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 .
Status of Claims
This action is in response to the reply received 3/16/2026.
Claims 1-10 were elected without traverse and claims 11-18 were withdrawn 3/16/2026.
Claims 1-10 are currently pending and have been examined.
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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-10 are drawn to a method and a device which are statutory categories of invention (Step 1: YES).
Independent claims 1 and 7 recite: estimating a health score, the health score being used to quantitatively evaluate a health status related to walking of a user, and the health score including a knee condition score [gait age] for quantitatively evaluating a knee condition [gait age] of the user, the estimating method comprising: acquiring a data provider feature that is a feature related to a gait condition of each of multiple data providers and is a feature correlated with the knee condition [gait condition] from measurement information indicating temporal changes in forces applied to multiple parts of a sole of each of the multiple data providers; generating by learning a correlation between the acquired data provider feature and the knee condition [gait age] from the data provider feature and data on the knee condition [gait age] of each data provider; acquiring a user feature that is a feature of the same type as the data provider feature from measurement information indicating temporal changes in forces applied to multiple parts of a sole of the user; and estimating the knee condition [gait age] of the user as the knee condition [gait age score] by providing with the acquired user feature.
The recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity between a user and a data provider, as reflected in the specification, which states that “when each of multiple data providers walks, temporal changes in forces applied to multiple parts of a sole of the data provider using a measurement device; measuring, in synchronization with the measurement of the temporal changes in the forces, temporal changes in positions of multiple parts of the upper body of the data provider; generating a learning model by learning a correlation between the measured temporal changes in the forces and the measured temporal changes in the positions of the multiple parts; measuring, when a user walks, temporal changes in forces applied to multiple parts of a sole of the user by using the same measurement device used for measurement for the data provider; and estimating temporal changes in positions of multiple parts of the upper body of the user by providing the learning model with the temporal changes” in the forces measured for the user.” (see: specification paragraph 11). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The present claims cover certain methods of organizing human activity because they address “The user can detect early signs of lumbar diseases, which allows for the possibility to halt
the progression of the disease. This enables the user to become aware of necessary
improvements much earlier than if the signs were unnoticed.” (see: specification paragraph 150). Accordingly, the claims recite an abstract idea(s) (Step 2A Prong One: YES).”
The judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including “learning model”, are recited at a high level of generality (e.g., that the generating, estimating, and displaying is performed using generic computer components with instructions are executed to perform the claimed limitations). Such that they amount to no more than mere instructions to apply the exception using generic c
Hence, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic component cannot provide an inventive concept. See MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The originally filed specification supports this conclusion at Figure 3, Figure 6 and
Paragraph 62, where “Additionally, the information processing unit 23 includes a knee condition learning model generation unit 40, a gait age learning model generation unit 41, and a first display processing unit 42. The information processing unit 23 may be, for example, processing circuitry such as a computer including a CPU”
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with route, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claims 2-6, 8-10 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are directed to an abstract idea without significantly more. Claim 2-6, 8-10 recite obtaining, analyzing, and displaying health data on the generically recited computing device as shown in the parent claims above.
These claims fail to remedy the deficiencies of their parent claims above, and therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
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.
Claim(s) 1, 3-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Aubin (US 2023/0022710 A1) in view of Agrawal (US 2020/0000373 A1).
CLAIM 1-
Aubin teaches the limitations of:
A method of estimating a health score, the health score being used to quantitatively evaluate a health status related to walking of a user, and the health score including a knee condition score for quantitatively evaluating a knee condition of the user, the estimating method comprising: (Aubin teaches a risk score that determines the health of the user to determine their knee joint health related to their gait when walking and includes a likelihood of patient outcomes on a scale value based on their knee and gait (para [0392, 0347, 0289, 0318, 0457, 0391-0392]))
acquiring a data provider feature that is a feature related to a gait condition of each of multiple data providers and is a feature correlated with the knee condition from measurement information indicating temporal changes in forces applied to multiple parts of a sole of each of the multiple data providers; (Aubin teaches monitoring the gait cycles to obtain data parameters (i.e., data providers) including features of the cycle time and knee range of motion (i.e., knee condition measurement data) that indicate forces applied to the foot (i.e., sole) (para [0195-0197, 0134, 0130-0131] Table 6))
generating a learning model by learning a correlation between the acquired data provider feature and the knee condition from the data provider feature and data on the knee condition of each data provider; (Aubin teaches analyzing the data using machine learning on the pre-operative and post-operative data sets to monitor the knee condition in classifying the movement type of the monitored gait cycles (i.e., data providers) (para [0128, 0326, 0195-0197, 0334, 0391-0392]))
estimating the knee condition of the user as the knee condition score by providing the learning model with the acquired user feature (Aubin teaches analyzing the data using machine learning on the pre-operative and post-operative data sets from training the system using data points to monitor the knee condition in classifying the movement type of the monitored gait cycles (i.e., data providers) with a condition score to determine user clinical outcome (para [0128, 0326, 0195-0197, 0334, 0391-0392, 0326]))
Aubin teaches acquiring a user feature, but does not explicitly teach, however Agrawal teaches:
acquiring a user feature that is a feature of the same type as the data provider feature from measurement information indicating temporal changes in forces applied to multiple parts of a sole of the user; and (Agrawal teaches that the data is trained using subjects (i.e., data providers) so that the system can compare the analysis to the user to provide real-time status of the gait and knee condition of the user using temporal changes in pressure (i.e., forces) to multiple parts of the sole of the user (para [0308, 0305, 0270, 0218-0219, 0251, 0094]))
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the patient condition and gait monitoring system of Aubin to integrate the application of monitoring different parts of the sole of Agrawal with the motivation of improving patient outcomes outside a laboratory setting (see: Agrawal, paragraph 3).
CLAIM 3-
Aubin in view of Agrawal teach the limitations of claim 1. Regarding claim 3, Aubin further teaches:
wherein the data on the knee condition of the data providers includes information regarding a classification indicating a degree of progress of knee disease (Aubin teaches analyzing the data using machine learning on the pre-operative and post-operative data sets to monitor the knee condition and gait in classifying the movement type of the monitored gait cycles and knee joints (i.e., data providers) (para [0128, 0326, 0195-0197, 0334, 0391-0392]))
CLAIM 4-
Aubin in view of Agrawal teach the limitations of claim 1. Regarding claim 4, Aubin further teaches:
further comprising displaying the estimated knee condition as the knee condition score on a display in a form of a map (Aubin teaches that the data and abnormality of the gait is classified as well as the probability of the knee condition (i.e., limping) by mapping it on a display (Figure 39A)
CLAIM 5-
Aubin in view of Agrawal teach the limitations of claim 4. Regarding claim 5, Aubin further teaches:
multiple regions for indicating a varying degree of the knee condition are set in the map, (Aubin teaches that multiple regions on the screen indicate different degrees of the knee condition such as stride length and swing velocity (Figure 39A, 39B))
and displaying the estimated knee condition on the display includes indicating which region the estimated knee condition is in or which region the estimated knee condition is near by a marker superimposed on the map (Aubin teaches that the display indicates the knee ROM and the gait cycle analytics (i.e., region of the knee joint) that is affected by the abnormality of the gait (Figure 39B, para [0132, 0131)).
CLAIM 6-
Aubin in view of Agrawal teach the limitations of claim 1. Regarding claim 6, Aubin further teaches:
wherein the forces are pressures (Aubin teaches that the forces are pressure (para [0130]))
Claim(s) 7-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Aubin (US 2023/0022710 A1) in view of Agrawal (US 2020/0000373 A1) and further in view of Xiaoyi (CN 112329716 A)
CLAIM 7-
Claim 7 is significantly similar to claim 1 and is rejected upon the same prior art as claim 1. Claim 7 further recites “gait age”, “gait age score” and “gait condition” which is taught by Xiaoyi (abstract).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the patient condition and gait monitoring system of Aubin in view of Agrawal to integrate the application of monitoring gait age and scoring the gait of Xiaoyi to improve patient medical treatment (see: Xiaoyi, abstract).
CLAIMS 8-10-
Claims 8-10 are significantly similar to claims 4-6 and are rejected upon the same prior art as claims 8-10 respectively. Claims 8-10 further recite “gait age”, “gait age score” and “gait condition” which is taught by Xiaoyi (abstract).
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the patient condition and gait monitoring system of Aubin in view of Agrawal to integrate the application of monitoring gait age and scoring the gait of Xiaoyi to improve patient medical treatment (see: Xiaoyi, abstract).
Claim(s) 7-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Aubin (US 2023/0022710 A1) in view of Agrawal (US 2020/0000373 A1) and further in view of Borgue (US 10984893 B2).
CLAIM 2-
Aubin in view of Agrawal teach the limitations of claim 1. Regarding claim 2, Aubin in view of Agrawal does not explicitly teach, however Bogue teaches:
wherein the data on the knee condition of the data providers includes information on results of responses made by the data providers to a questionnaire about the knee condition (Bogue teaches the use of a questionnaire to assess knee pre-operative values (abstract))
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify the patient condition and gait monitoring system of Aubin in view of Agrawal to integrate the application of assessment knee condition questionnaire of Bogue to improve patient medical satisfaction (see: Bogue, abstract).
Conclusion
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/KIMBERLY A. SASS/Examiner, Art Unit 3686
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