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 Objections
Claim 1 is objected to because of the following informalities:
Claim 1 includes “a. At least one…” but should be “a. at least one…” The MPEP, in section 608.01(m), states: "Each claim begins with a capital letter and ends with a period. Periods may not be used elsewhere in the claims except for abbreviations. See Fressola v. Manbeck, 36 USPQ2d 1211 (D.D.C. 1995).”
Claim 1 includes “i. that perform digital” but should be “i. perform digital…”
Claim 1 includes “using a series of A series of…” but should be “using a series…”
Claim 1 includes “the BAF principal” but should be “the BAF principle…”
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 1-21 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.
Step 1
Claims 1-21 are drawn to a system and a method, which is/are statutory categories of invention (Step 1: YES).
Step 2A Prong One
Independent claim 1 recites i. that perform digital signal processing of the raw wearable data via a series of digital signal processing algorithms; and ii. extracts wearable derived physiological biometrics (WDPB) from the results of said digital signal processing algorithms using a series of A series of extraction algorithms; iii. extract wearable derived behavioral biometrics (WDBB) from the results of said digital signal processing algorithms; and iv. utilize WBAPM for predicting biological age and biological age acceleration, where these models use physiological and behavioral biometrics (WDPB and WDBB) as input.
Independent claim 11 recites b. performing digital signal processing of the raw wearable data using a series of algorithms; c. extracting wearable-derived physiological biometrics (WDPB) from the results of the digital signal processing algorithms; d. extracting wearable-derived behavioral biometrics (WDBB) from the results of the digital signal processing algorithms; e. predicting biological age and biological age acceleration using WBAPM, based on the output models that predict biological age and biological age acceleration from high-throughput biology data (HBD) through application of the BiologicalAge Fit (BAF) principle.
The respective dependent claims 2-10 and 12-21, but for the inclusion of the additional elements specifically addressed below, provide recitations further limiting the invention of the independent claim(s).
Said above recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity, as reflected in the specification, which states that the invention is “to predict Wearable Derived Biological Age Acceleration (WDBAA) by utilizing a feature set known as the wearable-ome” (see: specification abstract). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people such as by following rules or instructions, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The present claims cover certain methods of organizing human activity because they address a problem where “[m]easuring the organismal state, biological age, and understanding the molecular and physiological mechanisms, how to track them, and influence the underlying processes is crucial for delaying the onset of chronic disease, and prolonging both healthspan and lifespan” (see: specification paragraph 2). The above recited limitations address these concerns by producing user “BAA and BA predictions…to provide feedback on their estimated biological age based on the BAF principle…” (see: specification paragraph 153). Accordingly, the claims recite an abstract idea(s) (Step 2A Prong One: YES).
Step 2A Prong Two
This judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including an “b. a computing device with memory, communication means, and processors, wherein the processors are configured to:…where these models…have been trained/are iteratively trained on the output models that predict biological age and biological age acceleration from HBD by application of the BAF principal…c. a user interface located on a wrist-worn wearable, a mobile device, a laptop, or a desktop display to display the biological age and biological age acceleration” (claim 1) and “trained on physiological and behavioral biometrics as input…f. providing a user interface, exemplified by a wrist-worn wearable, a mobile device, or a laptop/desktop display, to display results” (claim 11), which are additional elements that are claimed at a high level of generality (e.g., the “a computing device with memory, communication means, and processors” are implemented through no more than a statement than that said processors are “configured to” perform functions; the “models” are configured through no more than a statement than that they “have been trained/are iteratively trained on” desired data; the “user interface located on a wrist-worn wearable” and “user interface, exemplified by a wrist-worn wearable, a mobile device, or a laptop/desktop display” is/are configured through no more than a statement than that they are “to display” results data) such that they amount to no more than mere instruction to apply the exception using generic computer elements. See: MPEP 2106.05(f).
The claimed additional elements of “a. At least one wearable device that collects raw sensor data that i. tracks cardiovascular activity; and ii. tracks motion” (claim 1), “wherein additional behavioral biometrics (ABB) are recorded from other applicable IOT device(s) capable of transmitting lifestyle behavioral information and additional physiological biometrics (APB) are recorded from other applicable IOT device(s) capable of transmitting lifestyle behavioral information” (claim 4), “wherein a time series vector of multiple interchanging interventions are annotated or obtained through IOT for the user” (claim 8), “a. collecting raw sensor data from a wearable device;” (claim 11), “recording additional behavioral biometrics (ABB) and physiological biometrics (APB) from any other applicable IoT device capable of transmitting lifestyle behavioral information” (claim 14), and “annotating or obtaining a time series vector of multiple interchanging interventions through IoT for the user” (claim 18), are nominal or tangential addition to the abstract idea(s) and amount to extra-solution activity concerning mere data gathering. The addition of an insignificant extra-solution activity limitation does not impose meaningful limits on the claim such that it is not nominally or tangentially related to the invention. In the claimed context, these additional elements are incidental to the performance of the recited abstract idea(s) as outlined above. See: MPEP 2106.05(g).
The combination of these additional elements is no more than mere instructions to apply the exception using generic computer elements and limitations directed toward extra-solution activity. Accordingly, even in combination, these additional elements do not integrate the abstract idea(s) into a practical application because they do not impose any meaningful limits on practicing the abstract idea(s). Accordingly, the claims are directed to an abstract idea(s) (Step 2A Prong Two: NO).
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea(s) into a practical application, using the additional elements to perform the abstract idea(s) amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using generic components cannot provide an inventive concept. See MPEP 2106.05(f).
The claimed additional elements directed toward extra-solution activity, identified above, are not sufficient to amount to significantly more than the judicial exception because they are representative of concepts understood by the courts to be extra-solution activity and/or to perform well-understood, routine, and conventional activities previously known to the industry. The claimed limitations concerning collecting raw sensor data, obtaining information, and recording and transmitting information, are limitations representative of concepts related to electronic recordkeeping, receiving or transmitting data over a network such as by using the Internet to gather data or sending messages over a network, storing and retrieving information in memory, and performing clinical tests on individuals to obtain input for an equation. See: MPEP 2106.05(d)(II) and MPEP 2106.05(g).
The claimed additional elements directed to pre-solution activity, identified above, each amount to extra-solution activity and/or do not provide anything other than well‐understood, routine, and conventional functions when claimed in a merely generic manner (as they are presently). Viewing the claimed limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea(s) with routine, conventional activity specified at a high level of generality in a particular technological environment. Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea(s) (Step 2B: NO).
Dependent claim(s) 2-10 and 12-21, when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because they fail to establish that the claim(s) is/are not directed to an abstract idea(s) without significantly more. These claims fail to remedy the deficiencies of their parent claims above and are therefore rejected for at least the same rationale as applied to their parent claims above and incorporated herein.
Claim Rejections - 35 USC § 112
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 1-21 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 pre-AIA the applicant regards as the invention.
As per claim 1, the claim includes “WBAPM”, “HBD”, and “BAF” but does not fully elaborate upon each of the acronyms’ full meanings. To eliminate any chance for confusion, the first occurrence of each acronym should be completely spelled out and followed by the acronym in parenthesis. Claims 11 and 21 are rejected for similar reasons with regard to “WBAPM”.
As per claim 1, the claim includes “the BAF principal” but there is insufficient antecedent basis for this limitation in the claim. Claim 11 is rejected for similar reasons.
As per claim 1, the claim includes “have been trained/are iteratively trained” but it is unclear if the slash means the limitations are alternatives or if the claim covers both.
As per claim 1, the claim includes “these models” but there is insufficient antecedent basis for this limitation in the claim.
As per claim 1, the claim includes “trained on the output models that predict” but it is unclear as to if this means trained on the outputs of those models or trained to match them.
As per claim 2, the claim includes “several days” but “several” is a relative term which renders the claim indefinite. The term “several” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Claim 12 is rejected for similar reasons.
As per claim 9, the claim includes “wherein biological age changes predicted from periodic epigenome or other applicable HBD samples” but it is unclear as to if the predicted biological age is changed based on the samples, or if the change in biological age is predicted from the samples, or if this is an incomplete sentence fragment.
As per claim 9, the claim includes “(for example a change in pulse waveform health)” and “(e.g. increased vigorous exercise duration)”, but the phrases “for example” and “e.g.” render the claim indefinite because it is unclear whether the limitation(s) following the phrases are part of the claimed invention. See MPEP § 2173.05(d).
As per claim 10, the claim includes “FSCC” and “UPLGs” but does not fully elaborate upon each of the acronyms’ full meanings. To eliminate any chance for confusion, the first occurrence of each acronym should be completely spelled out and followed by the acronym in parenthesis.
As per claim 11, the claim includes “a user interface, exemplified by a wrist-worn wearable, a mobile device, or a laptop/desktop display,” but the phrases “exemplified” renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The remaining claims not specifically cited depend from and incorporate the rejected base claims addressed above and are rejected for similar reasons.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1-6, 11-17, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication 2019/0365332 to Gero in view of EP 2781602 A1 to Konstanz.
As per claim 1, Gero teaches a system comprising (computer implemented system and method for estimating wellness; Gero, para [0193]):
a. At least one wearable device that collects raw sensor data that (wearable device collects sensor data of users activity [raw sensor data]; Gero, para [0212]-[0213]),
i. tracks cardiovascular activity (smart wearable device tracks heartrate [cardiovascular activity]; Gero, para [0213]); and
ii. tracks motion (smart wearable device tracks speed, velocity, acceleration, orientation, angular velocity, angular acceleration [motion]; Gero, para [0213])
b. a computing device with memory, communication means, and processors, wherein the processors are configured to (computing device includes circuitry for network communication and processor executing stored instructions: Gero, para [0229], [0272]):
that perform digital signal processing of the raw wearable data via a series of digital signal processing algorithms (wellness evaluation data includes wearable sensor data of physical activity [raw sensor data] and processed using digital signal processors having a plurality of programmable processors implementing a plurality of evaluation procedures; Gero, para [0271]-[0272]); and
extracts wearable derived physiological biometrics (WDPB) from the results of said digital signal processing algorithms using a series of A series of extraction algorithms (a plurality of evaluation procedures [extraction algorithms] process subjects sensor data obtained from a wearable device using associated digital signal processors to determine physical parameters of the subject including heartrate [physiological biometrics], wherein the obtained data is extracted and analyzed for evaluating wellness; Gero, para [0208], [0213], [0271]-[0272]);
extract wearable derived behavioral biometrics (WDBB) from the results of said digital signal processing algorithms (wearable device obtains physical activity of subject to determine behaviors and habits [behavioral biometrics]; Gero, para [0213]; [0488], [0516], [0518]); and
utilize WBAPM for predicting biological age (wellness evaluation includes estimating age of subject, where the evaluated age of the subject comprises a biological age; Gero, para [0072], [0194], [0411]-[0413]), where these models use physiological and behavioral biometrics (WDPB and WDBB) as input and have been trained/are iteratively trained on the output models that predict biological age (wellness evaluation includes inputting physical activity and behavior of subject and training a machine learning model to estimate subjects biological age; Gero, para [0399], [0411]-[0413], [0510]) from HBD by application of the BAF principal (wellness evaluation uses fitness tracker [BAF principle] and biology data of subject such as birthdate and gender [biology data]; Gero, para [0513], [0521]); and
c. a user interface located on a wrist-worn wearable, a mobile device, a laptop, or a desktop display to display the biological age and biological age acceleration (outputting evaluated age to user through website of the front-end module including a desktop, laptop and mobile device [user interface]; Gero, para [0300], [0500], [0514], and [0517]).
Gero fails to disclose determining biological age and biological age acceleration; however, Konstanz teaches determining biological age and biological age acceleration (determination of the biological age of a human being includes identifying when aging process is accelerated; Konstanz, para [0014], [0050]).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the wellness evaluation system as taught by Gero to include determining biological age and age acceleration as taught by Konstanz with the motivation of enhancing health monitoring and diagnostic systems to more reliably detect underlying conditions leading to disease and providing more robust preventative healthcare (Konstanz, para [0011]).
As per claim 2, Gero and Konstanz teach the invention as claimed, see discussion of claim 1, and further teach:
where predictions of biological are averaged over several days in order to reduce the degree of day over day variability seen in BAF based models with low frequency sampling and hence make it possible to perform trend analysis on a shorter timescale (wellness evaluation includes processing dataset to reduce dataset [reduce variability] to detect and analyze trends by utilizing models that that sample the dataset in high and low frequency ranges, wherein reducing the data set includes averaging data over shorter timescales such as day to day datasets; Gero, para [0406]-[0409], [0429]-[0433]).
As per claim 3, Gero and Konstanz teach the invention as claimed, see discussion of claim 2, and further teach:
wherein the system is configured to provide the predictions daily, in order to provide more frequent estimates of biological age from wearable data than what is feasible by doing repeated sample collection and HBD production for BAF-based biological age prediction (wellness evaluation for determining age includes utilizing wearable device to obtain biology data [HBD production] and fitness analysis [BAF] and processing and sampling the datasets daily; Gero, [0406]-[0409], [0429]-[0433], [0513], [0520]).
As per claim 4, Gero and Konstanz teach the invention as claimed, see discussion of claim 2, and further teach:
wherein additional behavioral biometrics (ABB) are recorded from other applicable IOT device(s) capable of transmitting lifestyle behavioral information and additional physiological biometrics (APB) are recorded from other applicable IOT device(s) capable of transmitting lifestyle behavioral information (activity and behavior data obtained using smart wearable devices such as smartwatch, pocket smartphone, wristband, headband, knee guard, pair of glasses [IoT devices]; Gero, para [0212]-[0213]).
As per claim 5, Gero and Konstanz teach the invention as claimed, see discussion of claim 4, and further teach:
wherein Behavior-Physiology Temporal Causal Analysis (BPTCA) is used to discover statistically significant relationships between QCB and subsequent changes in biological age as predicted from the wearable device data, with a time delay ranging from zero days to one month (wearable device obtains sensor data that is analyzed to predict correlation in biological age with other health indices and lifestyle metrics [statistically significant relationships], wherein the evaluated age is updated [changes in biological age] based on the processed data; Gero, para [0365], [0380]-[0381], [0488]), with a time delay ranging from zero days to one month (wellness evaluation can be performed on a regular basis, for example, each week, or each month; Gero, para [0522]).
As per claim 6, Gero and Konstanz teach the invention as claimed, see discussion of claim 5, and further teach:
wherein candidate causal relationships (CCRs) between voluntary behavior and wearable-derived biological age are discovered on the data of a population of users and used to extrapolate insights from the larger population, to the behavior recorded for a single user (wellness evaluation includes processing behavior and biological data that is correlated to a reference population dataset; Gero, para [0195], [0503]-[0504]), wherein projected consequences of a user's behavior can be communicated to the user to provide a strong feedback mechanism that can help users adjust their behavior in time to prevent negative outcomes (producing recommendations and/or insights into lifestyle or living environment intervention to improve the subject's health; Gero, para [0196], [0518]).
As per claim 11, Gero teaches method comprising (computer implemented system and method for estimating wellness; Gero, para [0193]):
a. collecting raw sensor data from a wearable device (wearable device collects sensor data of users activity [raw sensor data]; Gero, para [0212]-[0213]);
b. performing digital signal processing of the raw wearable data using a series of algorithms (wellness evaluation data includes wearable sensor data of physical activity [raw sensor data] and processed using digital signal processors having a plurality of programmable processors implementing a plurality of evaluation procedures; Gero, para [0271]-[0272]);
c. extracting wearable-derived physiological biometrics (WDPB) from the results of the digital signal processing algorithms (a plurality of evaluation procedures [extraction algorithms] process subjects sensor data obtained from a wearable device using associated digital signal processors to determine physical parameters of the subject including heartrate [physiological biometrics], wherein the obtained data is extracted and analyzed for evaluating wellness; para Gero, [0208], [0213], [0271]-[0272]);
d. extracting wearable-derived behavioral biometrics (WDBB) from the results of the digital signal processing algorithms (wearable device obtains physical activity of subject to determine behaviors and habits [behavioral biometrics]; Gero, para [0213]; [0488], [0516], [0518]);
e. predicting biological age (wellness evaluation includes estimating age of subject, where the evaluated age of the subject comprises a biological age; Gero, para [0072], [0194], [0411]-[0413]) using WBAPM trained on physiological and behavioral biometrics as input, based on the output models that predict biological age (wellness evaluation includes inputting physical activity and behavior of subject and training a machine learning model to estimate subjects biological age; Gero, para [0399], [0411]-[0413], [0510]) from high-throughput biology data (HBD) through application of the BiologicalAge Fit (BAF) principle (wellness evaluation uses fitness tracker [BAF principle] and biology data of subject such as birthdate and gender [biology data]; Gero, para [0513], [0521]); and
f. providing a user interface, exemplified by a wrist-worn wearable, a mobile device, or a laptop/desktop display, to display results (outputting evaluated age to user through website of the front-end module including a desktop, laptop and mobile device [user interface]; Gero, para [0300], [0500], [0514], and [0517]).
Gero fails to disclose determining biological age and biological age acceleration; however, Konstanz teaches determining biological age and biological age acceleration (determination of the biological age of a human being includes identifying when aging process is accelerated; Konstanz, para [0014], [0050]).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the wellness evaluation system as taught by Gero to include determining biological age and age acceleration as taught by Konstanz with the motivation of enhancing health monitoring and diagnostic systems to more reliably detect underlying conditions leading to disease and providing more robust preventative healthcare (Konstanz, para [0011]).
As per claim 12, Gero and Konstanz teach the invention as claimed, see discussion of claim 11, and further teach:
averaging predictions of biological age over several days to reduce day-to-day variability in BiologicalAge Fit (BAF) based models with low-frequency sampling, facilitating trend analysis on a shorter timescale (wellness evaluation includes processing dataset to reduce dataset [reduce variability] to detect and analyze trends by utilizing models that that sample the dataset in high and low frequency ranges, wherein reducing the data set includes averaging data over shorter timescales such as day to day datasets; Gero, para [0406]-[0409], [0429]-[0433]).
As per claim 13, Gero and Konstanz teach the invention as claimed, see discussion of claim 12, and further teach:
providing daily predictions to offer more frequent estimates of biological age from wearable data compared to repeated sample collection and HBD production for BAF-based biological age prediction (wellness evaluation for determining age includes utilizing wearable device to obtain biology data [HBD production] and fitness analysis [BAF] and processing and sampling the datasets daily; Gero, [0406]-[0409], [0429]-[0433], [0513], [0520]) .
As per claim 14, Gero and Konstanz teach the invention as claimed, see discussion of claim 12, and further teach:
recording additional behavioral biometrics (ABB) and physiological biometrics (APB) from any other applicable IoT device capable of transmitting lifestyle behavioral information (activity and behavior data obtained using smart wearable devices such as smartwatch, pocket smartphone, wristband, headband, knee guard, pair of glasses [IoT devices]; Gero, para [0212]-[0213]).
As per claim 15, Gero and Konstanz teach the invention as claimed, see discussion of claim 14, and further teach:
using a Behavior-Physiology Temporal Causal Analysis (BPTCA) approach to discover statistically significant relationships between lifestyle QCB and subsequent changes in biological age as predicted from wearable device data (wearable device obtains sensor data that is analyzed to predict correlation in biological age with other health indices and lifestyle metrics [statistically significant relationships], wherein the evaluated age is updated [changes in biological age] based on the processed and correlated data; Gero, para [0365], [0380]-[0381], [0488]), with a time delay ranging from one day to one month (wellness evaluation can be performed on a regular basis, for example, each week, or each month; Gero, para [0522]).
As per claim 16, Gero and Konstanz teach the invention as claimed, see discussion of claim 15, and further teach:
Discovering causal relationships between voluntary behavior and wearable-derived biological age on the data of one user at a time, through the aggregation of volumes of longitudinal data on a single user, and sharing personalized insights with said user (user data is voluntary collected for an individual via a wearable device to evaluate biological age and is correlated to reference datasets including a selected population, wherein aggregated characteristics are determined [aggregation of volumes of longitudinal data] and visually output to the user [sharing personalized data]; Gero, para [0212], [0500], [0516]).
As per claim 17, Gero and Konstanz teach the invention as claimed, see discussion of claim 15, and further teach:
discovering candidate causal relationships between voluntary behavior and wearable-derived biological age on the data of a population of users, and extrapolating insights to the behavior recorded for a single user (wellness evaluation includes processing behavior and biological data that is correlated
to a reference population dataset; Gero, para [0195], [0503]-[0504]), to communicate the projected consequences of a user's behavior and provide a feedback mechanism for behavior adjustment (producing recommendations and/or insights into lifestyle or living environment intervention to improve the subject's health; Gero, para [0196], [0518]).
As per claim 21, Gero and Konstanz teach the invention as claimed, see discussion of claim 1, and further teach:
wherein the WBAPM for a particular user is continuously personalized by calibrating it through periodic WBD sample collection (wellness evaluation includes updating samples recorded from the subject to continuously produce evaluation metrics for personalized recommendations; Gero, para [0293], [0488]) and offsetting that difference in the output of the personalized WBAPM (evaluation metrics includes determining differences in datasets and providing datasets to user; Gero, para [0486]-[0487]).
Gero fails to teach determining the difference between WDBAA and EBAA; however, configuring health monitoring systems to process datasets to obtain correlations and differences is a process well known in the art, and Gero teaches obtaining differences between individuals health metrics and a population (Gero, para [0291]), and the specifics of correlating a designed set of metrics such as WDBM and EBM is a matter of mere manipulation of system parameters.
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the wellness evaluation system as taught by Gero to include the desired metrics for correlation and analysis by finding the difference between said desired metrics as taught by Gero with the motivation of providing a more accurate health diagnostic system to detect potential health risks (Gero, para [0008]).
Novelty of Claims
As per claims 7-10 and 18-20, the closest prior art of record, U.S. Patent Application Publication 2019/0365332 to Gero in view of EP 2781602A1 to Konstanz, neither alone nor in combination teach the invention of claims 7-10 and 18-20 in combination with the other claimed limitations from which they depend. Gero teaches a wellness evaluation includes estimating age of subject (para [0194], [0411]-[0413]), wellness evaluation includes processing behavior and biological data that is correlated to a reference population dataset (para [0195], [0503]-[0504]), producing recommendations and/or insights into lifestyle or living environment intervention to improve the subject's health (para [0196], [0518]), producing recommendations and/or insights into lifestyle or living environment intervention to improve the subject's health (para [0196], [0518]), and activity and behavior data obtained using smart wearable devices such as smartwatch, pocket smartphone, wristband, headband, knee guard, pair of glasses (para [0212]-[0213]). Konstanz teaches comparing a user evaluation of biological age with an average value derived from a population (para [0017]), a diagnostic tool for preventive medicine by enabling identification of premature aging (para [0050]), and that determination of the biological age of a human being includes identifying when aging process is accelerated (para [0014], [0050]). But the closest prior art of record does not anticipate or otherwise render indicated dependent claims, in combination with the limitations of claims from which they depend, obvious as rejection of the claimed combination of limitations would require an unreasonable combination of the available prior art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT A SOREY whose telephone number is (571)270-3606. The examiner can normally be reached Monday through Friday, 8am to 5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached at (571) 270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ROBERT A SOREY/ Primary Examiner, Art Unit 3682
