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 .
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “100” has been used to designate both the method depicted in Fig. 2 and the individual step of the same method of “Learning” [the Examiner notes that at least ¶0049 of the Specification refers to the method depicted in Fig. 2 as “inference method 1”; Fig. 1 also uses reference character “1” to refer to the method].
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: reference character “20 c” [Applicant’s Specification ¶0110].
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claim(s) 1-2, 10, and 21-22 is/are objected to because of the following informalities:
Claim 1 should read “[[the]] a plantar pressure line of the individual’s foot” [lines 14-15].
Claim 2 should read “[[the]] a plantar pressure line inferred from several stance phases” [lines 3-4].
Claim 10 should read “The method for inferring a[lines 1-2].
Claim(s) 21 is/are objected to under 37 CFR 1.75 as being a substantial duplicate of claim(s) 12. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim 22 should read “[[the]] a plantar pressure line of the individual’s foot” [lines 11-12].
Claim 22 should read “the [[model]] correlation model” [line 13].
Appropriate correction is required.
Claim Interpretation
Examiner Notes: currently, NO limitation invokes interpretation under § 112(f).
Claim Rejections - 35 USC § 112
Examiner’s Note Regarding Machine Learning: the claimed machine learning model of claim(s) 10 and 18 was considered under § 112(a), wherein the Examiner notes that the disclosure of machine learning [Applicant’s Specification ¶¶0063-0064, 0090-0091] of the Applicant’s Specification is considered to provide sufficient written description support for the machine learning model as presently claimed for one of ordinary skill in the art to understand that the Applicant possessed the instant invention at the time of filing.
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.
Claim(s) 2 and 13 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 recites the limitation “wherein the inferring step is repeated so as to establish the plantar pressure line inferred from several stance phases” [lines 2-4], which is considered indefinite, as the inferring step as defined in claim 1 specifically refers to the inferring being based on “the angle values calculated over the at least two instants of the stance phase of the foot” [lines 15-16 of claim 1], such that it is unclear how the inferring step may be repeated using the same data to establish a plantar pressure line inferred from “several stance phases”, without providing additional language to modify what data is used in the inferring step. For examination purposes, the Examiner has interpreted the “plantar pressure line inferred from several stance phases” to be based on angle values calculated over at least two instances of the stance phase that are not the same as the at least two instances of the stance phase used in the inferring step of claim 1.
Claim 13 recites the limitation “the calculation of the plantar pressure line of the individual’s foot” [line 2], which is considered to lack antecedent basis, as claims 1 and 13 fail to previously define a “calculation of the plantar pressure line of the individual’s foot”. The identified limitation is further considered to render claim 13 indefinite, as it is not clear whether the recited limitation is meant to refer to the previously defined step of claim 1 of “inferring the plurality of pressure centers to form the plantar pressure line of the individual’s foot” [lines 14-15 of claim 1]; define a new or separate step of performing a calculation of the plantar pressure line; further define the inferring step as being a calculation; or actually refer to the previously defined calculation limitation of claim 1 of “calculating foot angle values…” [lines 11-13 of claim 1]. For examination purposes, the Examiner has interpreted any of the identified interpretations to be applicable in light of any prior art applied under § 102 or § 103.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-16, 18-19, and 21-23 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. Each claim has been analyzed to determine whether it is directed to any judicial exceptions.
Representative claim(s) 22 [representing all independent claims] recite(s):
A device for inferring a plantar pressure line, said plantar pressure line including a plurality of pressure centers inferred for a foot of an individual, said inference device including one or several microprocessors, said one or several microprocessors being configured to:
- load a correlation model, said correlation model defining a relationship between a plurality of data obtained from plantar pressure sensors and a plurality of foot angle values relative to a predetermined reference frame;
- calculate foot angle values relative to the predetermined reference frame, from movement data generated by at least one inertial unit, over at least two instants of the stance phase of the foot of said individual; and
- infer a plurality of pressure centers to form the plantar pressure line of the individual’s foot, from the angle values calculated over the at least two instants of the stance phase of the foot and from the model correlation.
(Emphasis added: abstract idea, additional element)
Step 2A Prong 1
Representative claim(s) 22 recites the following abstract ideas, which may be performed in the mind or by hand with the assistance of pen and paper:
“load a correlation model, said correlation model defining a relationship between a plurality of data obtained from plantar pressure sensors and a plurality of foot angle values relative to a predetermined reference frame” – may be performed by merely thinking of or writing down known or derived relationships between different datasets for at least a limited amount of data
“calculate foot angle values relative to the predetermined reference frame, from movement data generated by at least one inertial unit, over at least two instants of the stance phase of the foot of said individual” – may be performed by merely observing known or previously collected data and drawing mental conclusions therefrom based on known or derived mathematical formulas or relationships for at least a limited amount of data under no particular time constraints, wherein the Examiner notes that the recitation of the movement data being “generated by at least one inertial unit, over at least two instants of the stance phase of the foot of said individual” merely defines the type of data/where the data may have come from and is not a positive recitation of any step of data collection by any particular structure
“infer a plurality of pressure centers to form the plantar pressure line of the individual’s foot, from the angle values calculated over the at least two instants of the stance phase of the foot and from the model correlation” – may be performed by merely observing known or previously collected data and drawing mental conclusions therefrom based on known or derived mathematical formulas or relationships for at least a limited amount of data under no particular time constraints
If a claim, under BRI, covers performance of the limitations in the mind but for the mere recitation of extra-solutionary activity (and otherwise generic computer elements) then the claim falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Step 2A Prong 1 of the Mayo framework as set forth in the 2019 PEG.
No limitations are provided that would force the complexity of any of the identified evaluation steps to be non-performable by pen-and-paper practice.
Alternatively or additionally, these steps describe the concept of using implicit mathematical formula(s) [i.e., “calculate foot angle values relative to the predetermined reference frame, from movement data generated by at least one inertial unit, over at least two instants of the stance phase of the foot of said individual”] to derive a conclusion based on input of data, which corresponds to concepts identified as abstract ideas by the courts [Diamond v. Diehr. 450 U.S. 175, 209 U.S.P.Q. 1 (1981), Parker v. Flook. 437 U.S. 584, 19 U.S.P.Q. 193 (1978), and In re Grams. 888 F.2d 835, 12 U.S.P.Q.2d 1824 (Fed. Cir. 1989)]. The concept of the recited limitations identified as mathematical concepts above is not meaningfully different than those mathematical concepts found by the courts to be abstract ideas.
The dependent claims merely include limitations that either further define the abstract idea [e.g. limitations relating to the data gathered or particular steps which are entirely embodied in the mental process] and amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they are merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Thus, these concepts are similar to court decisions of abstract ideas of itself: collecting, displaying, and manipulating data [Int. Ventures v. Cap One Financial], collecting information, analyzing it, and displaying certain results of the collection and analysis [Electric Power Group], collection, storage, and recognition of data [Smart Systems Innovations].
Step 2A Prong 2
The judicial exception is not integrated into a practical application.
Representative claim 22 only recites additional elements of extra-solutionary activity – in particular, extra-solution activity [generic computer function; the Examiner notes that there is NO POSITIVE RECITATION of data gathering in representative claim 22] – without further sufficient detail that would tie the abstract portions of the claim into a specific practical application (2019 PEG p. 55 – the instant claim, for example does not tie into a particular machine, a sufficiently particular form of data or signal collection – via the claimed extra-solution activity identified above, or a sufficiently particular form of display or computing architecture/structure).
Dependent claim(s) 2-6, 8-9, 11, 13-16, 19 merely add detail to the abstract portions of the claim but do not otherwise encompass any additional elements which tie the claim(s) into a particular application/integration [the dependent claim(s) recite generic ‘units’ or ‘steps’ which encompass mere computer instructions to carry out an otherwise wholly abstract idea].
Dependent claim(s) 7, 12, 21, 23 encounter substantially the same issues as the independent claim(s) from which they depend in that they encompass further generic extra-solutionary activity [generic data gathering] and/or generic computer elements [storage, memory per se].
Accordingly, the claim(s) are not integrated into a practical application under Step 2A Prong 2.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Independent claims 1 and 22 as individual wholes fail to amount to significantly more than the judicial exception at Step 2B. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of extra-solutionary activity [i.e., generic computer function] and generic computer elements cannot amount to significantly more than an abstract idea [MPEP § 2106.05(f)] and is further considered to merely implement an abstract idea on a generic computer [MPEP § 2106.05(d)(II) establishes computer-based elements which are considered to be well understood, routine, and conventional when recited at a high level of generality].
For the independent claim portions and dependent claims which provide additional elements of extra-solutionary data gathering, MPEP § 2106.05(g) establishes that mere data gathering for determining a result does not amount to significantly more. The extra-solutionary activity of processor steps [acquiring signals, etc.] as presently recited, cannot provide an inventive concept which amounts to significantly more than the recited abstract idea.
For the independent claims as well as the dependent claims merely reciting generic computer elements and functions [computer elements recited at a high level of generality and functions therein], MPEP § 2106.05(d)(II) establishes computer-based elements which are considered to be well understood, routine, and conventional when recited at a high level of generality.
Accordingly, the generic computer elements and functions therein, as presently limited, cannot provide an inventive concept since they fall under a generic structure and/or function that does not add a meaningful additional feature to the judicial exception(s) of the claim(s).
Claim 1 recites “implemented by at least one inertial unit coupled to a shoe worn by said individual and being configured to generate movement data for a plurality of instants of a stance phase of a foot of said individual” and claim 23 recites “at least one inertial unit is coupled to a shoe worn by said individual, said at least one inertial unit being configured to generate movement data for a plurality of instants of a stance phase of a foot of said individual”. The Examiner notes that claim 3 recites “movement data generated on six axes or nine axes”, claim 4 recites “the at least one inertial units while positioned in a removable or non-removable sole”, claim 5 recites “the at least one inertial unit while positioned in an electronic casing arranged to be fixed on the shoe worn by said individual”, “the at least one inertial unit while positioned in an electronic casing”; however, the Examiner notes that while the recitations of claims 3-5 are not considered to be positive recitations of functions of the at least one inertial unit, for the sake of compact prosecution the Examiner has included the limitations in the Step 2B analysis. Such an at least one inertial unit is considered well-understood, routine, and conventional, as known by at least:
Applicant’s disclosure is not particular regarding the particular structure of the generically claimed at least one inertial unit as positioned in a removable or non-removable sole / fixed on a shoe / positioned in an electronic casing, and recites the at least one inertial sensor at a high level of generality [The inertial unit 21 could for example be a six-axis or nine-axis inertial unit… the inertial unit 21 can be positioned in an electronic casing 20 fixed on the shoe worn by an individual (Applicant’s Specification ¶0094); The inertial unit is preferably coupled to a shoe but more generally it is coupled to the foot of an individual. The coupling can be direct or via a shoe (Applicant’s Specification ¶0095)]. 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 medical technology arts. Thus, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the field of gait analysis. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional element because it describes such an additional element in a manner that indicates that the additional element is 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, Page 3, (III)(A)(1), not attached]. Adding hardware that performs “well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible [TLI Communications].
Kiani (US-20150100105-A1) [FIG. 6 illustrates an example sensor configuration 600 with the sensor unit 120 embedded in an insole 602 of a footwear (Kiani ¶0126); The sensor unit socket 604 can receive a component, such as 670, that houses the other modules of the sensor unit 120, such as… other sensors in the sensor module 450 (e.g., accelerometer, gyroscope, etc.) (Kiani ¶0127); Figure 6]
Kirtley (US-20030009308-A1) [A light weight flexible insole 1… Two piezo-electric gyroscope sensors 3 and 6 (Murata ENC-03J) sense angular velocity about the longitudinal and transverse axes of the insole, respectively, while two bi-axial accelerometers 5 and 7 (Analog Devices ADXL202) sense acceleration in the three orthogonal directions (longitudinal, transverse and vertical) (Kirtley ¶0039); Figure 1]
Pease (US-20130041617-A1) [The system 100, as shown in FIG. 1, includes one or more sensors 105 attached to (e.g., embedded within, fixedly coupled to, or releasably coupled to) a portion of a shoe 110 of a runner 115 to measure one or more data conditions/performance characteristics during athletic activity (e.g., a run) (Pease ¶0049); The sensor(s) may be integrally embedded within the shoe and, for example, within one or more portions of a sole (e.g., an outsole, midsole, or insole) of a shoe (Pease ¶0050); Various sensors may be utilized to measure one or more data conditions during athletic activity. Example sensors include, but are not limited to,… accelerometers,… gyroscopic sensors (Pease ¶0051); a separate sensor (e.g., an accelerometer) may be used in the sensor unit in addition to the gyroscopic sensor, with the accelerometer being used to indicate when a foot strike event is taking place and the gyroscopic sensor only capturing angular velocity data (Pease ¶0106); Figures 2-4]
Claim 6 recites “said electronic casing also including one or several microprocessors” and claim 7 recites “one or several microprocessors positioned in an electronic casing integrated into a sole of the shoe”. Such an electronic casing is considered well-understood, routine, and convention, as known by at least:
Applicant’s disclosure is not particular regarding the particular structure of the generically claimed “electronic casing also including one or several microprocessors” / “one or several microprocessors positioned in an electronic casing integrated into a sole of the shoe”, and recites the electronic casing at a high level of generality [As will be detailed below, the inertial unit 21 generating the movement data is preferably positioned in an electronic casing 20 arranged to be integrated into a sole. However, the invention can be implemented from data generated by one or several inertial units positioned on a shoe or at the level of an ankle. Particularly, during the step 300 of generating the data by the inertial unit 21, the inertial unit 21 can be positioned in an electronic casing 20 fixed on the shoe worn by an individual (Applicant’s Specification ¶0094)]. 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 medical technology arts. Thus, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the field of gait analysis. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional element because it describes such an additional element in a manner that indicates that the additional element is 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, Page 3, (III)(A)(1), not attached]. Adding hardware that performs “well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible [TLI Communications].
Claim 10 recites “wherein the correlation model corresponds to a machine learning model” and claim 18 recites “wherein the machine learning model is selected from a supervised, unsupervised or reinforcement machine learning model”. Such a machine learning model is considered well-understood, routine, and conventional, as known by at least:
Hu (“Intelligent Sensor Networks”, NPL attached) [In supervised learning, the learner is provided with labeled input data. This data contains a sequence of input/output pairs of the form xi, yi, where xi is a possible input and yi is the correctly labeled output associated with it. The aim of the learner in supervised learning is to learn the mapping from inputs to outputs. The learning program is expected to learn a function f that accounts for the input/output pairs seen so far, f (xi) = yi, for all i. This function f is called a classifier if the output is discrete and a regression function if the output is continuous. The job of the classifier/regression function is to correctly predict the outputs of inputs it has not seen before (Hu, Page 5)]
Huang (“Kernel Based Algorithms for Mining Huge Data Sets”, NPL attached) [In supervised learning, the learner is provided with labeled input data. This data contains a sequence of input/output pairs of the form xi, yi, where xi is a possible input and yi is the correctly labeled output associated with it. The aim of the learner in supervised learning is to learn the mapping from inputs to outputs. The learning program is expected to learn a function f that accounts for the input/output pairs seen so far, f (xi) = yi, for all i. This function f is called a classifier if the output is discrete and a regression function if the output is continuous. The job of the classifier/regression function is to correctly predict the outputs of inputs it has not seen before (Huang, Page 1)]
Mitchell (“The Discipline of Machine Learning”, NPL attached) [For example, we now have a variety of algorithms for supervised learning of classification and regression functions; that is, for learning some initially unknown function f : X [Calibri font/0xE0] Y given a set of labeled training examples {xi; yi} of inputs xi and outputs yi = f(xi) (Mitchell, Pages 3-4)]
Examiner’s Note Regarding Particular Treatment or Prophylaxis: Claim(s) 1-16, 18-19, 21-23 fail to recite any subject matter that may be considered to be a particular treatment or prophylaxis, as none of the identified claims positively recite or include language that is considered to be a particular treatment or prophylaxis as an additional element [the Examiner notes that the recitation of “comparing the plantar pressure lines…” in each of claims 15-16 is not considered to define any kind of treatment or prophylaxis] to integrate the judicial exception into a practical application or allow the identified claims to amount to significantly more than the judicial exception [MPEP § 2106.04(d)(2)].
Accordingly, the claim(s) as whole(s) fail amount to significantly more than the judicial exception under Step 2B.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-2, 5, 8, 10-11, 13-14, 18, and 22-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ding (“Control of Walking Assist Exoskeleton With Time-delay Based on the Prediction of Plantar Force”, NPL cited and attached by Applicant) in view of Pattillo (US-20040143452-A1).
Regarding claim 1, Ding teaches
A method for inferring a plurality of pressure centers for a foot of an individual, said method being implemented by at least one inertial unit coupled to a shoe worn by said individual and being configured to generate movement data for a plurality of instants of a stance phase of a foot of said individual [As shown in Fig. 5, we placed the IMU sensors on the lower legs near the ankles (Ding p. 5)], said method including the following steps:
- loading a correlation model, said correlation model defining a relationship between a plurality of data obtained from plantar pressure sensors and a plurality of foot angle values relative to a predetermined reference frame [For training the network, we take n frames of the measured past signals of the IMU sensors as input. The measured plantar force after s frames is used as the target output. To use the trained network, we input the measured past n -frame signals from the IMU sensors, and the network will output the predicted plantar force of the future s frame (Ding p. 4)];
- calculating foot angle values relative to the predetermined reference frame, from the movement data generated by the at least one inertial unit, over at least two instants of the stance phase of the foot of said individual [As shown in Fig. 5, we placed the IMU sensors on the lower legs near the ankles (Ding p. 5); To test both stable and unstable walking, as shown in Fig. 7, we asked the subjects to walk from two steps to eight steps in every trail. Between two sets of walking, the subjects should pause and stand a moment before starting the next walking. Every subject performed such walking 8 trails and also performed 2 trails walking with random steps and pauses as desired. Totally, from every subject, we measured the walking data of 10 trails (Ding p. 6)]; and
- inferring the plurality of pressure centers of the individual’s foot, from the angle values calculated over the at least two instants of the stance phase of the foot and from the correlation model [The walking phase is estimated based on the predicted plantar force… Fig. 3 shows the change in the plantar force of the left foot during one walking cycle from a heel-strike to the next heel-strike. The plantar force starts on the heel fh and increases to the first peak during the heel-strike stage. Then, during the support stage, the plantar force wqualizes across all pressure cells on the foot. Before the foot swing, the plantar force on the tip ft increases to the second peak for kicking the ground. When foot start the swing, the plantar force is zero, f=0 . By detecting the changing points for each plantar force (fh , fm , and ft ), the walking phases can also be estimated (Ding p. 4, Fig. 3); The trained network can be copied to this computer to predict the walking phases in real-time from the measured IMU signals (Ding p. 5), wherein as depicted in Fig. 3, the predicted (inferred) plantar pressure for a predicted stage of a gait cycle is associated with a different portions of the subject’s foot defining a plurality of pressure centers, wherein based on the claim language wherein the inferred plurality of pressure centers themselves define the plantar pressure line, Ding is considered to infer the “plantar pressure line”].
However, Ding fails to explicitly disclose that the method is for inferring a plantar pressure line including a plurality of pressure centers inferred for a foot of an individual, wherein the inferred plurality of pressure centers are used to form the plantar pressure line of the individual's foot.
Pattillo discloses systems and methods for dynamically assessing an individual’s foot during strides, wherein Pattillo discloses forming a pressure line of the individual’s foot using a plurality of determined pressure centers of the foot [In general, stage 840 analyzes the gait line to detect any rolling in of the foot that may be missed by other stages, 810-830. To illustrate FIG. 13, FIG. 14 is a diagram of the gait line consistent with the principals of the present invention. The gait line 1440 is derived based on the pressure readings and is an indication of the center of pressure of the individual through the stride, where the center of pressure is the average point of pressure exerted by the foot on the platform at time, t.sub.i (Pattillo ¶0056, Fig. 14)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Ding to employ the method to infer a plantar pressure line including the plurality of pressure centers inferred for the foot of the individual, wherein the inferred plurality of pressure centers are used to form the plantar pressure line of the individual's foot, so as to provide additional contextual information of the individual’s gait, such as foot rolling.
Regarding claim 2, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1, wherein the inferring step is repeated so as to establish the plantar pressure line inferred from several stance phases [Ding p. 5-6, wherein Ding discloses that the prediction may be applied in real-time and further discloses assessing the gait during a plurality of trails comprising 2-8 steps each].
Regarding claim 5, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1, wherein the calculating step is carried out from movement data generated by the at least one inertial units while positioned in an electronic casing arranged to be fixed on the shoe worn by said individual [Ding Figs. 4-5].
Regarding claim 8, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1, wherein the calculating step is carried out for at least five foot placement instants [Ding p. 5-6, wherein Ding discloses that the prediction may be applied in real-time and further discloses assessing the gait during a plurality of trails comprising 2-8 steps each].
Regarding claim 10, Ding in view of Pattillo teaches
The method for inferring an inferred plantar pressure line according to claim 1, wherein the correlation model corresponds to a machine learning model [a model is created and trained based on Long short-term memory (LSTM) method (Ding p. 3)].
Regarding claim 11, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1, wherein the calculated foot angle values, relative to the predetermined reference frame, include angle values selected from: an angle of an antero-posterior axis of the foot relative to its progression line, an angle of the antero-posterior axis of the foot relative to the ground [wherein as depicted in at least Fig. 1 of Ding, the IMU is depicted as measuring at least an angle of the antero-posterior axis of the foot relative to the ground], an angle of a transverse axis of the foot relative to its progression line or an angle of the transverse axis of the foot relative to the ground.
Regarding claim 13, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1, wherein the calculation of the plantar pressure line of the individual's foot is carried out without taking into account data coming from a pressure sensor coupled to the individual's shoe [Ding p. 4-5, Fig. 3; wherein based on the § 103 modification above, the plantar pressure line is based on only the IMU data].
Regarding claim 14, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1, comprising calculation of the plantar pressure line for each of the feet of the individual [as Ding Fig. 5 depicts the use of IMUs for each foot of the individual, the prediction (Ding p. 4-5) is considered to be applicable to each foot].
Regarding claim 18, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 10, wherein the machine learning model is selected from a supervised, unsupervised or reinforcement machine learning model [wherein since the LSTM model is trained using input data, the machine learning model is considered to be supervised].
Regarding claim 22, Ding teaches
A device for inferring a plurality of pressure centers inferred for a foot of an individual, said inference device including one or several microprocessors [We assembled a small single board computer (Raspberry Pi 3B) in the exoskeleton. This computer can measure the signals from the IMU sensors through the Bluetooth communications. The trained network can be copied to this computer to predict the walking phases in real-time from the measured IMU signals (Ding p. 5)], said one or several microprocessors being configured to:
- load a correlation model, said correlation model defining a relationship between a plurality of data obtained from plantar pressure sensors and a plurality of foot angle values relative to a predetermined reference frame [For training the network, we take n frames of the measured past signals of the IMU sensors as input. The measured plantar force after s frames is used as the target output. To use the trained network, we input the measured past n -frame signals from the IMU sensors, and the network will output the predicted plantar force of the future s frame (Ding p. 4)];
- calculate foot angle values relative to the predetermined reference frame, from movement data generated by at least one inertial unit, over at least two instants of the stance phase of the foot of said individual [As shown in Fig. 5, we placed the IMU sensors on the lower legs near the ankles (Ding p. 5); To test both stable and unstable walking, as shown in Fig. 7, we asked the subjects to walk from two steps to eight steps in every trail. Between two sets of walking, the subjects should pause and stand a moment before starting the next walking. Every subject performed such walking 8 trails and also performed 2 trails walking with random steps and pauses as desired. Totally, from every subject, we measured the walking data of 10 trails (Ding p. 6)]; and
- infer a plurality of pressure centers of the individual’s foot, from the angle values calculated over the at least two instants of the stance phase of the foot and from the model correlation [The walking phase is estimated based on the predicted plantar force… Fig. 3 shows the change in the plantar force of the left foot during one walking cycle from a heel-strike to the next heel-strike. The plantar force starts on the heel fh and increases to the first peak during the heel-strike stage. Then, during the support stage, the plantar force wqualizes across all pressure cells on the foot. Before the foot swing, the plantar force on the tip ft increases to the second peak for kicking the ground. When foot start the swing, the plantar force is zero, f=0 . By detecting the changing points for each plantar force (fh , fm , and ft ), the walking phases can also be estimated (Ding p. 4, Fig. 3); The trained network can be copied to this computer to predict the walking phases in real-time from the measured IMU signals (Ding p. 5), wherein as depicted in Fig. 3, the predicted (inferred) plantar pressure for a predicted stage of a gait cycle is associated with a different portions of the subject’s foot defining a plurality of pressure centers, wherein based on the claim language wherein the inferred plurality of pressure centers themselves define the plantar pressure line, Ding is considered to infer the “plantar pressure line”].
However, Ding fails to explicitly disclose that the device is for inferring a plantar pressure line including a plurality of pressure centers inferred for a foot of an individual, wherein the inferred plurality of pressure centers are used to form the plantar pressure line of the individual's foot.
Pattillo discloses systems and methods for dynamically assessing an individual’s foot during strides, wherein Pattillo discloses forming a pressure line of the individual’s foot using a plurality of determined pressure centers of the foot [In general, stage 840 analyzes the gait line to detect any rolling in of the foot that may be missed by other stages, 810-830. To illustrate FIG. 13, FIG. 14 is a diagram of the gait line consistent with the principals of the present invention. The gait line 1440 is derived based on the pressure readings and is an indication of the center of pressure of the individual through the stride, where the center of pressure is the average point of pressure exerted by the foot on the platform at time, t.sub.i (Pattillo ¶0056, Fig. 14)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the device of Ding to employ the one or several microprocessors to infer a plantar pressure line including the plurality of pressure centers inferred for the foot of the individual, wherein the inferred plurality of pressure centers are used to form the plantar pressure line of the individual's foot, so as to provide additional contextual information of the individual’s gait, such as foot rolling.
Regarding claim 23, Ding in view of Pattillo teaches
The device for inferring a plantar pressure line according to claim 22,wherein the at least one inertial unit is coupled to a shoe worn by said individual, said at least one inertial unit being configured to generate movement data for a plurality of instants of a stance phase of a foot of said individual [Ding p. 5-6, Figs. 4-5].
Claim(s) 3-4, 6-7, and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ding in view of Pattillo, as applied to claim 1, in further view of Kiani (US-20150100105-A1).
Regarding claim 3, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1.
However, Ding in view of Pattillo is not particular regarding the inertial unit [In this research, due to wearability and usability, wireless IMU sensors are used to measure the walking motion. An IMU sensor is generally composed of accelerometer, gyroscope, and sometimes magnetometer, which can measure the acceleration, the angular velocity, and sometimes the direction of the magnetic field (Ding p. 3)], such that Ding in view of Pattillo fails to explicitly disclose wherein the calculation calculating step is carried out from movement data generated on six axes or nine axes.
Kiani discloses systems and methods for assessing an individual’s foot condition, wherein Kiani discloses an insole of the individual’s shoe comprising at least one 6-axis inertial unit for monitoring an orientation of the individual’s foot [the sensor unit 120 embedded in an insole 602 of a footwear (Kiani ¶0126, Fig. 6); The sensor unit socket 604 can receive a component, such as 670, that houses the other modules of the sensor unit 120, such as the power module 460, the sensor processor 410, the timer module 440, other sensors in the sensor module 450 (e.g., accelerometer, gyroscope, etc.), the user interface module 420, and the communication module 430 (Kiani ¶0127); In some embodiments, the gyroscope and the accelerometer may be provided together in an integrated circuit, such as in an inertial measurement unit (IMU) (Kiani ¶0120); A block diagram of an example IMU 500 is illustrated in FIG. 5. As shown in FIG. 5, the IMU 500 includes a three-axis gyroscope 510, a three-axis accelerometer 520 and a temperature sensor 530. The IMU 500 also includes a timing clock 540. The IMU 500 can generate a real-time angular velocity and acceleration of the foot of the user 170 where the sensor unit 120 is located (Kiani ¶0121)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Ding in view of Pattillo to employ wherein the calculation calculating step is carried out from movement data generated on six axes or nine axes, as this modification would amount to mere simple substitution of one known element [non-particular IMU of Ding] for another [6-axis IMU of Kiani] with similar expected results [MPEP § 2143(I)(B)].
Regarding claim 4, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1.
However, while Ding in view of Pattillo discloses positioning the inertial unit to detect the orientation of the individual’s foot [see Ding Fig. 5], Ding fails to explicitly disclose wherein the calculating step is carried out from movement data generated by the at least one inertial unit while positioned in a removable or non-removable sole.
Kiani discloses systems and methods for assessing an individual’s foot condition, wherein Kiani discloses an insole of the individual’s shoe comprising at least one inertial unit for monitoring an orientation of the individual’s foot [Kiani ¶¶0120-0121, 0126-0127].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Kiani to employ wherein the calculating step is carried out from movement data generated by the at least one inertial unit while positioned in a removable or non-removable sole, as this modification would amount to mere simple substitution of one known element [IMU attached to shoe] for another [IMU positioned in a removable or non-removable sole] with similar expected results [measure orientation of the individual’s foot] [MPEP § 2143(I)(B)].
Regarding claim 6, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1, wherein the calculating step is carried out from movement data generated by the at least one inertial units while positioned in an electronic casing [Ding Figs. 4-5].
However, Ding in view of Pattillo fails to explicitly disclose said electronic casing also including one or several microprocessors configured to calculate the foot angle values relative to the predetermined reference frame.
Kiani discloses systems and methods for assessing an individual’s foot condition, wherein Kiani positioning one or several microprocessors configured to calculate the foot angle values relative to the predetermined reference frame within an electronic casing that also contains IMUs [Kiani ¶¶0120-0121, 0126-0127; At 910, the sensor processor 410 receives motion information associated with the gait of the user 170. The sensor module 450 includes sensors that can collect, at least, motion information. The sensors may continuously or periodically collect motion information or may be triggered to collect motion information. The motion information can include a foot acceleration of the foot of the user 170 and a foot angular velocity of the foot of the user 170 (Kiani ¶0133); At 920, the sensor processor 410 generates a foot orientation indicator for the foot based on the foot acceleration and the foot angular velocity. The foot orientation indicator corresponds to an angular position relative to a longitudinal axis of the foot. The angular position may be generated based on an orientation of the foot with respect to the longitudinal axis of the foot. For example, as will be described with reference to FIGS. 12A and 12B, the angular position may correspond to various angles measured in the three-dimensional Cartesian coordinate system (Kiani ¶0141)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Ding in view of Pattillo to employ wherein said electronic casing also including one or several microprocessors configured to calculate the foot angle values relative to the predetermined reference frame, as this modification would amount to mere simple substitution of one known element [processing system to calculate foot angle values that is not within the same electronic casing of the IMU as disclosed by Ding] for another [one or several microprocessors positioned within the same electronic casing the of the at least one inertial unit as disclosed by Kiani] with similar expected results [allow for calculation of the foot angle values] [MPEP § 2143(I)(B)].
Regarding claim 7, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 6.
However, Ding fails to explicitly disclose wherein the calculating and inferring steps are implemented by one or several microprocessors positioned in an electronic casing integrated into a sole of the shoe.
Kiani discloses systems and methods for assessing an individual’s foot condition, wherein Kiani positioning one or several microprocessors configured to perform calculations and data processing in an electronic casing integrated into a sole of the shoe [Kiani ¶¶0120-0121, 0126-0127, 0133, 0141].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Ding in view of Pattillo to employ wherein the calculating and inferring steps are implemented by one or several microprocessors positioned in an electronic casing integrated into a sole of the shoe, as this modification would amount to mere simple substitution of one known element [processing system that is not within an electronic casing integrated into a sole of the shoe of Ding] for another [one or several microprocessors positioned in an electronic casing integrated into a sole of the shoe as disclosed by Kiani] with similar expected results [allow for data processing] [MPEP § 2143(I)(B)].
Regarding claim 9, Ding in view of Pattillo teaches
The method for inferring a plantar pressure line according to claim 1.
However, Ding fails to explicitly disclose wherein the calculating step includes the calculation of values of at least two angles of the foot.
Kiani discloses systems and methods for assessing an individual’s foot condition, wherein Kiani discl