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 Amendment
Applicants amendments filed 10th March 2026 have been entered. Claims 1, 3-12, 14-17, 19-23 & 25-26 are pending with claims 2, 13, 18, & 24 canceled.
Response to Arguments
In response to Applicants arguments and affidavit regarding the rejections under 35 U.S.C. § 112(a):
It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015) (reversing and remanding the district court’s grant of summary judgment of invalidity for lack of adequate written description where there were genuine issues of material fact regarding “whether the specification show[ed] possession by the inventor of how accessing disparate databases is achieved”). If the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention a rejection under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, for lack of written description must be made. See MPEP § 2161.01 I. Applicant’s arguments and affidavit are not persuasive. The rejections applied under 35 U.S.C. § 112(a) in the previous action mailed 11th September 2025 have been maintained.
Applicant’s arguments regarding the rejections under 35 U.S.C. § 101 are as follows:
‘We respectfully disagree. Claims 1 and 12, as amended, comprise the following limitations:
Receiving sensory data of motion by the at least one human subject;
Identifying a plurality of actions from the sensory data;
Classifying the actions to obtain an action type associated with each action;
Determining a plurality of points representing the at least one respective biomechanical parameter for the at least one action type for the subject;
Obtaining a characteristic of the plurality of points as the at least one value characterizing the at least one respective biomechanical parameter; and
Determining whether the at least one value characterizing the at least one respective biomechanical parameter during the second time period are in compliance with the model’
Examiner notes that every single limitation cited by applicant encompasses observations, judgements, evaluations or opinions which are abstract ideas grouped as a mental process involving under the 2019 PEG as annotated in the updated rejection under 101 below.
Applicant argues further, arguing against the idea that the claims do not organize human activity. Examiner notes that the rejection under 101 never stated that this was the case. The rejection under 101 was applied for limitations that contained abstract ideas encompassing mental processes and reciting mathematical relationships, not organizing human activity.
Applicant further argues that the steps cannot be performed in the human mind, then recites verbatim claim language. Examiner disagrees with the Applicant’s assertion that the steps cannot be performed in the human mind. Receiving sensory data (by any known means), identifying actions from data, classifying actions to obtain an action type associated with each action, determining a plurality of points representing at least one biomechanical parameter for at least one action type, obtaining a characteristic of the plurality of points as the at least one value characterizing the at least one respective biomechanical parameter and determining whether the at least one value characterizing the at least one respective biomechanical parameter during the second time period are in compliance are all well within the realm of the human mind involving observations, judgements, evaluations or opinions. See the 101 rejection below, updated to account for amendments.
Applicant further argues that the supposed abstract idea is integrated into a practical application, citing ‘the received sensory data is sensory data of motion of a human subject; and… a plurality of physical actions of the human subject are identified and classified… Claims 10, 11, 22 and 23 further integrate the limitations into a practical application since the user’s contact duration and speed are utilized’. These arguments are not persuasive. The limitations and claims cited by applicant merely further narrow the abstract idea, but a narrow abstract idea is still an abstract idea. See MPEP 2106.04 & 2106.05.
Applicant continues, arguing ‘the unconventional combination of the steps of amended claims 1 and 12 confines the claims to a particular useful application: analyzing physical motion of a human subject’. It is noted that in the Affidavit-traversing rejections or objections rule 132, the Declaration of Dr. Eran Amit under 37 CFR 1.132 dated 10th March 2026, Dr. Eran Amit declared “I have reviewed the below list of amended claims, and it is my opinion that each and every step of these claims could be implemented, and were implemented, with techniques that were very well-known at the time of filing of the PCT application on December 20, 2021”, further citing the amended claim set that is currently pending. It does not appear that the combination of steps in the claims are unconventional by Dr. Eran Amit’s admission.
In response to Applicant’s arguments regarding the rejections under 35 U.S.C. 102:
Applicant argues the motion paths described in Figs. 11A-11B, and Para. [0068-0069], are related to single actions and that this is in contrast to the Applicants limitations of claims 1 & 12. Examiner notes that the paragraphs and figures cited by Applicant were not cited or used in the entirety of the previous office action. The citations in the Examiner’s rejections of the limitations that Applicant is referring to is Para. [0030] of Chang, which cites ‘A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months).’. The current citation meets the claim, as amended, Applicant’s argument is unpersuasive.
Applicant continues, stating that ‘the plurality of points are identified for the action type, as opposed to Chang which at the most uses a plurality of points for identifying the action type.’. This argument is unclear. In regard to the limitation: ‘determining a plurality of points representing the biomechanical parameter for the at least one action type for the subject’ as previously presented in claim 2, to which Examiner believes Applicant is referring, the requirement of the citation is merely to determine a plurality of points that represent the biomechanical parameter for the at least one action type for the subject, thus the citation of Chang: Para. [0036] meets the claim.
Applicant continues, arguing Claims 25 and 26 ‘are further deemed patentable for citing that the parameter is a function of speed. ‘Chang describes no such thing, and only describes single actions that are not based on any functions (see e.g., FIGs. 11A-11C of Chang). Particularly, Chang looks at a sequence of steps at a (roughly) constant speed and derive average parameters describing it, while claims 25 and 26 provide variations of motion, per action type, based on speed.’.
Examiner notes Claim 25 ‘The method of claim 1, wherein the biomechanical parameter is a function of speed’ and Claim 26 ‘The apparatus of claim 12, wherein the biomechanical parameter is a function of speed.’. Examiner directs Applicant to Para. [0051] ‘running use case’ and Para. [0044] & Para. [0057] of Chang, where functions of speed are listed as potential performance features. Applicant’s arguments are not persuasive. See the prior art rejection below, updated to account for amendments.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claim 1, 12 & 14-16 are objected to because of the following informalities:
Claims 1 & 12 ‘wherein obtaining the at least one value characterizing the at least one respective biomechanical parameter, comprises:’ should likely read ‘wherein obtaining the at least one value characterizing the at least one respective biomechanical parameter comprises:’.
Claim 14, ‘the first time period I the uncontrolled environment’ should likely read ‘the first time period in the uncontrolled environment’.
Claims 15 and 16: ‘mounted on’ should read ‘configured to be mounted on’
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
Claims 1, 3-12, 14-17, 19-23 and 25-26 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.
Claims 1, 3-12, 14-17, 19-23 and 25-26 collectively recite the functions of ‘receiving a model associated with a baseline of at least respective one biomechanical parameter of at least one action type of at least one human subject, the model describing the at least one biomechanical parameter during a first time period, wherein the at least one respective biomechanical parameter is based on a continuous independent motion variable having various values’; ‘classifying the actions to obtain an action type associated with each action…’; ‘training the model based on the at least one baseline value, the model describing the baseline of the at least one action type of the subject’; ‘wherein subject to the at least one value being not in compliance with the model, the processor is adapted to: determine that the baseline has changed; and determine a second model to be used instead of the model’; ‘wherein the at least one value characterizing the biomechanical parameter is described analytically as a function of a continuous independent variable’, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this model. For example, How many and what types of layers are there? How is the data propagated? What logics are programmed to help the model make a decision? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
Claims 2-11 and 14-23 & 25-26 are also rejected for being dependent on an independent claim that is rejected under 35 U.S.C. § 112(a).
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, 3-12, 14-17, 19-23 and 25-26 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.
Claims 1, 3, 6, 8, 10, 12, 14, 20 & 22 ‘at least one respective biomechanical parameter’, it is unclear what the at least one respective biomechanical parameter is respective to, rendering the scope of these claims indefinite.
Claim 1, ‘the model describing the at least one biomechanical parameter during a first time period’, there is insufficient antecedent basis for this limitation in this claim.
Claim 1 & 12 ‘classifying the actions to obtain an action type associated with each action;… for the action type for the at least one…”, it is unclear if the underlined terms are referring to the previously recited “plurality of actions” and “at least one action type” as previously recited in claims 1 & 12.
Claims 3, 5, 6, 10, 12, 14, 16 & 22, ‘the subject’, there is insufficient antecedent basis for this limitation in these claims.
Claims 4, 12, 15, 16, ‘the human subject’, there is insufficient antecedent basis for this limitation in these claims.
Claims 3 & 14, ‘a plurality of actions’, it is unclear whether this is referring to the ‘a plurality of actions’ recited in claim 1 & 12 or not, rendering claim 3 & 14 indefinite.
Claims 3 & 14, ‘classifying the actions to obtain an action type associated with each action’, it is unclear if these limitations are referring to ‘at least one action type’ and ‘a plurality of actions’ as previously recited in claim 1 & 12 or not, rendering claim 3 & 14 indefinite.
Claims 3 & 14, ‘the baseline of the at least one action type’, there is insufficient antecedent basis for this limitation in these claims.
Claims 3 & 14 ‘representing at least one respective biomechanical parameter’, it is unclear if this recitation of ‘at least one respective biomechanical parameter is referring to ‘at least one respective biomechanical parameter’ as previously recited in claims 1 & 12 or not, rendering claims 3 & 14 indefinite.
Claims 7 & 19, ‘the baseline’, there is insufficient antecedent basis for this limitation in these claims.
Claims 25-26, ‘the biomechanical parameter’, there is insufficient antecedent basis for this limitation in these claims.
Claims 3-11, 14-17, 19-23 and 25-26 are further rejected for being dependent on an independent claim that is rejected under 35 U.S.C. § 112(b).
Claim Rejections - 35 USC § 101
Section 33(a) of the America Invents Act reads as follows:
Notwithstanding any other provision of law, no patent may issue on a claim directed to or encompassing a human organism.
Claim 12 is rejected under 35 U.S.C. 101 and section 33(a) of the America Invents Act as being directed to or encompassing a human organism. See also Animals - Patentability, 1077 Off. Gaz. Pat. Office 24 (April 21, 1987) (indicating that human organisms are excluded from the scope of patentable subject matter under 35 U.S.C. 101). The claims appear to positively recite ‘the human subject’. An example limitation of this is provided in Claim 12: “receiving sensory data of motion by the human subject”. Seemingly implying the human subject provides the sensory data.
Claims 1, 3-12, 14-17, 19-23 and 25-26 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.
Each of Claims 1, 3-12, 14-17, 19-23 and 25-26 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1, 3-12, 14-17, 19-23 and 25-26 recites at least one step or instruction for receiving sensor data, manipulating sensor data, making determinations based on sensor data, and outputting results based on sensor data, and using a formula to calculate results based on parameters from data, which is grouped as a mental process under the 2019 PEG or a certain method of organizing human activity under the 2019 PEG.
Accordingly, each of Claims 1, 3-12, 14-17, 19-23 and 25-26 recites an abstract idea.
Claim 1:
A computerized method performed by a processor, comprising: receiving a model associated with a baseline of at least one respective biomechanical parameter of at least one action type of at least one human subject (observation), the model describing the at least one biomechanical parameter during a first time period (judgement), wherein the at least one respective biomechanical parameter is based on a continuous independent motion variable having various values; receiving sensory data of motion by the at least one human subject (Observation); based at least in part on the received sensory data, obtaining at least one value characterizing the biomechanical parameter of the at least one action type in an uncontrolled environment during a second time period (observation), the second time period being later than the first time period; determining whether the at least one value characterizing the at least one respective biomechanical parameter during the second time period are in compliance with the model (judgement); and outputting an alert if the at least one value is not in compliance with the model (evaluation/opinion), wherein obtaining the at least one value characterizing the at least one respective biomechanical parameter (Observation), comprises: identifying a plurality of actions of the at least one human subject from the sensory data (Observation); classifying the actions to obtain an action type associated with each action; determining a plurality of points representing the at least one respective biomechanical parameter for the action type for the at least one human subject (Judgement); and obtaining a characteristic of the plurality of points as the at least one value characterizing the at least one respective biomechanical parameter (Observation).
Claim 12:
An apparatus having a processor, the processor being adapted to perform the steps of: receiving a model associated with a baseline of at least one respective biomechanical parameter of at least one action type of at least one human subject (observation), the model describing the at least one respective biomechanical parameter during a first time period (judgement) wherein the at least one respective biomechanical parameter is based on a continuous independent motion variable having various values; receiving sensory data of motion by the human subject (Observation); based at least in part on the received sensory data, obtaining at least one value characterizing the at least one respective biomechanical parameter of the at least one action type in an uncontrolled environment during a second time period (observation), the second time period being later than the first time period; determining whether the at least one value characterizing the at least one respective biomechanical parameter during the second time period are in compliance with the model (judgement); and outputting an alert if the at least one value is not in compliance with the model (evaluation/opinion), wherein obtaining the at least one value characterizing the at least one respective biomechanical parameter (Observation), comprises: identifying a plurality of actions from the sensory data (Observation); classifying the actions to obtain an action type associated with each action (Judgement); determining a plurality of sensory data measurements representing the at least one respective biomechanical parameter for the action type for the subject (Judgement); and obtaining the at least one value characterizing the at least one respective biomechanical parameter as a characteristic of the plurality of sensory data measurements (Observation).
Regarding the dependent claims, the dependent claims are directed to either 1) steps that are also abstract or 2) additional data output that is well-understood, routine and previously known to the industry or 3) further recite additional elements at a high level of generality which are conventional in the art or 4) include reciting mathematical relationships, formulas, equations, or calculations or 5) generally link the use of a judicial exception to a particular technological environment or field of use.
Claims 3-4, 6-9, 13-17, 19-21 recite additional elements at a high level of generality which are conventional in the art
Claims 3, 5-8, 13-14, 19-21 and 25-26 include steps that are also abstract as a mental process through additional data gathering or analysis
Claims 10, 11, 22, and 23 include reciting mathematical relationships, formulas, equations, or calculations
Claims 4, and 15-16 are steps that generally link the use of a judicial exception to a particular technological environment or field of use
Although the dependent claims are further limiting, they do not recite significantly more than the abstract idea. A narrow abstract idea is still an abstract idea and an abstract idea with additional well-known equipment/functions is not significantly more than the abstract idea.
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea.
Step 2A, Prong 2
The above-identified abstract idea in each of independent Claims 1 and 12 (and their respective dependent claims) is not integrated into a practical application under 2019 PEG because the additional elements (identified above in independent Claims 1 and 12), either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the additional elements of: a processor, a model, receiving sensory data, classifying the actions to obtain an action type associated with each action, outputting an alert if the at least one value is not in compliance with the model are generically recited computer elements in independent Claims 1, 12, and 24 (and their respective dependent claims) which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above in independent Claims 1 and 12 (and their respective dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer (e.g., processor as claimed). In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claims 1, 12, and 24 (and their respective dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claims 1 and 12 (and their respective dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 1, 3-12, 14-17, 19-23 and 25-26 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of: A processor, a model, a computer program product, a computer readable storage medium, program instructions, sensors, Inertial Measurement Units, receiving sensory data of motion, determining sensory data measurements, outputting an alert, and training the model as recited in independent Claims 1, 12, and 24 (and their respective dependent Claims).
The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Per Applicant’s specification, A processor ([0118]), a model (Para. [0073-0075]; [0112]), a computer program product (Para. [0010]; [0113]; [0117]; [0120]), a computer readable storage medium (Para. [0114]), program instructions (Para. [0115]), sensors (Para. [0009] ‘Inertial Measurement Units (IMUs) or a motion capture system.’), Inertial Measurement Units ([0009] ‘Inertial Measurement Units (IMUs)’), receiving sensory data of motion (Para. [0009]), determining sensory data measurements (Para. [0009]), outputting an alert (Para. [0040]; [0080]), and training the model (Para. [0040]; [0058-0059]; [0069-0070]; [0075]; [0094-0097]; [0112])
Accordingly, in light of Applicant’s specification, the claimed term processor, model, etc. are reasonably construed as a generic computing device. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the processor, and model. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Claims 1, 3-12, 14-17, 19-23 and 25-26 amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the apparatus’, methods, and computer program product of Claims 1, 3-12, 14-17, 19-23 and 25-26 are directed to applying an abstract idea as identified above on a general purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1, 3-12, 14-17, 19-23 and 25-26 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claims 1, 12, and 24 (and their dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1, 3-12, 14-17, 19-23 and 25-26 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1, 3-12, 14-17, 19-23 and 25-26 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1, 3-12, 14-17, 19-23 and 25-26 are not patent eligible and rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-9, 12, 14-17, 19-21, and 25-26 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20170182360 A1 to Chang et al. (hereinafter, Chang).
Regarding Claim 1, Chang discloses a computerized method performed by a processor (Chang: Abstract; Para. [0029] ‘a computing platform 120’), comprising:
receiving a model (Chang: Para. [0083] ‘..a set of possible target performance signatures.’.) associated with a baseline of at least one respective biomechanical parameter of at least one action type of at least one human subject (Chang: Para. [0029] ‘The system functions to monitor a participant during an activity, produce a performance signature of at least one action performed during the activity,’),
the model describing the at least one biomechanical parameter during a first time period, wherein the at least one respective biomechanical parameter is based on a continuous independent motion variable having various values (Chang: Para. [0048] ‘The kinematic measurements can include acceleration, velocity, displacement, force, angular velocity, angular displacement, tilt/angle, and/or any suitable metric corresponding to a kinematic property or dynamic property of an activity. Other forms of kinematic measurements can be these indicators as a function of time, as a function of a metric changing in time, and/or a comparison or relationship of one or more metrics over time.’);
receiving sensory data of motion by the at least one human subject (Chang: Para. [0032]; [0044] ‘The performance features are preferably measured automatically through one or more sensors attached to the user, sensors attached to equipment or environment, remote sensing elements (such as cameras, 3D scanners, and the like), and/or other suitable elements for the collection of action information’);
based at least in part on the received sensory data obtaining at least one value characterizing the at least one respective biomechanical parameter of the at least one action type in an uncontrolled environment during a second time period, the second time period being later than the first time period (Chang: Para. [0030] ‘A stepping motion, object swinging motion, a kicking motion, a throwing motion, a lifting motion, and other motions are examples, of potential motions. A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months)’; Note: Emphasis added);
determining whether the at least one value characterizing the at least one respective biomechanical parameter during the second time period are in compliance with the model (Chang: Para. [0083] ‘Comparing participants may additionally be used in generating a training recommendation to transition a performance signature towards a second performance signature S146 as shown in FIG. 10, which functions to coach an individual to perform an action more like another athlete or class of athlete. Such training recommendations may help an individual adjust their performance style to approximate a professional athlete or other suitable prototypical athlete. The second performance signature is preferably selected from a set of possible target performance signatures.’; Para. [0037] ‘There can be a performance processing module for comparing performance signatures, a performance processing module for matching performance signatures, a performance processing module for generating training recommendations to transform a first performance signature to a second performance signature, and/or any suitable processing module’); and
outputting an alert if the at least one value is not in compliance with the model (Chang: Para. [0027] ‘In some cases the performance signature can be applied to keep an individual acting within safe parameters. For example, a weight lifting application can use a generated performance signature to warn a user of improper form and/or to recommend when to increase or decrease weight.’; Para. [0084] ‘Deterioration of a performance signature can also be used to identify fatigue and alert a user to help avoid injury in running, golfing and other sports.’),
wherein obtaining the at least one value characterizing the at least one respective biomechanical parameter comprises: identifying a plurality of actions of the at least one human subject from the sensory data (Chang: Para. [0030] ‘A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months).’; [0044] ‘The performance features are preferably measured automatically through one or more sensors attached to the user, sensors attached to equipment or environment, remote sensing elements (such as cameras, 3D scanners, and the like), and/or other suitable elements for the collection of action information’);
classifying the actions to obtain an action type associated with each action (Chang: Para. [0030] ‘activity is used to classify the context of an action. An activity will preferably have at least one action that is monitored. A sport or exercise classification can be a type of activity.’);
determining a plurality of points representing the at least one respective biomechanical parameter for the action type for the at least one human subject (Chang: Chang: Para. [0036] ‘the inertial measurement system(s) 112 can be used in building a motion path reading for one or more points.’); and
obtaining a characteristic of the plurality of points as the at least one value characterizing the at least one respective biomechanical parameter (Chang: Para. [0036] ‘The inertial measurement system(s) 112 can additionally be used in generating biomechanical signals that characterize other aspects of the activity. A biomechanical signal preferably parameterizes a biomechanical-based property of some action by a user. More particularly, a biomechanical signal quantifies at least one aspect of motion that occurs once or repeatedly during an activity.’).
Regarding Claim 3, Chang discloses the method of Claim 1. Chang further discloses wherein the sensory data is obtained during the second time period in the uncontrolled environment (Chang: Para. [0030] ‘A stepping motion, object swinging motion, a kicking motion, a throwing motion, a lifting motion, and other motions are examples, of potential motions. A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months), the method further comprising determining the model, comprising:
identifying a plurality of actions from the sensory data (Chang: Para. [0030] ‘A stepping motion, object swinging motion, a kicking motion, a throwing motion, a lifting motion, and other motions are examples, of potential motions. A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months)’; Note: Emphasis added);
classifying the plurality of actions to obtain an action type associated with each action (Chang: Para. [0030] ‘activity is used to classify the context of an action. An activity will preferably have at least one action that is monitored. A sport or exercise classification can be a type of activity.’);
determining at least one plurality of sensory data measurements representing at least one respective biomechanical parameter of the least one action type for the subject (Chang: Para. [0036] ‘the system and method for a running use-case preferably operate with a set of biomechanical signals that can include ground contact time, braking, pelvic rotation, pelvic tilt, pelvic drop, vertical oscillation of the pelvis, forward oscillation, forward velocity properties of the pelvis, step duration, stride or step length, step impact or shock, and/or foot pronation… the inertial measurement system(s) 112 can be used in building a motion path reading for one or more points.’);
obtaining at least one baseline value characterizing the at least one respective biomechanical parameter as characterizing values for the at least one plurality of sensory data measurements (Chang: Para. [0025] ‘the system and method may determine which of a set of potential target performance signatures most closely corresponds to the patterns of a particular participant, and then use that target performance signature as a reference as the participant trains to improve form.’); and
training the model based on the at least one baseline value, the model describing the baseline of the at least one action type of the subject (Chang: Para. [0052] and [0083]).
Regarding Claim 4, Chang discloses the method of Claim 1. Chang further discloses wherein the sensory data is obtained from at least one sensor mounted on at least one shoe of the human subject (Chang: Para. [0031] ‘The activity monitor device is preferably small enough to be mounted to a participant in an unobtrusive way and may be integrated into a wearable such as a belt, a bracelet, a watch, clothing, shoes, or other articles.’).
Regarding Claim 5, Chang discloses the method of Claim 1. Chang further discloses wherein the method is used for assessing abnormal behavior due to a factor selected from the group consisting of: increase or decrease in physical fitness of the subject; fatigue; injury; a major external variation; and fraud (Chang: Para. [0021]; Para. [0084] ‘Deterioration of a performance signature can also be used to identify fatigue and alert a user to help avoid injury in running, golfing and other sports.’).
Regarding Claim 6, Chang discloses the method of Claim 1. Chang further discloses wherein the method is used for determining that the at least one value characterizing the at least one respective biomechanical parameter are of a different subject than the subject of the model (Chang: Para. [0025] ‘the system and method can be applied to training a user to perform an action in a particular style. This style training can target general performance characteristics, performance characteristics of a group of athletes or for training to be like one individual athlete.’).
Regarding Claim 7, Chang discloses the method of Claim 1. Chang further discloses subject to the at least one value being not in compliance with the model (Chang: Para. [0021]):
determining that the baseline has changed; and determining a second model to be used instead of the model (Chang: Para. [0025]; Para. [0076] ‘when combining the performance features to form a performance signature, previously collected performance features and/or a previous performance signatures can be factored into the generation of an updated performance signature.’).
Regarding Claim 8, Chang discloses the method of Claim 1. Chang further discloses wherein the at least one value characterizing the at least one respective biomechanical parameter is described analytically as a function of a continuous independent variable (Chang: Para. [0044] ‘A subset of performance features can relate to measurements of kinematic properties such as linear or rotational displacements, velocities, and accelerations measured at one or more points.’).
Regarding Claim 9, Chang discloses the method of Claim 8. Chang further discloses wherein the continuous independent variable is at least one item selected from the group consisting of: linear speed, angular velocity, acceleration, deceleration, jump height or kick velocity (Chang: Para. [0044] ‘A subset of performance features can relate to measurements of kinematic properties such as linear or rotational displacements, velocities, and accelerations measured at one or more points.’).
Regarding Claim 12, Chang discloses an apparatus having a processor (Chang: Abstract; Para. [0029] ‘a computing platform 120’), the processor being adapted to perform the steps of:
receiving a model (Chang: Para. [0083] ‘..a set of possible target performance signatures.’.)
associated with a baseline of at least one respective biomechanical parameter of at least one action type of at least one human subject (Chang: Para. [0029] ‘The system functions to monitor a participant during an activity, produce a performance signature of at least one action performed during the activity,’),
the model describing the at least one respective biomechanical parameter during a first time period wherein the at least one respective biomechanical parameter is based on a continuous independent motion variable having various values (Chang: Para. [0048] ‘The kinematic measurements can include acceleration, velocity, displacement, force, angular velocity, angular displacement, tilt/angle, and/or any suitable metric corresponding to a kinematic property or dynamic property of an activity. Other forms of kinematic measurements can be these indicators as a function of time, as a function of a metric changing in time, and/or a comparison or relationship of one or more metrics over time.’);
receiving sensory data of motion by the human subject (Chang: Para. [0032]; [0044] ‘The performance features are preferably measured automatically through one or more sensors attached to the user, sensors attached to equipment or environment, remote sensing elements (such as cameras, 3D scanners, and the like), and/or other suitable elements for the collection of action information’);
based at least in part on the received sensory data, obtaining at least one value characterizing the at least one respective biomechanical parameter of the at least one action type in an uncontrolled environment during a second time period, the second time period being later than the first time period (Chang: Para. [0030] ‘A stepping motion, object swinging motion, a kicking motion, a throwing motion, a lifting motion, and other motions are examples, of potential motions. A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months)’; Note: Emphasis added);
determining whether the at least one value characterizing the at least one respective biomechanical parameter during the second time period are in compliance with the model (Chang: Para. [0083] ‘Comparing participants may additionally be used in generating a training recommendation to transition a performance signature towards a second performance signature S146 as shown in FIG. 10, which functions to coach an individual to perform an action more like another athlete or class of athlete. Such training recommendations may help an individual adjust their performance style to approximate a professional athlete or other suitable prototypical athlete. The second performance signature is preferably selected from a set of possible target performance signatures.’; Para. [0037] ‘There can be a performance processing module for comparing performance signatures, a performance processing module for matching performance signatures, a performance processing module for generating training recommendations to transform a first performance signature to a second performance signature, and/or any suitable processing module’); and
outputting an alert if the at least one value is not in compliance with the model (Chang: Para. [0027] ‘In some cases the performance signature can be applied to keep an individual acting within safe parameters. For example, a weight lifting application can use a generated performance signature to warn a user of improper form and/or to recommend when to increase or decrease weight.’; Para. [0084] ‘Deterioration of a performance signature can also be used to identify fatigue and alert a user to help avoid injury in running, golfing and other sports.’),
wherein obtaining the at least one value characterizing the at least one respective biomechanical parameter comprises: identifying a plurality of actions of the at least one human subject from the sensory data (Chang: Para. [0030] ‘A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months).’; [0044] ‘The performance features are preferably measured automatically through one or more sensors attached to the user, sensors attached to equipment or environment, remote sensing elements (such as cameras, 3D scanners, and the like), and/or other suitable elements for the collection of action information’);
classifying the actions to obtain an action type associated with each action (Chang: Para. [0030] ‘activity is used to classify the context of an action. An activity will preferably have at least one action that is monitored. A sport or exercise classification can be a type of activity.’);
determining a plurality sensory data measurements representing the at least one respective biomechanical parameter for the action type for the subject (Chang: Chang: Para. [0036] ‘the inertial measurement system(s) 112 can be used in building a motion path reading for one or more points.’); and
obtaining the at least one value characterizing the at least one respective biomechanical parameter as a characteristic of the plurality of sensory data measurements (Chang: Para. [0036] ‘The inertial measurement system(s) 112 can additionally be used in generating biomechanical signals that characterize other aspects of the activity. A biomechanical signal preferably parameterizes a biomechanical-based property of some action by a user. More particularly, a biomechanical signal quantifies at least one aspect of motion that occurs once or repeatedly during an activity.’).
Regarding Claim 14, Chang discloses the method of Claim 12. Chang further discloses wherein the sensory data is obtained during the first time period I the uncontrolled environment (Chang: Para. [0030] ‘A stepping motion, object swinging motion, a kicking motion, a throwing motion, a lifting motion, and other motions are examples, of potential motions. A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months)’; Note: Emphasis added), wherein the processor is further adapted to determine the model, comprising:
identifying a plurality of actions from the sensory data (Chang: Para. [0030] ‘A stepping motion, object swinging motion, a kicking motion, a throwing motion, a lifting motion, and other motions are examples, of potential motions. A performance signature can be associated with a single particular action (e.g., the most recent golf swing) but may alternatively be associated with a number of actions (e.g., a golf swing signature for all golf swings in the last 3 months)’; Note: Emphasis added);
classifying the plurality of actions to obtain an action type associated with each action (Chang: Para. [0030] ‘activity is used to classify the context of an action. An activity will preferably have at least one action that is monitored. A sport or exercise classification can be a type of activity.’);
determining at least one plurality of sensory data measurements representing at least one respective biomechanical parameter of the least one action type for the subject (Chang: Para. [0036] ‘the system and method for a running use-case preferably operate with a set of biomechanical signals that can include ground contact time, braking, pelvic rotation, pelvic tilt, pelvic drop, vertical oscillation of the pelvis, forward oscillation, forward velocity properties of the pelvis, step duration, stride or step length, step impact or shock, and/or foot pronation… the inertial measurement system(s) 112 can be used in building a motion path reading for one or more points.’);
obtaining at least one baseline value characterizing the at least one respective biomechanical parameter as characterizing values for the at least one plurality of sensory data measurements (Chang: Para. [0025] ‘the system and method may determine which of a set of potential target performance signatures most closely corresponds to the patterns of a particular participant, and then use that target performance signature as a reference as the participant trains to improve form.’); and
training the model based on the at least one baseline value characterizing the at least one respective biomechanical parameter, the model describing the baseline of the at least one action type of the subject (Chang: Para. [0052] and [0083]).
Regarding Claim 15, Chang discloses the method of Claim 12. Chang further discloses wherein the sensory data is obtained from at least one sensor mounted on at least one shoe of the human subject (Chang: Para. [0031] ‘The activity monitor device is preferably small enough to be mounted to a participant in an unobtrusive way and may be integrated into a wearable such as a belt, a bracelet, a watch, clothing, shoes, or other articles.’).
Regarding Claim 16, Chang discloses the method of Claim 12. Chang further discloses wherein the sensory data is obtained from sensors mounted on at least one shoe of the subject (Chang: Para. [0031] ‘The activity monitor device is preferably small enough to be mounted to a participant in an unobtrusive way and may be integrated into a wearable such as a belt, a bracelet, a watch, clothing, shoes, or other articles.’) and an additional sensor mounted on another location on the human subject (Chang: Para. [0033]).
Regarding Claim 17, Chang discloses the method of Claim 12. Chang further discloses wherein the sensory data is obtained from at least one sensor comprising at least one Inertial Measurement Unit (IMU) or a motion capture system (Chang: Para. [0032] ‘The inertial measurement system 112 preferably includes at least one inertial measurement unit (IMU).’).
Regarding Claim 19, Chang discloses the method of Claim 12. Chang further discloses wherein subject to the at least one value being not in compliance with the model (Chang: Para. [0021]), the processor is further adapted to:
determine that the baseline has changed; and determine a second model to be used instead of the model (Chang: Para. [0025]; Para. [0076] ‘when combining the performance features to form a performance signature, previously collected performance features and/or a previous performance signatures can be factored into the generation of an updated performance signature.’).
Regarding Claim 20, Chang discloses the method of Claim 12. Chang further discloses wherein the at least one value characterizing the at least one respective biomechanical parameter is described analytically as a function of a continuous independent variable (Chang: Para. [0044] ‘A subset of performance features can relate to measurements of kinematic properties such as linear or rotational displacements, velocities, and accelerations measured at one or more points.’).
Regarding Claim 21, Chang discloses the method of Claim 20. Chang further discloses wherein the continuous independent variable is at least one item selected from the group consisting of: linear speed, angular velocity, acceleration, deceleration, jump height or kick velocity (Chang: Para. [0044] ‘A subset of performance features can relate to measurements of kinematic properties such as linear or rotational displacements, velocities, and accelerations measured at one or more points.’).
Regarding Claim 25, Chang discloses the method of claim 1, Chang further discloses wherein the biomechanical parameter is a function of speed (Para. [0032] [0051] [0073] [0074]).
Regarding Claim 26, Chang discloses the apparatus of claim 12, Chang further discloses wherein the biomechanical is a function of speed (Para. [0032] [0051] [0073] [0074]).
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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/SHAWN CURTIS BROUGHTON/Examiner, Art Unit 3791
/PATRICK FERNANDES/Primary Examiner, Art Unit 3791
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