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 .
Response to Arguments
I. Claim Rejections under 35 U.S.C. § 101
Applicant’s arguments concerning the previous § 101 rejections have been fully considered but are not persuasive.
Applicant first argues that “it is not feasible to assess a plurality of biomarker-related data to generate physiological biomarkers, and determine a health status of the subject based on the physiological biomarkers in the human mind.” The Examiner respectfully disagrees. The human mind is fully capable of performing calculations and evaluations such as these. For example, a doctor can mentally generate multiple biomarkers of a patient based on an analysis of the patient and/or their data, and then make mental determinations as to the patient’s health status based on the biomarkers.
Applicant next argues that the claims recite a “particular machine” and thus satisfy Step 2A Prong Two (integration into a practical application) of the § 101 analysis. The Examiner respectfully disagrees.
The Examiner first notes that claim 9 and its dependents do not positively require the structural details of the collection unit at all, despite reciting the language of it in the claim. Given the nature of claim 9 being directed to media with instructions, the scope of the claim does not actually include the collection unit itself; rather, the scope of the claim includes only the instructions which merely act on data that originated from such a unit. There is nothing within the scope of the claim which suggests that the instructions are somehow limited to only being able to process data that was collected by that unit. Rather, it appears that claim 9 merely encompasses instructions that must be capable of processing the recited data collected from such a unit. As such, this argument is moot for claim 9.
Turning to claims 1 and 14, this argument is not persuasive because (1) the amended data collection unit is still recited at a high level of generality, and (2) the amended data collection unit is merely involved in the claim as pre-solution activity. See MPEP 2106.05(b) (two factors relevant to the “particular machine” element include the particularity or generality of the machine, and whether its involvement is extra-solution activity).
Concerning (1) above, other than excluding small unit sizes (“configured to receive an entirety of the subject”), there is nothing particular about the structure claimed. The claimed first and second positions of the sensors are insignificant because they aren’t claimed as particular or specific positions, and it is otherwise inherently true that two different sensors do not occupy the exact same space, and thus two different sensors will always be in two different positions. The claimed size is also not particular; it simply excludes smaller form factors. Otherwise, it could be approximately the size of a human body, or twice as large, or ten times as large, etc. with no upper limit. There is nothing claimed to indicate even the general shape or size of such a “structure.” As such, there are no claimed particular details that would be sufficient to satisfy the § 101 concerns due to reciting a particular machine.
Concerning (2) above, as noted in MPEP § 2106.05(b), “Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not integrate a judicial exception or provide significantly more.” Here, the claimed collection unit is merely used to gather biomarker-related data of the user so that the data can subsequently be used for the data analysis, i.e. for the mental process.
Accordingly, the added limitations of the data collection unit do not amount to an integration into a practical application in Step 2A Prong Two and/or significantly more in Step 2B.
II. Claim Rejections under 35 U.S.C. § 102
Applicant’s remarks concerning the previous § 102 rejections have been fully considered; although not fully persuasive (see next paragraph), the claims have been amended to recite additional limitations not taught by Heneghan alone. Those rejections have been withdrawn. However, after further search and consideration, updated grounds of rejection under 35 U.S.C. § 103 are made in view of a newly discovered prior art reference.
Concerning Applicant’s remark that “Without further explanation, the Office Action references the same sections of Heneghan as allegedly describing the first and second physiological biomarkers disclosed in claim 1. As recited in claim 1 and described in the Specification (e.g., at [0053]-[0059]), the recited biomarker-related data and the physiological biomarkers are distinctively defined elements of claim 1. As such, a single feature described in Heneghan cannot disclose both the biomarker-related data and the physiological biomarkers,” the Examiner notes that just like Applicant, Heneghan collects raw data via sensors which are they processed into meaningful physiological metrics (as is standard in the medical diagnostic arts). One skilled in the art would realize from the same cited portions in the office action (as well as from having ordinary skill in understanding how such sensors function) that Heneghan teaches both the raw data as well as the metrics/biomarkers.
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 and 3-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a mental process without significantly more.
Step 1: All of claims 1-20 are directed either to a method/process or to a system/machine.
Step 2A, Prong One: The claims recite a mental process including steps such as “generating … and determining …” [see claims 1 and 14], “receive … identify … generate a … model …” [see claim 9], and “receive … generate … and determine …” [see claim 14] which could be performed by the human mind and/or by a human with a physical aid such as pen and paper.
Step 2A, Prong Two: This judicial exception is not integrated into a practical application because the claims merely implement the mental process using generic processing technology and add insignificant extra-solution activity. Specifically: the steps of collecting the biomarker-related data and/or environmental data using a multimodal data collection unit with sensors is considered insignificant pre-solution activity of mere data gathering, since it merely collects the data necessary to carry out the mental process; the step of displaying the end result (see, e.g., claim 8) is considered insignificant post-solution activity since it merely outputs the result of the mental process using a generic output modality. Furthermore, merely carrying out mental steps using generic computing technology such as “one or more processors” and “computer readable media” and a generated “machine learning model” is well established to not amount to an integration into a practical application under the § 101 analysis. See, e.g., MPEP §§ 2106.04(a)(2)(III)(C) and 2106.04(d)(I) and 2106.05(f).
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements recited in the claims are generic processing/computing components and generic data collection and output components. The Examiner previously took official notice that these are basic, generic components which are well-understood, routine and conventional in the medical diagnostic arts, and the claims here merely use them for their well-understood, routine and conventional functions. Applicant’s subsequent reply did not traverse the Examiner's assertion of official notice; therefore, the facts under official notice are now taken to be admitted prior art. See MPEP § 2144.03(C) (“If applicant does not traverse the examiner' s assertion of official notice or applicant' s traverse is not adequate, the examiner should clearly indicate in the next Office action that the common knowledge or well-known in the art statement is taken to be admitted prior art because applicant either failed to traverse the examiner' s assertion of official notice or that the traverse was inadequate.”). The Examiner further takes official notice that a data collection unit configured to receive an entirety of a subject and having numerous sensors for detecting physiological parameters of the subject is also well-understood, routine and conventional in the medical diagnostic arts. As such, those additional elements cannot be considered “significantly more” than the judicial exception in Step 2B of the § 101 analysis.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1 and 3-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 11,191,466 B1 to Heneghan et al. (hereinafter “Heneghan”) in view of US 2022/0087546 A1 to Simon et al. (hereinafter “Simon”).
Regarding Claims 1 and 14, Heneghan teaches a method comprising:
collecting first biomarker-related data of a subject from a first sensor of a multimodel data collection unit and a second biomarker-related data of the subject from a second sensor of the multimodal data collection unit (see, e.g., the abstract: “Physiological variables, metrics, biomarkers, and other data points can be used, in connection with a non-invasive wearable device, to screen for, and predict, mental health issues and cognitive states.”; see, e.g., Col. 3 lines 14-26 discussing some example sensor types), wherein the first sensor is positioned at a first position of the multimodal data collection unit relative to the subject; the second sensor is positioned at a second position of the multimodal data collection unit relative to the subject (inherently true, as any two different sensors do not occupy the exact same physical space, i.e. they cannot be in the exact same position as each other); the first biomarker-related data being tagged with a first time of collection of the first biomarker-related data from the first sensor, the second biomarker- related data being tagged with a second time of collection of the second biomarker-related data from the second sensor (as is customary in medical diagnostics, the sensor data is tagged with the time of measurement – see, e.g., FIGS. 2A-B showing measurements over time, and see, e.g., Col. 4 lines 27-30: “One or more of the health-related metrics can be monitored over time to determine patterns or cycles of variation in the metrics, which can be correlated with mental state” and Col. 13 lines 53-56: “As with resting heart rate data illustrated in FIGS. 2A and 2B, values for metrics such as hemoglobin, water concentration, and SpO.sub.2 can be cyclical. By monitoring how these metrics vary in the user's body over time”);
generating a first physiological biomarker using the first biomarker-related data and a second physiological biomarker using the second biomarker-related data (see portions cited above); and
determining a health status of the subject based on the first physiological biomarker and the second physiological biomarker (see, e.g., the abstract: “Applying predictive modeling, one or more of the monitored metrics can be correlated with mental states and disorders. Identified patterns can be used to update the predictive models, such as via machine learning-trained models, as well as to update individual event predictions. Information about the mental state predictions, and updates thereto, can be surfaced to the user accordingly”; also see, e.g., claim 1: “determining, using the one or more biomarkers, a mental state status for the user”).
Heneghan envisions a variety of form factors, but fails to teach “the multimodal data collection unit comprises a structure configured to receive an entirety of the subject.” However, this form factor of a multimodal data collection unit was known in an analogous piece of art, as seen in Simon who teaches a full-body vital sign scanner and capture device (100) configured to receive an entirety of the subject (see e.g. FIG. 2 reproduced below) and which includes a variety of non-invasive sensor types spaced along the sidewalls and/or top member (see e.g. the abstract). It would have been obvious to one of ordinary skill in the art as of Applicant's effective filing date to modify Heneghan to implement the device in the full-body scanner form factor seen in Simon because it would predictably and advantageously help evaluate the health of subjects who pass through the device, which would be particularly advantageous in situations such as the entrance to public transit, a theme park, an office building, a stadium etc. where similar portal-style form factor devices are already commonly used (e.g. for metal detection) to screen large numbers of entrants.
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Regarding Claim 15, see, e.g., “non-invasively obtained data” in the title and “a non-invasive wearable device” in the abstract of Heneghan.
Regarding Claims 3 and 16, see, e.g., Col. 27 line 55 through Col. 28 line 8 discussing environmental sensor(s) which may be factored into the health status determination.
Regarding Claims 4, 9, 11, 13 and 17, in addition to the portions cited above for independent claims 1 and 14, see, e.g., Col. 11 lines 24-31 which discusses how machine learning techniques can be trained on metrics, physiological data etc. for “a general population,” i.e. a plurality of subjects. Also see other recitations of “machine learning” throughout Heneghan.
Regarding Claims 5 and 18, see, e.g., the discussing of “gamification” data, such as in claim 1 of Heneghan.
Regarding Claims 6 and 19, Heneghan teaches that a variety of combinations of multiple sensors could be used, which would include three or more sensors. As one example, see Col. 28 lines 1-3 (“For example, a monitoring device may calculate the user's stress or relaxation levels based on a combination of HR variability, skin conduction, noise pollution, and/or sleep quality”). Also see Col. 15 lines 4-24.
Regarding Claims 7, 10 and 20, see, e.g., Col. 8 line 19-35 and Col. 13 lines 53-62 and Col. 15 line 54 through Col. 16 line 21.
Regarding Claim 8, see, e.g., display screen 106. Also see, e.g., FIG. 6 and its corresponding description starting at Col. 28 line 46. Furthermore, Simon teaches that the full-body scanner form factor can include display screen 108 which can display both the health status (see e.g. Paras. 26-28, 32, 34, 38-39 of Simon) and instructions to follow (see e.g. Para. 34 of Simon). It would have been obvious to one of ordinary skill in the art as of Applicant's effective filing date to further modify Heneghan to incorporate a display into the multimodal collection unit, as seen in both Heneghan and Simon, so that both instructions and health status could be conveniently viewed.
Regarding Claim 12, see e.g. claim 2 of Heneghan (the machine learning techniques disclosed can include various types of neural networks).
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Heneghan in view of Simon as applied to claim 1 above, and further in view of US 11,633,103 B1 to Nudd et al. (hereinafter “Nudd”).
Regarding Claim 21, Heneghan as modified above teaches a camera (see “camera” in Heneghan) but fails to specifically teach the second sensor comprises a camera sensor, the second biomarker-related data comprises video data of the subject, and the first physiological biomarker comprises a walking gait biomarker of the subject. However, this type of sensing was known in an analogous multi-model system. Nudd teaches a multi-modal health monitoring system which includes monitoring gait from video cameras for health purposes (see e.g. Col. 18 lines 3-38). It would have been obvious to one of ordinary skill in the art as of Applicant's effective filing date to further modify Heneghan to monitor gait via a video camera, as seen in Nudd, because it would predictably enhance Heneghan by collecting additional useful diagnostic information.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20210287798 A1 to Peterson et al. teaches a similar portal/checkpoint-style physiological scanner. See e.g. FIG. 1.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN R DOWNEY whose telephone number is (571)270-7247. The examiner can normally be reached Monday-Friday 8:30am-5:00pm ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, NIKETA PATEL can be reached at (571)-272-4156. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOHN R DOWNEY/Primary Examiner, Art Unit 3792
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