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 1 is amended. Claims 1-7 are pending.
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 1-7 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 1-7 are drawn to a method for estimating fitness scores from data associated with a wearable device which is within the four statutory categories (i.e. process).
Claim 1 of recites a method of estimating fitness scores from data associated with a wearable device comprising:
receiving user profile data comprising:
age, gender, weight, height and body mass index;
extracting sensor data, which includes bioelectrical impedance analysis (BIA) data, exercise session data and activity level data;
obtaining a data set of sensor data features and respective performance on tests for health-related physical fitness (HRPF) domains, including: muscular endurance, muscular strength, flexibility, body composition and cardiorespiratory;
normalizing training of the data set by subtracting a mean and dividing by a standard deviation of each feature;
obtaining a prediction model for each HRPF domain that is different by training machine learning algorithms, one for each domain, using the normalized data set; and
obtaining predictions for a new data instance by:
a) normalizing a new data feature vector by subtracting the mean and dividing by the standard deviation of each variable in a training set;
b) applying different regression models with source-dependent feature selection and latent variable projection corresponding to each domain based on sensor data extract for the new data instance and obtaining a prediction for each domain; and
c) normalizing each prediction by a distribution corresponding to age and sex of the new data instance,
wherein the method performs source-dependent input of each type of source of the sensor data into the prediction model obtained in correspondence with each HRPF domain and outputs a comprehensive description of estimated fitness scores as a multidimensional representation of fitness status associated with the user profile.
The bolded limitations, given the broadest reasonable interpretation, cover a mathematical concept and/or a certain method of organizing human activity because they recite mathematical relationships, formulas, equations, and/or mathematical calculations and/or fundamental economic practices, commercial or legal interactions, and/or managing personal behavior or relationships or interactions between people. Any limitations not identified above as part of abstract idea are underlined and are deemed “additional elements,” and will be discussed in further detail below.
Dependent Claims 2-7 include other limitations, for example Claim 2 recites wherein the extracting of sensor data further comprises obtaining a most recently valid value within 30 days for VO2max and bioelectrical impedance; temporally aggregating activity level data by performing multiple aggregations across different time scales; and temporally aggregating exercise session data features by performing multiple aggregations across different time scales, Claim 3 recites wherein based on VO2Max data being unavailable, estimating the VO2Max data according to an equation as follows: VO2-max = 79.9 - (0.39 X Age) - (13.7 X Gender[0 = male, 1 = female]) - (0.127 X
Weight[lbs]), Claim 4 recites wherein the sensor data from the wearable device is an input and user performance on HRPF tests are ground truth for the prediction model, Claim 5 recites wherein the obtaining of the prediction model for each HRPF domain by training machine learning algorithms further comprises: source-dependent feature selection, in which bioelectrical impedance analysis (BIA), pedometry, calorie, and exercise session data features are dropped based on their Pearson correlation being lower than a threshold, and temporal features are further subject to selection of an aggregation with largest correlation; source-dependent latent projection, in which profile data, BIA, activity level data and exercise session data forwarded by source-dependent feature selection are subject to their respective Principal Component Analysis (PCA) projection, wherein a smallest subset of vectors representing a given proportion of a variance in the training set is preserved; and linear regressions on features transformed via source- dependent latent projection, where muscular endurance domain employs Poisson regression, and remaining domains employ Lasso regression, Claim 6 recites wherein the normalization of a prediction further comprises: obtaining percentiles of a target variable, according to American College of Sports Medicine (ACSM) , for the age and sex of the predicted respective instance; and for each domain, calculating multiple health-related physical fitness domains' scores of the prediction by subtracting a lowest percentile and dividing by a difference between a highest and lowest percentile, wherein the normalization of f(x) follows:
f(x) = 100 x-PL% ,
PH%-PL%
P where x is a value to be normalized, PL% and PH% are the percentiles of a group-specific distribution, L and H are defined by ACSM guidelines for each domain, Claim 7 requires displaying, on a display of the wearable device, a simultaneous depiction of multiple health-related physical fitness domains' scores, but these only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent Claim 1.
Furthermore, Claims 1-7 are not integrated into a practical application because the additional elements (i.e. the limitations not identified as part of the abstract idea) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of a display of a wearable device, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see paragraphs [0028] of the present Specification, see MPEP 2106.05(f).
Furthermore, the Claims do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because, the additional elements (i.e. the elements other than the abstract idea) amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
paragraphs [0028] of the Specification discloses that the additional elements (i.e. smartwatch) comprise a plurality of different types of generic computing systems or off the shelf devices that are configured to perform generic computer functions
Dependent Claims 2-7 include other limitations, but none of these functions are deemed significantly more than the abstract idea because the additional elements recited in the aforementioned dependent claims similarly represent no more than elements recited at an apply it level (the display of the wearable device feature of Claim 7).
Thus, taken alone, the additional elements do not amount to “significantly more” than the above-identified abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, Claims 1-7 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's arguments filed 08/16/2026 have been fully considered. Examiner notes that the claims are free from prior art rejections.
REJECTION UNDER 35 U.S.C. § 101
Applicant asserts that claim 1 does not recite an abstract idea as it “performs source-dependent projections which enables data from corresponding sources that has different characteristics to be handled for the estimation” and that “source-dependent input of each type of source of the sensor data into the prediction model obtained in correspondence with each HRPF domain and outputs a comprehensive description of estimated fitness scores as a multidimensional representation of fitness status associated with the user profile (Remarks, page 5).” Examiner maintains that this is part of the abstract idea and it is using profile data and extracted sensor data, which is run through various models, to output a comprehensive description of estimated fitness scores. The claimed invention is directed towards creating an overall fitness status of a user (Specification [0001]).
With respect to Step 2A, Prong 2, Applicant asserts that “claim 1 currently recites processes that, both individual and as an ordered combination, are integrated into a practical application…of [a] wearable device that provides estimated fitness scores (Remarks, page 6).” The independent claim does not recite any additional elements to be considered “either individually or in an order combination.” The abstract idea cannot be used to integrate itself into a practical application.
The wearable device is not positively recited in claim 1. Claim 1 does not recite any additional elements, and therefore, there is nothing to integrate the abstract idea into practical application. Rather, the claim requires using data from the wearable device to calculate an estimated fitness score. Even if the display was positively recited (such as claim 7 reciting “on a display of a wearable device”), it is recited at an “apply it” level, and is not improved as a result of the claimed invention. It is merely used for its intended purpose which is to collect the user’s fitness data.
Therefore, the claims remain rejected as being directed towards an abstract idea without a practical application or significantly more.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rachelle Reichert whose telephone number is (303)297-4782. The examiner can normally be reached M-F 9-5 MT.
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/RACHELLE L REICHERT/Primary Examiner, Art Unit 3686
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