by a real-time YOLO object detection model, identifying the nostril region of interest by applying a neural network that divides each current thermal image into a grid and predicts bounding boxes and probabilities for sections of the grid; counting cycles of inhalation and exhalation; and the normal respiratory standard including completing one inhalation followed by one exhalation within a predetermined time period
Xu teaches a system which includes generating a pixel-intensity time-series representing brightness changes of the nostril region for counting cycles of inhalation and exhalation; and the normal respiratory standard including completing one inhalation followed by one exhalation within a predetermined time period (Paragraphs 0035, 0039-0041, 0045: the thermal camera values are converted into RBG pixels, the system may detect and count the peaks in the RBG curves over time to count the number of inhales and exhales to determine a respiration rate and compare this number to a normal rate to identify abnormal breathing. The amplitude and period of each cycles is monitored by comparing them to threshold values or previously recorded normal breaths to indicate abnormal breathing; Fig. 5A)
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to implement the conversion of thermal values into RBG pixels and to count the inhalations and exhalations based on the time varying signal of the RBG values and compare the determined respiration rate to a normal respiration rate to identify abnormal breathing as taught by Xu into the method of Lewis because determining the respiration rate by monitoring breaths over time as taught by Xu may provide a more consistent measurement of respiration rate and better indication of normal breathing than the method of Lewis which uses durations between detected breaths to identify abnormal breathing and is more susceptible to variability than the measurement method of Xu since the measurement method of Lewis takes place over a shorter timeframe.
Lewis in view of Xu fails to further disclose the method wherein the process is executed by a real-time YOLO object detection model, identifying the nostril region of interest by applying a neural network that divides each current thermal image into a grid and predicts bounding boxes and probabilities for sections of the grid.
Gupta teaches a method wherein the process is executed by a real-time YOLO object detection model, identifying the nostril region of interest by applying a neural network that divides each current thermal image into a grid and predicts bounding boxes and probabilities for sections of the grid (Pages 3-4 section C. Nostril tracking: You Only Look Once [YOLOv4-Tiny]: the YOLO algorithm overlays a grid on the thermal image, predicts bounding boxes, generates a probability map, and determines confidence values for sections of the grid to identify the region of interest. The algorithm includes a neural network).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to configure the method of modified Lewis to be carried out using the YOLO algorithm as taught by Gupta because Gupta teaches that such an algorithm is fast and capable of identifying context-based information in the images to rapidly determine the regions of interest and thus may improve the speed and/or accuracy of the algorithm.
Regarding claims 2 and 13 modified Lewis teaches the facial recognition system and method according to claims 1 and 12 respectively. Modified Lewis further teaches the system and method wherein the processor is further configured to determine that the abnormal respiratory information is present when a temperature difference of the nostril region of interest remains unchanged for longer than the predetermined time period (Paragraphs 0177-0179 and 0183: The temperature may be expressed in terms of pixel color and intensity; if no exhalation is detected for a certain period of time, generate the alert; periodic alterations of higher and lower temperatures are indicative of inhalation and exhalation).
Regarding claims 3 and 14 modified Lewis teaches the facial recognition system and method according to claims 1 and 12 respectively. Modified Lewis further teaches the system and method wherein the processor is configured to determine that the abnormal respiratory information is present when the pixel-intensity time-series corresponding to the brightness changes of the nostril region of interest remains unchanged for longer than the predetermined time period (Paragraphs 0177-0178: if no exhalation is detected for a certain period of time, generate the alert; periodic alterations of higher and lower temperatures are indicative of inhalation and exhalation).
Regarding claims 9 and 19 modified Lewis teaches the facial recognition system and method according to claims 1 and 12 respectively. Modified Lewis further teaches the system or method wherein the processor is configured to; obtain, from the thermal imaging sensor, a plurality of temperature readings at different positions within the region of interest; compute an average temperature from the plurality of temperature readings and determine abnormal temperature information when the average forehead temperature is outside a normal temperature range (Paragraphs 0179-0180: Body temperature may be determined by aggregating, averaging, or otherwise analyzing radiometric data of the face of the infant which includes the forehead; an alarm may be generated when the body temperature is determined to be outside certain threshold values)
An obvious variation of modified Lewis would be to identify a forehead region of interest in the one or more current thermal images, and determine the temperature readings and their average from the forehead region. Such a variation would be obvious because Lewis already discloses the capability of identifying facial regions in the thermal images (Paragraph 0175) and thus the identification of the forehead region would be obvious to try with a reasonable expectation of success because there are a finite number of known facial regions such as the forehead, cheeks, nose, mouth, and eyes and the recitations of Lewis in identifying some of these regions would lead one of ordinary skill in the art to try identifying all of them. Additionally, performing the body temperature measurement using the forehead temperature is considered an obvious variation because there are a finite number of identifiable and predictable solutions for determining a body temperature using thermal data of the face. Lewis teaches the use of aggregated thermal data to determine a body temperature (Paragraph 0179), and one of ordinary skill in the art would recognize that there are a finite number of identifiable and predictable locations of the face from which this data could be collected and aggregated including the forehead, cheek, mouth, nose, eyes, or any combination thereof. Thus the detection of a forehead region in the thermal imaging data and the determination of the body temperature therefrom are considered to be obvious variations of modified Lewis.
Regarding claim 10, modified Lewis teaches the facial recognition system according to claim 1. Modified Lewis further teaches the system wherein the processor is further configured to: activate the alarm component in response to determining the abnormal respiratory information (Paragraph 0174: the alarm is generated when abnormal breathing is detected; Paragraph 0195: the alarm may be a warning light and/or a speaker)
Regarding claim 11, (as best understood in light of the above presented 35 USC 112(b) rejection above) modified Lewis teaches the facial recognition system according to claim 1. Modified Lewis further teaches the system further comprising a communication component coupled to the processor, wherein the processor is configured to transmit at least one of the respiratory information and the abnormal respiratory information to a user equipment via an Access Point (Paragraphs 0189-0192: the system may include wireless communication capabilities to communicate with external devices, or user equipment; Paragraph 0199: the system may communicate through a wireless router or hub)
Claims 4-5 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Lewis US Patent Application Publication Number US 20130342691 A1 hereinafter Lewis in view of Xu US Patent Application Publication Number US 20120289850 A1 hereinafter Xu further in view of Gupta “Thermal Nostril Tracking Using YOLOv4-Tiny” published by IEEE on April 11th 2022, pages 1-6 hereinafter Gupta and applied to claims 1 and 12 above and further in view of Hill US Patent Application Publication Number US 20200085370 A1 hereinafter Hill.
Regarding claims 4-5 and 15-16 modified Lewis teaches the facial recognition system and method according to claims 1 and 12 respectively. Modified Lewis further teaches that breathing is detected by the periodic alteration of slightly higher and lower temperatures in the nostrils (Paragraph 0178), but fails to further disclose the system wherein the processor is further configured to: classify samples of the pixel-intensity time-series of the nostril region of interest into a first state and a second state based on whether pixel-intensity values are above or below a threshold derived from a reference brightness value; count alternations between the first state and the second state within a time window to generate a breaths-per-minute (BPM) estimate; and determine that the abnormal respiratory information is present when the breaths-per- minute (BPM) is outside a breaths-per-minute (BPM) criterion; and wherein the processor is configured to classify inhalation samples and exhalation samples of the nostril region of interest based on the brightness changes of the nostril region of interest in the one or more current thermal images prior to generate the breaths-per-minute estimate
Xu teaches that thermal imaging data may be converted into RBG values (Paragraph 0035). Xu teaches that the RBG values may be tracked over time to identify peaks and valleys in the RBG values. The peaks/valleys representing the varying temperature of the nostrils over the exhalation/inhalation cycle. The number of peaks/valleys within a time window are counted and compared to a normal breathing rate to determine abnormal breathing conditions (Paragraphs 0039-0041).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to implement the RGB conversion of thermal values and peak/valley detection as taught by Xu to detect abnormal breathing into the system and method of modified Lewis because Xu teaches that such a detection mechanism allows the amplitudes and periods of individual breaths to also be evaluated for abnormalities.
Modified Lewis fails to further teach the system or method wherein the processor is further configured to: classify samples of the pixel-intensity time-series of the nostril region of interest into a first state and a second state based on whether pixel-intensity values are above or below a threshold derived from a reference brightness value; and wherein the processor is configured to classify inhalation samples and exhalation samples of the nostril region of interest based on the brightness changes of the nostril region of interest in the one or more current thermal images prior to generate the breaths-per-minute estimate.
Hill teaches devices and methods for monitoring respiratory functions using thermal sensors (Abstract). Thus Hill falls within the same field of endeavor as Applicant’s invention.
Hill teaches that thermal data that shows rising temperature indicates an expiratory breath cycle and a dropping temperature indicates an inspiratory breath cycle. Hill teaches the use of a calculated or pre-determined threshold temperature to differentiate between the beginning and end of each breath cycle, or inspiratory and expiratory phases (Paragraph 0007).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to classify the peaks and valleys taught by Xu into inspiration and expiration phases using a predetermined or calculated threshold value as taught by Hill before generating breaths-per-minute estimates because such a value would clearly and consistently demark the beginning and end of each inhalation and exhalation which may improve the accuracy and consistency of breath evaluations by providing a consistent metric to demark their beginnings and ends.
Claims 6-7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Lewis US Patent Application Publication Number US 20130342691 A1 hereinafter Lewis in view of Xu US Patent Application Publication Number US 20120289850 A1 hereinafter Xu further in view of Gupta “Thermal Nostril Tracking Using YOLOv4-Tiny” published by IEEE on April 11th 2022, pages 1-6 hereinafter Gupta and applied to claims 1 and 12 above and further in view of Patil US Patent Application Publication Number US 20180035082 A1 hereinafter Patil in view of Agrawal US Patent Number US 9750420 B1 hereinafter Agrawal
Regarding claims 6-7 and 17 modified Lewis teaches the facial recognition system and method according to claims 1 and 12 respectively. Modified Lewis fails to further teach the system or method wherein, when the face region in the one or more current visible images is identifiable, the processor is configured to identify a forehead region of interest in the one or more current visible images; extract a photoplethysmography signal from brightness changes of the forehead region of interest; transform the photoplethysmography signal from a time domain into a frequency domain to generate a spectrum; extract a peak frequency as heart rate information from the spectrum; and determine abnormal heart rate information when the heart rate information is outside a normal range defined by a physiological criterion; and compute, for each image frame, an average pixel-intensity value within the forehead region of interest to form a time-domain brightness signal and transforming the time-domain brightness signal into a brightness signal in the frequency domain.
Patil teaches a monitoring system which uses cameras to monitor physiological conditions including breathing and heart rate (Abstract; Paragraph 0060). Thus, Patil falls within the same field of endeavor as Applicant’s invention.
Patil teaches a system and method wherein when the face region in the one or more current visible images is identifiable (Paragraph 0150: the face is used for heart rate detection and thus must be visible), the processor is configured to identify a region of interest in the one or more current visible images (Paragraph 0150: the face and neck); ; and determine abnormal heart rate information when the heart rate information is outside a normal range defined by a physiological criterion (Paragraph 0156: generate an alert when the determined heart rate is outside the range of normal heart rates).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to implement the heart rate monitoring taught by Patil into the system of modified Lewis because cardiac and respiratory conditions are closely related and configuring the system of modified Lewis to monitor heart rate as well and respiration signals would allow the system to provide a more comprehensive analysis and monitoring of the patient’s well-being.
Lewis in view of Xu in view of Gupta further in view of Patil fails to further teach the system or method wherein the region of interest is the forehead and the heart rate calculation includes extract a photoplethysmography signal from brightness changes of the forehead region of interest; transform the photoplethysmography signal from a time domain into a frequency domain to generate a spectrum; extract a peak frequency as heart rate information from the spectrum; and compute, for each image frame, an average pixel-intensity value within the forehead region of interest to form a time-domain brightness signal and transforming the time-domain brightness signal into a brightness signal in the frequency domain.
Agrawal teaches an image classifier for detecting features of the face and detecting heart rate using cameras by analyzing the color of the image data measurements over time (Abstract). Thus, Agrawal is reasonably pertinent to the problem at hand.
Agrawal teaches a system or method wherein the region of interest is the forehead (Col 11 lines 25-33: the forehead may be the region of interest) and the heart rate calculation includes extract a photoplethysmography signal from brightness changes of the forehead region of interest; transform the photoplethysmography signal from a time domain into a frequency domain to generate a spectrum; extract a peak frequency as heart rate information from the spectrum; and compute, for each image frame, an average pixel-intensity value within the forehead region of interest to form a time-domain brightness signal and transforming the time-domain brightness signal into a brightness signal in the frequency domain. (Col 11 line 65 – Col 12 line 53: the heart rate may be determined by transforming the color intensity signals, or PPG signals, which are determined by taking a mean intensity value of the pixels in the region of interest to form a time-based pattern, and transforming them to a frequency domain then selecting the frequency with the highest amplitude as the heart rate).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to configure the system and method of Lewis in view of Xu in view of Gupta further in view of Patil to utilize the heart rate determination method using the forehead region as taught by Agrawal because it is a simple substitution of one known element (the method of Patil) for another known method (the method of Agrawal) with no surprising technical effect (the heart rate is determined).
Claims 8 and 18 have not been rejected over the prior art because, as described in the above 35 USC 112(b) rejection, their scope and how they relate to the claimed system and method is unclear and seemingly contradictory.
Response to Arguments
Applicant’s arguments with respect to the claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant’s arguments that the amended claims are not capable of being performed in the human mind and thus do not constitute an abstract idea are not found to be persuasive because the recited steps of the claim do not include any constraints to the determinations, calculations, or processes which would render them incapable of being practically performed in the human mind. The claimed receipt of images and sensors used for such purposes are addressed as mere data gathering outside of the abstract idea. The activation of an alarm and transmission of data are also considered to be insufficient extra-solution activity drawn towards the mere output of the abstract idea, or the processing algorithm. The claims taken as a whole are not considered to amount to significantly more than the abstract idea itself.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/MATTHEW ERIC OGLES/Examiner, Art Unit 3791
/JASON M SIMS/Supervisory Patent Examiner, Art Unit 3791
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