DETAILED ACTION
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-7 and 9 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.
Regarding claim 2, the limitation “a second feature amount” renders the claim indefinite because a second feature is already recited in claim 1. It is unclear if these are the same second feature amounts. For purposes of examination the indefinite limitation has been deemed to claim the same feature amounts.
Regarding Claim 2, the limitation “estimates at least one physical ability factor” renders the claim indefinite, because a “physical ability factor” has already been introduced in Claim 1. Furthermore, the claims recite both “a physical ability” and “at least one physical ability”. For purposes of examination the indefinite limitation has been deemed to claim that all the mentioned physical abilities are the same physical ability.
Regarding claim 2, the limitation “the at least one physical ability factor output” lacks proper antecedent basis. While a “physical ability factor” has been previously claimed, an “output” thereof has not.
Regarding claim 3, the limitation “the at least one attribute factor” renders the claim indefinite because it is unclear if this is the same attribute factor as previously claimed that does not mention “at least one”. For purposes of examination the indefinite limitation has been deemed to claim that all the claimed attribute factors are the same attribute factor.
Regarding Claim 9, the limitation “a subject” renders the claim indefinite as it is unclear if “a subject” is the same subject as previously set forth in the claims.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-8, 10 and 11 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 1-8, 10 and 11 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1-8, 10 and 11 recites at least one step or instruction for outputting an estimated falling risk information calculated from PCA data including a physical ability factor and an attribute factor, 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 1-8, 10 and 11recites an abstract idea.
Specifically, Claims 1, 10 and 11 recites memory and a processor that acquires gait data and attribute data, performs PCA on the data to construct second feature data, and estimates falling risk from the second feature data (observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG);
Further, dependent Claims 2-8 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
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, 10 and 11 (and their respective dependent Claims 2-8) is not integrated into a practical application under 2019 PEG because the additional elements (identified above in independent Claims 1-8, 10 and 11), 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: memory, processor, and storageare generically recited computer elements in independent Claims 1, 10 and 11 (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, 10 and 11 (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, memory, and storage 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, 10 and 11(and their respective dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claims 1, 10 and 11 (and their respective dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 1-8, 10 and 11 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: processor, memory and storage
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, the claimed terms of processor, memory and storage is 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, memory and storage.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 1-8, 10 and 11 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 and methods of Claims 1-8, 10 and 11 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 1-8, 10 and 11 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, 10 and 11 (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 1-8, 10 and 11 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 1-8, 10 and 11 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1-8, 10 and 11 are not patent eligible and rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
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 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, 8, 10 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20220257148 A1 to Aihara et al. (hereinafter, Aihara) and Daily-Life Gait Quality as Predictor of Falls in Older People: A 1-Year Prospective Cohort Study in view of van Schooten (hereinafter, van Schooten).
Regarding Claims 1, 10 and 11, Aihara discloses an estimation device, method and non-transitory recording medium that records a program for causing a computer to execute inter alia:
a first memory (e.g., storage 24 and combination of two or more dedicated circuits) storing instructions ([0038] “Estimation device 20 includes calculator 21, risk analyzer 22, factor analyzer 23, and storage 24.” (emphasis added) ([0053] “The processing units in estimation device 20 may be implemented by one processor, microcomputer, or dedicated circuit having their functions, or implemented by a combination of two or more processors, microcomputers, or dedicated circuits.” (emphasis added)); and
a first processor (e.g., calculators and analyzers and combination of two or more processors or microcomputers) connected to the first memory and configured to execute the instructions ([0038] “Estimation device 20 includes calculator 21, risk analyzer 22, factor analyzer 23, and storage 24.” (emphasis added)) ([0053] “The processing units in estimation device 20 may be implemented by one processor, microcomputer, or dedicated circuit having their functions, or implemented by a combination of two or more processors, microcomputers, or dedicated circuits.” (emphasis added)) to:
acquire first feature amount data related to a physical ability ([0040] “…walking parameters include walking speed, step length, joint angle, and/or lumbar or head displacement that correlate with at least one of muscle strength, muscle mass, sense of balance, or cognitive function.”) measured according to a gait of a subject and attribute data of the subject ([0039] “…calculator 21 obtains moving image data captured by measurement device 10, as body motion data indicating the body motion of measured person 50 during walking.”);
construct second feature amount data related to a physical ability factor by performing principal component analysis on the acquired first feature amount data ([0078] “…factor analyzer 23 performs main component analysis based on the walking parameters to thus estimate a main component included in the factor of fall risk.”),
estimate falling risk information according to a falling risk factor using the constructed second feature amount data ([0080] “Factor analyzer 23 then estimates a factor of fall risk of measured person 50 based on, for example, the degree of influence for each main component (S25)”) ([0042] “FIG. 3 is a diagram illustrating an example of the formula for calculating a fall risk value by risk analyzer 22 according to this embodiment. Scores X1, X2, and X3 illustrated in FIG. 3 are numeric values based on walking parameters.”); and
output the estimated falling risk information ([0081] “Following this, factor analyzer 23 outputs information indicating the estimation result to display device 40 (S26). That is, factor analyzer 23 causes display device 40 to display the estimation result.”);
(Claim 2) further comprising a storage configured to store an estimation model that estimates at least one physical ability factor related to the falling risk factor as the first feature amount data are input ([0051] “Storage 24 also stores, for example, a program for each processing unit to carry out a factor estimation method according to the embodiment, and information and data used in factor analysis.”), constructs a second feature amount by performing principal component analysis of the estimated physical ability factor ([0078] “… factor analyzer 23 may calculate the degree of influence on the fall risk based on the score of walking speed and the score of step length. Factor analyzer 23 calculates, for example, the sum of the score of walking speed and the score of step length as the degree of influence of the main component “muscle strength” on the fall risk. In other words, factor analyzer 23 performs main component analysis based on the walking parameters to thus estimate a main component included in the factor of fall risk.”), and outputs a falling risk score using the constructed second feature amount ([0081] “Following this, factor analyzer 23 outputs information indicating the estimation result to display device 40 (S26). That is, factor analyzer 23 causes display device 40 to display the estimation result.”), wherein the first processor is configured to execute the instructions to input the acquired first feature amount data to the estimation model ([0053] “The processing units in estimation device 20 may be implemented by one processor, microcomputer, or dedicated circuit having their functions, or implemented by a combination of two or more processors, microcomputers, or dedicated circuits.”), and estimate the falling risk information using the at least one physical ability factor output from the estimation model ([0080] “Factor analyzer 23 then estimates a factor of fall risk of measured person 50 based on, for example, the degree of influence for each main component (S25). That is, factor analyzer 23 estimates the factor of fall risk based on two or more walking parameters. Based on the two or more walking parameters, factor analyzer 23 estimates one or more main components included in the factor of fall risk of measured person 50 from among the plurality of main components. As an example, factor analyzer 23 may estimate a main component whose degree of influence is highest, as the factor of fall risk of measured person 50. As another example, factor analyzer 23 may estimate a main component whose degree of influence is greater than or equal to a predetermined degree, as the factor of fall risk of measured person 50.”); and
(Claim 8) wherein the first processor is configured to execute the instructions to output recommendation information for the subject to do decision making corresponding to the falling risk information ([0100], [0106], [0107], [0119]).
Aihara discloses the claimed invention as set forth and cited above except for expressly disclosing (Claims 1) where the principal component analysis also includes analysis on the acquired attribute data to construct second feature amount data related to both a physical ability factor and an attribute factor, (Claim 2) where the storage, constructs of a second feature by PCA and estimation also include attribute data.
However, van Schooten teaches a fall risk predicition system for adults that uses a wearable sensor to capture gait combined with subject characteristics and processed via PCA to predict prospective falls (Abstract and Method sections). Van Schooten teaches performing PCA on a combined set of gait features and subject attribute data including age, weight, height and grip strength (Statistical analysis “Prior to fitting multivariate models, we performed a principal component analysis (PCA) as data reduction technique.”) (PCA and multivariate associations with time-to-fall “PCA revealed 18 principal components with an eigenvalue exceeding 1. Together, these principal components explained 80.5% of the variance in the questionnaire, tests, and accelerometry data (in total 75 variables). The varimax-rotated factor matrix can be found in S2 Table. The 18 factors reflected aspects which we coined gait quality, vigour,ML balance, physical activity, complexity, strength, disability, maximal gait duration, transfers, slow movements, history of falls, executive function, fear and depression, physical inactivity, cognition, body composition, alcohol consumption, and solace.”).
One having an ordinary skill in the art at the time the invention was filed would have found it obvious to expand the main-component analysis of Aihara to include the subject’s attribute data of van Schotten, such that the resulting principal components represent both a physical ability factor and an attribute factor, because using a main-component analysis to include both gait factors and attribute factors would have predicted falls accurately (Discussion “Our results indicate that factors related to history of falls, alcohol consumption and gait quality predicted time-to-first-fall with an adequate to good accuracy (AUC 0.66–0.72). With the addition of the factor related to strength, these factors were able to predict time-to-second fall with adequate to good accuracy (AUC 0.69–0.76).”) and Aihara evidences the supplementation of gait derived inputs with non-gait subject information by already incorporating a fall-history score into its fall-risk calculation ([0044]).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Aihara in view of van Schooten, and further in view of US 20180279915 A1 to Huang et al. (hereinafter, Huang).
Aihara in view of van Schooten teach and a gait measurement device including a sensor that generates sensor data according to the gait parameters from the sensor data and outputs the generated sensor data ([0031] “Factor estimation system 1 measures the body motion of measured person (i.e. person to be measured) 50 during walking (i.e. during gait) by measurement device 10 (for example, camera), to generate moving image data.”), a second memory storing instructions (e.g., storage 24 and combination of two or more dedicated circuits) ([0038] “Estimation device 20 includes calculator 21, risk analyzer 22, factor analyzer 23, and storage 24.” (emphasis added) ([0053] “The processing units in estimation device 20 may be implemented by one processor, microcomputer, or dedicated circuit having their functions, or implemented by a combination of two or more processors, microcomputers, or dedicated circuits.” (emphasis added)); and a second processor connected to the second memory (e.g., calculators and analyzers and combination of two or more processors or microcomputers) ([0038] “Estimation device 20 includes calculator 21, risk analyzer 22, factor analyzer 23, and storage 24.” (emphasis added)) ([0053] “The processing units in estimation device 20 may be implemented by one processor, microcomputer, or dedicated circuit having their functions, or implemented by a combination of two or more processors, microcomputers, or dedicated circuits.” (emphasis added)) and configured to execute the instructions to extract gait parameters to extract a first feature amount to be used in estimating the falling risk factor and generate the first feature amount data including the extracted first feature amount, and output the generated first feature amount data to the estimation device ([0037] “Estimation device 20 analyzes the walking state of measured person 50 based on the moving image data captured by measurement device 10, estimates the factor of fall risk of measured person 50, and outputs the estimation result to display device 40. Thus, estimation device 20 can notify, for example, a caregiver who cares for measured person 50 of the estimation result of the factor of fall risk of measured person 50.”).
However, Aihara in view of van Schooten do not expressly disclose and a gait measurement device including a sensor that measures a spatial acceleration and a spatial angular velocity, generates sensor data according to the gait using the measured spatial acceleration and spatial angular velocity, and outputs the generated sensor data, a second memory storing instructions; and a second processor connected to the second memory and configured to execute the instructions to extract gait waveform data for one gait cycle from time-series data of the sensor data, normalize the extracted gait waveform data, extract a first feature amount to be used in estimating the falling risk factor from the normalized gait waveform data, generate the first feature amount data including the extracted first feature amount, and output the generated first feature amount data to the estimation device, wherein the sensor is installed on footwear of a subject who is a target in estimating the falling risk factor.
However, Huang teaches a gait measurement device including a sensor that measures a spatial acceleration and a spatial angular velocity ([0022] “The three-axis accelerometer and three-axis gyroscope are inertial sensors, which can measure motion.”), generates sensor data according to the gait using the measured spatial acceleration and spatial angular velocity ([0004] “The operations include: receiving sensor data from sensors embedded within a wearable device…”), and outputs the generated sensor data, a second memory storing instructions ([0045] “ The MCU 76 with the Bluetooth Low Energy module 77 provided a wireless channel to connect the insole to a smart electronic device.”); and a second processor connected to the second memory ([0045] “…a micro control unit (MCU) 76 with a Bluetooth Low Energy (BLE) module 77, a battery module 78, and an on-board Fog computing module 79.”) and configured to execute the instructions to extract gait waveform data for one gait cycle from time-series data of the sensor data, normalize the extracted gait waveform data ([0050] “The CSV data contained information of foot side, the timestamp, nine IMU sensor data including three each from accelerometer, gyroscope and magnetometer and forty-eight pressure sensor data on the Wearable Gait Lab. The CSV data contained information of foot side, the timestamp, nine IMU sensor data including three each from accelerometer, gyroscope and magnetometer and forty-eight pressure sensor data on the Wearable Gait Lab. ), extract a first feature amount to be used in estimating the falling risk factor from the normalized gait waveform data ([0045] “…the magnetometer provided aids for data calibration.”) ([0029] “…the inertial data from the three-dimensional accelerometer and three-dimensional gyroscope can be filtered and calibrated using the three-dimensional magnetometer data. Additionally, noise can be removed from the pressure data from the pressure array.”), generate the first feature amount data including the extracted first feature amount ([0049] “…process the data into CSV files.”), and output the generated first feature amount data to the estimation device ([0045] “The MCU 76 with the Bluetooth Low Energy module 77 provided a wireless channel to connect the insole to a smart electronic device.”) (]0049] “…the mobile communication device 90 with the application 92 is able to receive the corresponding real-time movement and pressure sensor data and process the data into CSV files.”), wherein the sensor is installed on footwear of a subject who is a target in estimating the falling risk factor ([0018] “FIG. 2 illustrates an example implementation of the system 10. In FIG. 2, the wearable device 12 is implemented as an insert 22 for a shoe. The example of the insert 22 illustrated in FIG. 2 can be an insole. However, the wearable device 12 can be other devices other than the insert 22. In one example, the wearable device 12 can be an entire shoe. In another example, the wearable device 12 can be a portion of the shoe, such as the bottom.”).
One having an ordinary skill in the art at the time the invention was filed would have found it obvious to modify the collection of data via camera of Aihara with the data collection and processing of data from a shoe worn sensors on Huang and Huang teaches at [0014] and [0015] that clinical gait labs are not wearable or user friendly, and the wireless and portable gait system of van Shooten allows friendly and accurate testing in real-time rather than being confined to a clinical setting.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN PATRICK DOUGHERTY whose telephone number is (571)270-5044. The examiner can normally be reached 8am-5pm (Pacific Time).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jacqueline Cheng can be reached at (571)272-5596. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SEAN P DOUGHERTY/Primary Examiner, Art Unit 3791
Prosecution Insights