PurePredictive, Inc.

Patent Trials and Appeals Board

Aug 19, 2020

2019002600 (P.T.A.B. Aug. 19, 2020)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
14/162,571 01/23/2014 Kelly D. Phillipps 3128.2.7 6359
36491 7590 08/19/2020
Kunzler Bean & Adamson
50 W. Broadway
Suite 1000
Salt Lake City, UT 84101
EXAMINER
LAMARDO, VIKER ALEJANDRO
ART UNIT PAPER NUMBER
2126
NOTIFICATION DATE DELIVERY MODE
08/19/2020 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
docket@kba.law
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte KELLY D. PHILLIPPS and RICHARD W. WELLMAN
___________

Appeal 2019-0026001
Application 14/162,571
Technology Center 2100
_________________

Before CAROLYN D. THOMAS, JEREMY J. CURCURI, and
JAMES B. ARPIN, Administrative Patent Judges.

ARPIN, Administrative Patent Judge.

DECISION ON APPEAL
Appellant appeals under 35 U.S.C. § 134(a) from the Examiner’s final
rejection of claims 1–3 and 6–22, all of the pending claims. Final Act. 2.2

1 The word “Appellant” refers to “applicant” as defined in 37 C.F.R. § 1.42.
Appellant identifies the real party-in-interest as Pure Predictive, Inc. Appeal
Br. 2.
2 In this Decision, we refer to Appellant’s Appeal Brief (“Appeal Br.,” filed
November 5, 2018) and Reply Brief (“Reply Br.,” filed February 13, 2019);
the Final Office Action (“Final Act.,” mailed June 1, 2018), Advisory Action
(“Adv. Act.,” mailed August 27, 2018), and the Examiner’s Answer (“Ans.,”
mailed December 13, 2018); and the Specification (“Spec.,” filed January
23, 2014). Rather than repeat the Examiner’s findings and determinations
and Appellant’s contentions in their entirety, we refer to these documents.
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Claims 4 and 5 are cancelled. Id. We have jurisdiction under 35 U.S.C.
§ 6(b).
We affirm.
STATEMENT OF THE CASE
Appellant’s claimed methods and apparatus “relate[] to machine
learning and more particularly relates to an action plan generated by
machine learning.” Spec. ¶ 2.
As noted above, claims 1–3 and 6–22 are pending. Claims 1, 17, and
21 are independent. Appeal Br. 11 (claim 1), 14–15 (claim 17), 16–17
(claim 21) (Claims App.). Claim 1 recites, “[a] method for an action plan”
(id. at 11); claim 17 recites, “[a]n apparatus for an action plan, the apparatus
comprising: a machine learning module configured to” perform steps
substantially as recited in claim 1 (id. at 14); and claim 21 recites, “[a]n
apparatus for an action plan, the apparatus comprising” means for
performing the functions as recited in claim 1 (id. at 16). Claims 2, 3, and
6–16 depend directly or indirectly from claim 1; claims 18–20 depend
directly or indirectly from claim 17; and claim 22 depends directly from
claim 21. Id. at 11–17.
Claim 1 is representative.
1. method for an action plan, the method comprising:
simulating multiple different values for one or more non-
actionable features of different instances of data by varying at
least missing values for the one or more non-actionable features,
actual values of the one or more nonactionable features not being
changeable by a user;
processing the different instances of data using machine
learning to produce one or more results, the different instances
of data comprising different values for one or more actionable
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features and the simulated multiple different values for the one
or more non-actionable features;
selecting one or more recommended actions based on the one
or more results, the one or more recommended actions
comprising an action for collecting data associated with at least
the missing values for the one or more nonactionable features,
the action for collecting data specifying additional types of data
to collect for at least the missing values for the one or more
nonactionable features, the additional types of data useable for
optimizing an action plan for actionable features based on
machine learning results produced using the collected additional
types of data; and
providing an action plan associated with the one or more
recommended actions.
Id. at 11.
REJECTION
The Examiner rejects claims 1–3 and 6–22 under 35 U.S.C. § 101, as
directed to patent ineligible subject matter without significantly more.3
Final Act. 2–6. We conduct a limited de novo review of the appealed
rejection for error based upon the issues identified by Appellant and in light
of the arguments and evidence produced thereon. Ex parte Frye, 94
USPQ2d 1072, 1075 (BPAI 2010) (precedential). Arguments not made are
waived. See 37 C.F.R. § 41.37(c)(1)(iv). Unless otherwise indicated, we
adopt the Examiner’s findings in the Final Action and the Answer as our
own and add any additional findings of fact for emphasis. For the reasons
given below, we affirm the Examiner’s rejection.

3 The Examiner rejected claims 21 and 22 as indefinite. Final Act. 6–9.
The Examiner has withdrawn that rejection. Ans. 3.
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ANALYSIS
Patent Ineligible Claims
A. Section 101
An invention is patent-eligible if it claims a “new and useful process,
machine, manufacture, or composition of matter.” 35 U.S.C. § 101.
However, the U.S. Supreme Court has long interpreted 35 U.S.C. § 101 to
include implicit exceptions: “[l]aws of nature, natural phenomena, and
abstract ideas” are not patentable. Alice Corp. Pty. Ltd. v. CLS Bank Int’l,
573 U.S. 208, 216 (2014).
In determining whether a claim falls within an excluded category, we
are guided by the Court’s two-part framework, described in Mayo and Alice.
Id. at 217–18 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc.,
566 U.S. 66, 75–77 (2012)). In accordance with that framework, we first
determine what concept the claim is “directed to.” See Alice, 573 U.S. at
219 (“On their face, the claims before us are drawn to the concept of
intermediated settlement, i.e., the use of a third party to mitigate settlement
risk.”); see also Bilski v. Kappos, 561 U.S. 593, 611 (2010) (“Claims 1 and 4
in petitioners’ application explain the basic concept of hedging, or protecting
against risk.”). According to the Court, concepts determined to be abstract
ideas and, thus, patent ineligible, include certain methods of organizing
human activity, such as fundamental economic practices (Alice, 573 U.S. at
219–20; Bilski, 561 U.S. at 611); mathematical formulas (Parker v. Flook,
437 U.S. 584, 594–95 (1978)); and mental processes (Gottschalk v. Benson,
409 U.S. 63, 67 (1972)).
In Diamond v. Diehr, the claim at issue recited a mathematical
formula, but the Court held that “a claim drawn to subject matter otherwise
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statutory does not become nonstatutory simply because it uses a
mathematical formula.” Diamond v. Diehr, 450 U.S. 175, 187 (1981).
Having said that, the Court also indicated that a claim “seeking patent
protection for that formula in the abstract . . . is not accorded the protection
of our patent laws, . . . and this principle cannot be circumvented by
attempting to limit the use of the formula to a particular technological
environment.” Id. at 191 (citing Benson and Flook). Nevertheless, the
Court noted that “[i]t is now commonplace that an application of a law of
nature or mathematical formula to a known structure or process may well be
deserving of patent protection.” Id. at 187; see also BASCOM Glob. Internet
Servs., Inc. v. AT&T Mobility LLC, 827 F.3d 1341, 1352 (Fed. Cir. 2016)
(Even if the individual components were known, “an inventive concept can
be found in the ordered combination of claim limitations that transform the
abstract idea of filtering content into a particular, practical application of
that abstract idea.” (emphasis added)).
If the claim is “directed to” an abstract idea, we next “must examine
the elements of the claim to determine whether it contains an ‘inventive
concept’ sufficient to ‘transform’ the claimed abstract idea into a patent-
eligible application.” Alice, 573 U.S. at 221. “A claim that recites an
abstract idea must include ‘additional features’ to ensure ‘that the [claim] is
more than a drafting effort designed to monopolize the [abstract idea].’” Id.
(quoting Mayo, 566 U.S. at 77). “[M]erely requir[ing] generic computer
implementation[] fail[s] to transform that abstract idea into a patent-eligible
invention.” Id.
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B. Office Patent Eligibility Guidance
In an effort to achieve clarity and consistency in how the Office
applies the Court’s two-part framework, the Office published revised
guidance on the application of 35 U.S.C. § 101. 2019 Revised Patent
Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019).4 In
Step One of our analysis, we look to see whether the claims fall within one
of the four statutory categories identified in 35 U.S.C. § 101. Id. at 53
(“Examiners should determine whether a claim satisfies the criteria for
subject matter eligibility by evaluating the claim in accordance with the
criteria discussed in MPEP 2106, i.e., whether the claim is to a statutory
category (Step 1) and the Alice/Mayo test for judicial exceptions (Steps 2A
and 2B).[5]”).
Under the guidance, we then look to whether the claim recites:
(1) Step 2A — Prong One: any judicial exceptions, including
certain groupings of abstract ideas (i.e., mathematical concepts,
certain methods of organizing human activity, such as a
fundamental economic practice, or mental processes); and
(2) Step 2A — Prong Two: additional elements that integrate
the judicial exception into a practical application (see MPEP
§ 2106.05(a)–(c), (e)–(h)).

4 “All USPTO personnel are, as a matter of internal agency management,
expected to follow the guidance.” 2019 Revised Patent Subject Matter
Eligibility Guidance, 84 Fed. Reg. at 51; see also October 2019 Update:
Subject Matter Eligibility, 2 (October 17, 2019) (“Note, the feedback
received was primarily directed to examination procedures and, accordingly,
this update focuses on clarifying practice for patent examiners. However, all
USPTO personnel are expected to follow the guidance.”).
5 All Manual of Patent Examining Procedure (“MPEP”) citations herein are
to MPEP, 9th Ed. Rev. 10.2019, June 2020.
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See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg.
at 54–55 (“Revised Step 2A”).
Only if a claim (1) recites a judicial exception and (2) does not
integrate that exception into a practical application, do we then look to
whether the claim:
(3) adds a specific limitation beyond the judicial exception that
is not “well-understood, routine, conventional” in the field (see
MPEP § 2106.05(d)); or
(4) simply appends well-understood, routine, conventional
activities previously known to the industry, specified at a high
level of generality, to the judicial exception.
See id. at 56 (“Step 2B: If the Claim Is Directed to a Judicial Exception,
Evaluate Whether the Claim Provides an Inventive Concept.”).
C. Step One — Claims Directed to Statutory Category
Independent claims 1 and its associated dependent claims are directed
to a method, i.e., a process; and each of independent claims 17 and 21 and
their associated dependent claims is directed to an apparatus, i.e., a machine.
Appeal Br. 11–17 (Claims App.). The Examiner finds that each of claims 1–
3 and 6–22 is directed to a recognized statutory category. Final Act. 2.
D. Two-Part Alice/Mayo Framework
1. Step 2A, Prong One — Claims Recite an Abstract Idea
Applying the first part of the Alice/Mayo framework (Step 2A), the
Examiner finds, “[e]xemplary claims 1, 17, and 21 are directed to the
abstract idea of analyzing collected data to provide an action plan. This is
similar to other ideas found to be abstract by various courts, such as
collecting information, analyzing it, and displaying certain results of the
collection and analysis [(Electric Power Group, LLC v. Alstom, S.A., 830
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F.3d 1350, 1356 (Fed. Cir. 2016))].” Final Act. 3. Thus, the Examiner finds
that the independent claims recite a mental process. 2019 Revised Patent
Subject Matter Eligibility Guidance, 84 Fed. Reg. at 52 (“Mental
processes—concepts performed in the human mind (including an
observation, evaluation, judgment, opinion).”); see also October 2019
Update: Subject Matter Eligibility at 7 (citing Electric Power Group).
The claims generally recite processing data involving values for at
least one non-actionable and at least one actionable feature to select at least
one recommended data collecting action, and providing an action plan
associated with the at least one recommended action. See e.g., Appeal
Br. 11 (Claims App.).
An actionable feature, as used herein, comprises a feature which
a user may impact, change, or affect, such as a size of a target
set, an amount spent on an action, a timing for an action, a
location for an action, a product for an action, or the like. A non-
actionable feature, as used herein, comprises a feature which a
user cannot directly impact, change, or affect, such as the gender
of a customer, the zip code of a residence, the cost of a
component from a supplier, or the like.
Spec. ¶ 88. In particular, the method of claim 1 recites the steps of:
(1) simulating multiple different values for a non-actionable feature of
different instances of data by varying at least the missing values for the non-
actionable feature; (2) processing the different instances of data to produce a
result, the different instances of data comprising different values for an
actionable feature and the simulated multiple different values for the non-
actionable feature; (3) selecting a recommended action based on the result,
the recommended action comprising collecting data associated with the
missing values for the non-actionable feature, the additional data useable for
optimizing an action plan for the actionable feature using the collected
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additional data; and (4) providing the action plan based on the recommended
action. See e.g., Appeal Br. 11 (Claims App.); see also Final Act. 3
(analyzing claim limitations). Claims 17 and 21 recite corresponding
limitations. Appeal Br. 14–17 (Claims App.).
Appellant contends the Examiner fails to identify: (1) the abstract
idea grouping that the claims recite; and (2) the specific limitations that
recite the abstract idea. Reply Br. 3. Nevertheless, the Examiner finds, “the
claim is essentially directed to analyzing collected data to provide an action
plan.” Final Act. 3. The Office groups collecting information, analyzing it,
and displaying certain results of the collection and analysis within mental
processes. October 2019 Update: Subject Matter Eligibility at 7. Further,
the Examiner identifies the claim limitations, which support the finding that
these claims fall within this grouping. Final Act. 3.
In addition, Appellant contends that the claims do “not recite a mental
process because the steps are not practically performed in the human mind.”
Reply Br. 4. However, the Office notes:
The courts have found claims requiring a generic computer or
nominally reciting a generic computer may still recite a mental
process even though the claim limitations are not performed
entirely in the human mind.
. . . .
By way of example, examiners may review the specification to
determine if the underlying claimed invention is described as a
concept that is performed in the human mind and applicant is
merely claiming that concept performed 1) on a generic
computer, 2) in a computer environment or 3) is merely using a
computer as a tool to perform the concept.
October 2019 Update: Subject Matter Eligibility at 8. Here, although the
claims recite that the processing may be achieved by “machine learning,” the
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Specification discloses
the action plan module 102 provides and/or accesses a machine
learning framework allowing the action plan module 102 and/or
clients 104 to request machine learning ensembles or other
predictive programs, to make analysis requests, and to receive
machine learning results, such as a classification, a confidence
metric, an inferred function, a regression function, an answer, a
prediction, a recognized pattern, a rule, a recommendation, or
other results. Machine learning, as used herein, comprises one
or more modules, computer executable program code, logic
hardware, and/or other entities configured to learn from or train
on input data, and to apply the learning or training to provide
results or analysis for subsequent data.
Spec. ¶ 46. Thus, we are persuaded that the recitation of machine learning
merely describes the use of machine leaning as a tool for performing the
analysis or the environment in which the analysis is performed.
We determine that the claims recite a mental process, including
observation, evaluation, judgment, and opinion, which is an abstract idea.
2. Step 2A, Prong Two — Abstract Idea Not Integrated Into Practical
Application
Under the Office’s Guidance, having determined that the claims recite
an abstract idea, we now determine if additional elements in the claims
integrate the identified abstract idea into a practical application. See MPEP
§§ 2106.05(a)–(c), (e)–(h). Thus, we look to see whether the “additional
elements” impose a meaningful limit on the identified abstract idea. See
October 2019 Update: Subject Matter Eligibility at 11.
Claim 1, as well as claims 17 and 21, expressly recites simulating,
processing, and collecting “data,” using “machine learning,” and providing
an action plan. See e.g., Appeal Br. 11 (Claims App.). Claim 17 further
recites “[a]n apparatus” comprising “a machine learning module” for
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accomplishing the operations as recited in claim 1. Id. at 14. Although the
claims describe the methods and apparatus without specific references to
hardware and/or software components, the Specification discloses various
generic computer hardware and/or software components to accomplish the
recited operations. Spec. ¶¶ 27–33, 35–39. In particular, the Specification
explains,
the action plan module 102 provides and/or accesses a machine
learning framework allowing the action plan module 102 and/or
clients 104 to request machine learning ensembles or other
predictive programs, to make analysis requests, and to receive
machine learning results, such as a classification, a confidence
metric, an inferred function, a regression function, an answer, a
prediction, a recognized pattern, a rule, a recommendation, or
other results. Machine learning, as used herein, comprises one
or more modules, computer executable program code, logic
hardware, and/or other entities configured to learn from or train
on input data, and to apply the learning or training to provide
results or analysis for subsequent data.
Id. ¶ 46 (emphasis added). The Specification describes machine learning
utilizing known techniques. See id. ¶¶ 63–65. Thus, we are persuaded that
the claimed methods and apparatus employ generic computer components
performing generic computer functions. Final Act. 3; see Ans. 3–4.
Therefore, considered individually or as an ordered combination, we are not
persuaded that these components recite a particular machine. See MPEP
§ 2106.05(b); see also 2019 Revised Patent Subject Matter Eligibility
Guidance, 84 Fed. Reg. at 55 n.27.
Further, applying the second part of the Alice/Mayo framework,6 the
Examiner finds “[t]he claims recite the use [of] machine learning as mere

6 We acknowledge that some of the considerations at Step 2A, Prong Two,
properly may be evaluated under the second part of the Alice/Mayo
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instructions to implement an abstract idea on a computer.” Final Act. 11;
see MPEP § 2106.05(f); 2019 Revised Patent Subject Matter Eligibility
Guidance, 84 Fed. Reg. at 55 n.30.
In addition, the Examiner finds:
The claims do recite that the method is computer-implemented.
However, this is merely a generic computer implementation that
does not amount to significantly more. Looking at the limitations
as an ordered combination adds nothing that is not already
present when looking at the elements taken individually. There
is no indication that the combination of elements improves the
functioning of a computer or improves another technology.
Their collective functions merely provide conventional computer
implementations.
Final Act. 3; see Adv. Act. 2; Ans. 3–5.
Appellant disagrees and contends,
the claimed solution describes a specific improvement to
machine learning and predictive analytics computing
technology. The improvement is directed to optimizing machine
learning technology to generate an action plan for one or more
recommended actions associated with actionable and non-
actionable features. For instance, as recited in the claimed
solution, the action plan may be for a recommendation for
“collecting data associated with at least the missing values for
the one or more non-actionable features,” and the action for
collecting data may specify “additional types of data to collect
for at least the missing values for the one or more non-actionable
features,” which may be used “for optimizing an action plan for
actionable features based on machine learning results produced
using the collected additional types of data.” In other words, the

framework (Step 2B of the Office guidance). See Final Act. 3, 10–12;
Ans. 3–7. For purposes of maintaining consistent treatment within the
Office, we evaluate those considerations under the first part of the
Alice/Mayo framework (Step 2A of the Office guidance). See 2019 Revised
Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. at 55 nn.25, 27–32.
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improvement is directed to continuously optimizing the action
plan for actionable features using machine learning, e.g., by
teaching computers to analyze data and predict results without
user input, by collecting additional data of the recommended
types for at least the missing values for the non-actionable
features.
Appeal Br. 5–6; see Reply Br. 4–5. We are not persuaded by Appellant’s
contentions.
First, as noted above, the Specification makes clear known techniques
of machine learning and predictive analytics are employed in the claimed
methods and apparatus. See Spec. ¶¶ 46, 63–65. The alleged improvement
is merely recommending missing data for collection and using that data to
provide an action plan by known techniques. Here the recommendations for
additional data collection are selected through the black box of “machine
learning.” See Reply Br. 5 (quoting Spec. ¶¶ 45, 46). There is nothing
amounting to a technological improvement in using different data to produce
a different plan.
Second, the use of computer hardware and/or software components to
optimize the processing of data may improve the abstract idea, but, in this
context, is not a technological improvement. Appeal Br. 5; see Intellectual
Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367 (Fed. Cir.
2015) (“[C]laiming the improved speed or efficiency inherent with applying
the abstract idea on a computer [does not] provide a sufficient inventive
concept.” (emphasis added)); Bancorp Servs., L.L.C. v. Sun Life Assur. Co.
of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012) (“[T]he fact that the
required calculations could be performed more efficiently via a computer
does not materially alter the patent eligibility of the claimed subject matter.”
(emphasis added)); see also Synopsys, Inc. v. Mentor Graphics Corp., 839
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F.3d 1138, 1151 (Fed. Cir. 2016) (“[A] new abstract idea is still an abstract
idea.”). Considered individually, the additional elements do not recite an
improvement to computer technology. Ans. 3–5; cf. DDR Holdings, LLC v.
Hotels.com, L.P., 773 F.3d. 1245 (Fed. Cir. 2014) (“Instead, the claimed
solution is necessarily rooted in computer technology in order to overcome a
problem specifically arising in the realm of computer networks.”); Enfish,
LLC v. Microsoft Corp., 822 F.3d 1327, 1333 (Fed. Cir. 2016) (“The patents
teach that multiple benefits flow from this design. First, the patents disclose
an indexing technique that allows for faster searching of data than would be
possible with the relational model. Second, the patents teach that the self-
referential model allows for more effective storage of data other than
structured text, such as images and unstructured text. Finally, the patents
teach that the self-referential model allows more flexibility in configuring
the database.”). Nor do the additional elements, considered as an ordered
combination, improve the technology employed to select the recommended
action or to provide the action plan. Cf. BASCOM, 827 F.3d at 1350
(“According to BASCOM, the inventive concept harnesses this technical
feature of network technology in a filtering system by associating individual
accounts with their own filtering scheme and elements while locating the
filtering system on an ISP server.”). Unlike DDR Holdings, Enfish, and
BASCOM, the limitations of the pending claims, individually or as an
ordered combination, improve the action plan, not the technology involved
in providing it. Ans. 3–6.
Other than identifying, collecting, and processing different data and
using computer hardware and/or software components to optimize the
processing, Appellant does not adequately explain “how the claim
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limitations are rooted in computer technology, and how the claim limitations
are solving a technical problem that only arises in machine learning
technology.” Adv. Act. 2. Thus, we agree with the Examiner that “[t]he
claims are not rooted in machine learning technology, and the claims do not
solve a technical problem that only arises in machine learning technology.”
Id.; see MPEP § 2106.05(a); 2019 Revised Patent Subject Matter Eligibility
Guidance, 84 Fed. Reg. at 55 n.25.
Appellant does not contend that the pending claims recite a
transformation or reduction of a particular article to a different state or thing
or other meaningful limitations beyond generally linking the use of the
abstract idea to a particular technological environment. Such contentions are
waived.
In view of Appellant’s claim recitations and the Specification’s
disclosure, and consistent with the Examiner’s findings, we are persuaded
the rejected claims do not recite:
(i) an improvement to the functioning of a computer;
(ii) an improvement to another technology or technical field;
(iii) an application of the abstract idea with, or by use of, a
particular machine;
(iv) a transformation or reduction of a particular article to a
different state or thing; or
(v) other meaningful limitations beyond generally linking the
use of the abstract idea to a particular technological
environment.
See MPEP § 2106.05(a)–(c), (e)–(h); see also Ans. 7 (discussing MPEP
§§ 2106.05(b) and 2106.05(f))). Thus, we are persuaded the additional
elements of the rejected claims do not integrate the identified abstract idea
into a practical application and the claims are directed to an abstract idea.
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3. Step 2B — Not Significantly More Than the Abstract Idea
Because we determine that the claims recite an abstract idea and do
not integrate that abstract idea into a practical application, we now consider
whether the claims include additional limitations, such that the claims
amount to significantly more than the abstract idea. Applying the second
part of the Alice/Mayo framework, the Examiner finds:
Claims 1, 17, and 21 do appear to recite additional elements that
would be analyzed under the second part of the Mayo test, these
additional elements are hardware circuits, programmable
hardware devices, and non-transitory computer readable storage
media. All of the claimed steps are directed towards the abstract
idea described above. The claims do recite that the method is
computer-implemented. However, this is merely a generic
computer implementation that does not amount to significantly
more. Looking at the limitations as an ordered combination adds
nothing that is not already present when looking at the elements
taken individually. There is no indication that the combination
of elements improves the functioning of a computer or improves
another technology. Their collective functions merely provide
conventional computer implementations.
Final Act. 3; see Ans. 6–7.
Appellant contends that the Examiner fails to provide sufficient
evidence that these elements are well-understood, routine, and conventional
to a skilled artisan, as required by our reviewing court in Berkheimer v. HP
Inc., 881 F.3d 1360 (Fed. Cir. 2018). Appeal Br. 7–9; Reply Br. 5–6.
Nevertheless, as the Office explains, a finding that additional elements are
well-understood, routine, and conventional may be supported by:
A citation to an express statement in the specification . . . that
demonstrates the well-understood, routine, conventional nature
of the additional element(s). A specification demonstrates the
well-understood, routine, conventional nature of additional
elements when it describes the additional elements as well-
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understood or routine or conventional (or an equivalent term),
as a commercially available product, or 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).
USPTO Memorandum of April 19, 2018, “Changes in Examination
Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter
Eligibility Decision (Berkheimer v. HP, Inc.)” 3–4 (Apr. 19, 2018)
(emphasis added; (hereinafter the “Berkheimer Memorandum”)). 7
Here, the Specification explains, “the disclosure may be practiced
without one or more of the specific details, or with other methods,
components, materials, and so forth. In other instances, well-known
structures, materials, or operations are not shown or described in detail to
avoid obscuring aspects of the disclosure.” Spec. ¶ 35 (emphasis added).
For the reasons discussed here and above, we are persuaded that the
Specification adequately demonstrates that the additional limitations of the
claimed methods and apparatus are well-understood, conventional, and
routine. See, e.g., Spec. ¶¶ 27–33, 35–39, 46, 63–65; see also id. ¶¶ 128–
130 (describing data collection).
On this record, we agree with the Examiner that independent claim 1,
as well as independent claims 17 and 21, is directed to an abstract idea and
fails to recite “significantly more” than the identified abstract idea. Thus,
we are not persuaded that the Examiner errs in determining that the
independent claims are patent-ineligible, and we sustain the rejection of
claims 1, 17, and 21.

7 Available at https://www.uspto.gov/sites/default/files/documents/memo-
berkheimer-20180419.PDF.
Appeal 2019-002600
Application 14/162,571

18

E. Remaining Claims
As noted above, each of claims 2, 3, 6–16, 18–20, and 22 depends
directly or indirectly from independent claim 1, 17, or 21. As noted above,
Appellant challenges the rejection of dependent claims 2, 3, 6–16, 18–20,
and 22 for the same reasons as their base claims. Because we are not
persuaded the Examiner errs with respect to the patent ineligibility rejection
of claim 1, 17, or 21, we also are not persuaded the Examiner errs with
respect to the rejection of claims 2, 3, 6–16, 18–20, and 22. For this reason,
we also sustain the rejection of those claims.
DECISION
1. The Examiner does not err in rejecting claims 1–3 and 6–22 under
35 U.S.C. § 101, as directed to patent-ineligible subject matter without
significantly more.
2. Thus, on this record, claims 1–3 and 6–22 are not patent eligible.
CONCLUSION
We affirm the Examiner’s rejection of claims 1–3 and 6–22.
In summary:
Claims Rejected 35 U.S.C. § Basis Affirmed Reversed
1–3, 6–22 101 Eligibility 1–3, 6–22
No time for taking any action connected with this appeal may be
extended under 37 C.F.R. § 1.136(a)(1).

AFFIRMED