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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 8/30/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
The information disclosure statement (IDS) submitted on 2/12/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The disclosure is objected to because of the following informalities:
Paras[0029], [0036], [0037], and [0040] recite “measurement device 20”.
The objection can be overcome by replacing “measurement device 20” with “information terminal 50”. “Measurement device 20” does not contain “information acquirer 30” as recited
Paras[0059], [0060], and [0061] recite “column”.
The objection can be overcome by replacing “column” with “box”.
Appropriate correction is required.
Claim Objections
Claims 1-17 are objected to because of the following informalities:
Claim 1 is objected to because of the following informalities: In line 13 “measurement values” should be – the measurement values - .
Claim 2 is objected to because of the following informalities: In line 4 “the degree of approximation” should be – a degree of approximation - .
Claims that depend on the above objected claims are also objected to.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
In Claim 1,
an information acquirer which has the corresponding structure of a measurement device see Para[0012] of the instant application.
a measurement value acquirer which has the corresponding structure of a measurement device see Para[0012] of the instant application.
a classification processing unit, a mode determination unit, and an output unit which have the corresponding structure of computer server elements see Paras[0017] and [0020] of the instant application.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 5-14 and 16 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 5-6 and 9-14 recite “other measurement values”. It is not clear what “other measurement values” is with respect to, rendering these claims indefinite.
Claims 7-8 recite “other motion analysis indices”. It is not clear what “other motion analysis indices” is with respect to, rendering these claims indefinite.
Claim 16 recites “the classified measurement values”. Claim 1 recites “classifies measurement values” and claim 2 recites “classifies a measurement value”, hence there is insufficient antecedent basis for this limitation in the claim.
Claims that depend on the above rejected claims are also rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gu (US 20160375306 A1) in view of Aibara (US 20140067096 A1).
With respect to Claim 1, Gu teaches
A running analysis system (See Abstract), comprising:
an information acquirer that acquires position information and motion information of a user as a runner, measured at each point of passage in a run by a predetermined measurement device (See Para[0080] “For example, an acceleration sensor may measure a user's motion and the number of user's steps at the same time.” and Para[0045] “Referring to FIG. 1, a user runs in an execution state of a health application of the electronic device 100, user's location information may be collected continuously by using a GPS 110” and Para[0142] “workout such as cycling or running”);
a measurement value acquirer (See Fig. 1 the electronic device 100) that acquires measurement values of a plurality of types of motion analysis indices indicating a running motion state of the user (See Para[0073] “By utilizing information detected through such a sensor, the electronic device 100 may identify user's current workout time, distance, speed, elevation, and location. The identified information may be utilized to obtain the maximum speed, an average speed, a calorie consumption amount, an average/maximum pace, the maximum elevation, an elevation gain, a total uphill section, and a total downhill section.”) for each predetermined unit measurement section, based on the position information and the motion information chronologically consecutive;
an output unit (See Fig. 1 the output module 150) that is capable of outputting at least information regarding the classified measurement values, based on the determined output mode (See Para[0054] “The output module 150 may correspond to hardware for outputting a performance result of the processing module 140.”). However, Gu is silent to the language of
a classification processing unit that classifies measurement values in a plurality of measurement sections for each type of the motion analysis indices, using a predetermined classification method for classification by property; a mode determination unit that determines an output mode of the classified measurement values based on comparison with a predetermined comparison target;
Nevertheless, Aibara teaches
a classification processing unit (See Para[0092] “the CPU 141 judges whether the relevant item is out of the numerical value range in a movement distance range”) that classifies measurement values in a plurality of measurement sections for each type of the motion analysis indices (See Para[0091] “In FIG. 4, the straight line La is a pace reference line indicating a relation between pitch and stride when a section distance of 5 km is moved at a pace of nineteen minutes”), using a predetermined classification method for classification by property (See Para[109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 judges that this item has a problem, and thereby causes character information including the numerical value of this item to be displayed on the display section 131 and performs caution display or alert display to prompt the user US to improve the running style.”);
a mode determination unit (See Para[109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 judges that this item has a problem, and thereby causes character information including the numerical value of this item to be displayed on the display section 131 and performs caution display or alert display to prompt the user US to improve the running style.”) that determines an output mode of the classified measurement values based on comparison with a predetermined comparison target (See Fig. 7A-7D the display section 131 and the corresponding values outputted).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein a classification processing unit, using a predetermined classification method for classification by property, and a mode determination unit that determines an output mode of the classified measurement values based on comparison with a predetermined comparison target is used such as that of Aibara.
One of ordinary skill would have been motivated to modify Gu because Aibara teaches a classification processing unit and a corresponding method to classify measurement values in a predetermined unit measurement section that can allow for more precise and analytical control of the measurement values when they get classified, and Aibara also teaches a mode determination unit along with a corresponding output unit to display the output mode of the classified measurement values based on a comparison of the classified measurement values to a preset range of values, which will allow for a more efficient way to determine how to output certain exercise data that is relevant for the given user.
With respect to Claim 17, Gu teaches
A running analysis method (See Abstract), comprising:
acquiring position information and motion information of a user as a runner, measured at each point of passage in a run by a predetermined measurement device (See Para[0080] “For example, an acceleration sensor may measure a user's motion and the number of user's steps at the same time.”);
acquiring measurement values of a plurality of types of motion analysis indices indicating a running motion state of the user (See Para[0073] “By utilizing information detected through such a sensor, the electronic device 100 may identify user's current workout time, distance, speed, elevation, and location. The identified information may be utilized to obtain the maximum speed, an average speed, a calorie consumption amount, an average/maximum pace, the maximum elevation, an elevation gain, a total uphill section, and a total downhill section.”) for each predetermined unit measurement section (See Para[0058] “ In operation 203, the electronic device 100 may determine a plurality of workout sections based on the workout route data and the user profile.”), based on the position information and the motion information chronologically consecutive;
outputting at least information regarding the classified measurement values, based on the determined output mode (See Para[0054] “The output module 150 may correspond to hardware for outputting a performance result of the processing module 140.”).
However, Gu is silent to the language of
classifying measurement values in a plurality of measurement sections for each type of the motion analysis indices, using a predetermined classification method for classification by property; determining an output mode of the classified measurement values based on comparison with a predetermined comparison target;
Nevertheless, Aibara teaches
classifying measurement values in a plurality of measurement sections for each type of the motion analysis indices (See Para[0091] “In FIG. 4, the straight line La is a pace reference line indicating a relation between pitch and stride when a section distance of 5 km is moved at a pace of nineteen minutes”), using a predetermined classification method for classification by property (See Para[109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 judges that this item has a problem, and thereby causes character information including the numerical value of this item to be displayed on the display section 131 and performs caution display or alert display to prompt the user US to improve the running style.”);
determining an output mode of the classified measurement values based on comparison with a predetermined comparison target (See Para[109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 judges that this item has a problem, and thereby causes character information including the numerical value of this item to be displayed on the display section 131 and performs caution display or alert display to prompt the user US to improve the running style.” and Fig. 7A-7D the display section 131 and the corresponding values outputted).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein classifying measurement values in a plurality of measurement sections for each type of the motion analysis indices, using a predetermined classification method for classification by property and determining an output mode of the classified measurement values based on comparison with a predetermined comparison target is done such as that of Aibara.
One of ordinary skill would have been motivated to modify Gu because Aibara teaches a method to classify measurement values in a predetermined unit measurement section that can allow for more precise and analytical control of the measurement values when they get classified, and Aibara also teaches a method to display the output mode of the classified measurement values based on a comparison of the classified measurement values to a preset range of values, which will allow for a more efficient way to determine how to output certain exercise data that is relevant for the given user.
Claim(s) 2-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gu as applied to claim 1 above, and further in view of Ten Kate (US 20150226764 A1).
With respect to Claim 2, Gu is silent to the language of
The running analysis system according to claim 1, wherein the classification processing unit classifies a measurement value using a predetermined classification method for performing classification by the degree of approximation between measurement values for each type of the motion analysis indices.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 1, wherein the classification processing unit classifies a measurement value using a predetermined classification method for performing classification by the degree of approximation between measurement values (See Para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements in the collected measurements”) for each type of the motion analysis indices (See Para[0043] “Gait parameters can include measures such as step size, step width, step time, double support time (i.e. the time that both feet are in contact with the ground), gait velocity, and cadence.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the classification processing unit classifies a measurement value using a predetermined classification method for performing classification by the degree of approximation between measurement values for each type of the motion analysis indices such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to classify measurement values through the degree of approximation between measurement values, which will in turn allow for a more accurate analysis of the running state of a runner.
With respect to Claim 3, Gu is silent to the language of
The running analysis system according to claim 2, wherein the classification processing unit classifies a measurement value based on a range obtained using an average value and the standard deviation of measurement values for each type of the motion analysis indices.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, wherein the classification processing unit classifies a measurement value based on a range obtained using an average value and the standard deviation of measurement values for each type of the motion analysis indices (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the classification processing unit classifies a measurement value based on a range obtained using an average value and the standard deviation of measurement values for each type of the motion analysis indices such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to classify measurement values using a range defined by the mean and standard deviation, which will allow for a more efficient process to identify outliers in measurement data for subsequent running analysis of a user.
With respect to Claim 4, Gu is silent to the language of
The running analysis system according to claim 2, wherein the classification processing unit classifies a measurement value by cluster analysis for each type of the motion analysis indices.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, wherein the classification processing unit classifies a measurement value by cluster analysis for each type of the motion analysis indices (See Para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements in the collected measurements”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the classification processing unit classifies a measurement value by cluster analysis for each type of the motion analysis indices such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to classify measurement values using cluster analysis, which will allow for a more efficient process to identify outliers in measurement data for subsequent running analysis of a user.
With respect to Claim 5, Gu is silent to the language of
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition has been detected is distinguished from other measurement values (See Para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements in the collected measurements”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by observing when a measurement exceeds a threshold through cluster analysis, which will allow for a more efficient process to identify outliers in measurement data for subsequent running analysis of a user.
With respect to Claim 6, Gu is silent to the language of
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition has been detected is distinguished from other measurement values (See Para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements in the collected measurements”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by observing when a measurement exceeds a threshold through cluster analysis, which will allow for a more efficient process to identify outliers in measurement data for subsequent running analysis of a user.
With respect to Claim 7, Gu is silent to the language of
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from other motion analysis indices.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from other motion analysis indices (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from other motion analysis indices such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish motion analysis indices by observing when the observed parameter value exceeds a threshold through calculating the standard deviation and mean of the set of parameter values, which will allow for a more efficient process to identify outliers in the motion analysis indices for subsequent running analysis of a user.
With respect to Claim 8, Gu is silent to the language of
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from other motion analysis indices.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from other motion analysis indices (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from other motion analysis indices such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish motion analysis indices by observing when the observed parameter value exceeds a threshold through calculating the standard deviation and mean of the set of parameter values, which will allow for a more efficient process to identify outliers in the motion analysis indices for subsequent running analysis of a user.
With respect to Claim 9, Gu is silent to the language of
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a change condition specified by a user has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a change condition specified by a user has been detected is distinguished from other measurement values (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a change condition specified by a user has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by observing when the measurement value (interpreted as observed parameter value a in the instant application) exceeds a threshold through calculating the standard deviation and mean of the set of measurement values, which will allow for a more efficient process to identify outliers in the measurement values for subsequent running analysis of a user.
With respect to Claim 10, Gu is silent to the language of
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a change condition specified by a user has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a change condition specified by a user has been detected is distinguished from other measurement values (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a change condition specified by a user has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by observing when the measurement value (interpreted as observed parameter value a in the instant application) exceeds a threshold through calculating the standard deviation and mean of the set of measurement values, which will allow for a more efficient process to identify outliers in the measurement values for subsequent running analysis of a user.
With respect to Claim 11, Gu is silent to the language of
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a motion analysis index specified by a user has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 1, The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a motion analysis index specified by a user has been detected is distinguished from other measurement values (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a motion analysis index specified by a user has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by observing when the motion analysis index (here interpreted to be a - μ) exceeds a threshold through calculating the standard deviation and mean of the set of parameter values a (here interpreted as the measurement values), which will allow for a more efficient process to identify outliers in the measurement values for subsequent running analysis of a user.
With respect to Claim 12, Gu is silent to the language of
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a motion analysis index specified by a user has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a motion analysis index specified by a user has been detected is distinguished from other measurement values (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a motion analysis index specified by a user has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by observing when the motion analysis index (here interpreted to be a - μ) exceeds a threshold through calculating the standard deviation and mean of the set of parameter values a (here interpreted as the measurement values), which will allow for a more efficient process to identify outliers in the measurement values for subsequent running analysis of a user.
With respect to Claim 13, Gu is silent to the language of
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a measurement section specified by a user has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 1, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a measurement section specified by a user has been detected is distinguished from other measurement values (See Para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements in the collected measurements in which the magnitude of each of the measurements exceeds a threshold.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a measurement section specified by a user has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by using cluster analysis to define which measurement values exceed a threshold (which is interpreted as a predetermined change condition specified by a user) in a measurement section (which is interpreted as the clusters). Doing this will allow for an efficient process of identifying outlier measurement values for subsequent analysis of a running profile of a runner.
With respect to Claim 14, Gu is silent to the language of
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a measurement section specified by a user has been detected is distinguished from other measurement values.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a measurement section specified by a user has been detected is distinguished from other measurement values (See Para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements in the collected measurements in which the magnitude of each of the measurements exceeds a threshold.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines the output mode such that a measurement value in which a change that meets a predetermined change condition in a measurement section specified by a user has been detected is distinguished from other measurement values such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches a method to distinguish measurement values by using cluster analysis to define which measurement values exceed a threshold (which is interpreted as a predetermined change condition specified by a user) in a measurement section (which is interpreted as the clusters). Doing this will allow for an efficient process of identifying outlier measurement values for subsequent analysis of a running profile of a runner.
With respect to Claim 15, Gu is silent to the language of
The running analysis system according to claim 1, wherein the mode determination unit determines an output mode of the classified measurement values based on comparison with a comparison target specified by a user.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 1, wherein the mode determination unit determines an output mode of the classified measurement values based on comparison with a comparison target specified by a user (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines an output mode of the classified measurement values based on comparison with a comparison target specified by a user such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches an output mode of the classified measurement values which are based on comparison with a comparison target specified by a user (which is the user-defined threshold), which will allow for a more efficient process of identifying outliers in the classified measurement values for subsequent running analysis of a user.
With respect to Claim 16, Gu is silent to the language of
The running analysis system according to claim 2, wherein the mode determination unit determines an output mode of the classified measurement values based on comparison with a comparison target specified by a user.
Nevertheless, Ten Kate teaches
The running analysis system according to claim 2, wherein the mode determination unit determines an output mode of the classified measurement values based on comparison with a comparison target specified by a user (See Para[0048] “if μ represents the calibration mean (i.e. the mean of the normal values for a particular parameter), σ represents the standard deviation in that calibration mean, and a represents the currently observed parameter value, a deviation is signaled if |a – μ|/ σ exceeds a threshold.” and Para[0049] “For example, exp[-(a- μ)2/2σ2] maps to a value between 0 and 1, where 1 indicates normal gait (for that user), and a deviation from normal gait is signaled (i.e. the user is at a higher risk of falling) if the result falls below a threshold, for example 0.7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein the mode determination unit determines an output mode of the classified measurement values based on comparison with a comparison target specified by a user such as that of Ten Kate.
One of ordinary skill would have been motivated to modify Gu because Ten Kate teaches an output mode of the classified measurement values which are based on comparison with a comparison target specified by a user (which is the threshold), which will allow for a more efficient process of identifying outliers in the classified measurement values for subsequent running analysis of a user.
Conclusion
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/MOSTOFA AHMED HISHAM/Examiner, Art Unit 2863
/YOSHIHISA ISHIZUKA/Primary Examiner, Art Unit 2863