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 .
Response to Arguments
Claims 1-14 and 17 are pending. Claims 1-14 and 17 are amended. Claims 15-16 are cancelled.
Applicant’s arguments, filed 05/08/2026, with respect to specification objections have been fully considered and are persuasive. The objections of the specification have been withdrawn.
Applicant’s arguments, filed 05/08/2026, with respect to claim objections 1-14 and 17 have been fully considered and are persuasive. The objections of Claims 1-14 and 17 have been withdrawn.
Applicant’s arguments, filed 05/08/2026, with respect to claim rejections under 35 U.S.C 112(b) for Claims 5-14 have been fully considered and are persuasive. The rejection of Claims 5-14 have been withdrawn. However, new 35 U.S.C 112(b) rejections are given for Claims 1-14 and 17 in light of applicant’s amendments.
Applicant’s arguments, filed 05/08/2026, with respect to claim rejections under 35
U.S.C 103 of Claims 1-14 and 17 are directed to the amended subject matter. A new
rejection under 35 U.S.C 103 is applied for Claims 1-14 and 17 under prior arts Gu (US 20160375306 A1) in view of Ten Kate (US 20150226764 A1) and Aibara (US 20140067096 A1) in response to Applicant’s amendments.
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, an output target determination unit, a comparison target setting unit, a comparison 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 the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 2-14 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 2-4 recite “classifies the plurality of measurement sections for each motion analysis index” in Claim 2 lines 2-3, Claim 3 lines 2-3, and Claim 4 lines 2-3. Neither the specification nor the drawings recite that the plurality of measurement sections for each motion analysis index is classified. Therefore, applicant has not demonstrated possession and the Claims are rejected under 35 U.S.C. 112(a). The specification recites in paragraph [0008] classifying measurement values in multiple measurement sections for each type of the motion analysis indices, and [0046] classifying index measurement values. Examiner recommends amending the claim language to be in line with the specification.
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 1-14 and 17 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.
Claims 1, 5-6, 9-14, and 17 recite “the motion analysis index” in Claim 1 lines 14, 16, and 22, Claim 5 lines 4 and 6, Claim 6 lines 4 and 6, Claim 9 lines 4 and 6, Claim 10 lines 4 and 6, Claim 11 lines 4, 5, and 7, Claim 12 lines 4, 5, and 7, Claim 13 lines 4-8, Claim 14 lines 4-8, and Claim 17 lines 12, 14, 16, and 19-20. Claim 1 lines 5-6 recite “at least one motion analysis index”, making it unclear which “motion analysis index” is being referred to in Claims 1, 5-6, 9-14, and 17, rendering these limitations in the claims as indefinite.
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
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 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gu (US 20160375306 A1) in view of Ten Kate (US 20150226764 A1) and 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 at least one motion analysis index 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 (i.e. at least one motion analysis index). 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 target determination unit that sets, as an output target for analysis and comparison, a motion analysis index of the at least one motion analysis index based on a user input indicating the motion analysis index (See Para[0063] “when a user enters a workout route or a specific target section, the electronic device 100 may notify that the workout route or the specific target section (for example, a target route) starts before entering. For example, the electronic device 100 (i.e. an output target determination unit) may provide a notification “1.6 km uphill section starts soon. Target passing time is 5 min””. Therefore, the electronic device 100 sets an output target of 5 minutes that is analyzed and compared, see Para[0064] “If the target route is completed, for example, when a user completes the 1.6 km uphill section in 5 min, in operation 213, the electronic device 100 may provide a screen or a comment for notifying reward or target accomplishment. If the target route is not completed, for example, when a user does not complete the 1.6 km uphill section or exceeds a time, in operation 215, the electronic device 100 may provide failure related feedback.” Therefore, a comparison of time is done, and a corresponding analysis is provided. The output target is a motion analysis index as the running motion state of the user is dependent on time, and the time completed is dependent on the user input via the running of the user (i.e. based on a user input indicating the motion analysis index).);
an output unit (See Fig. 1 the output module 150) that outputs the user interface (See Para[0054] “The output module 150 may correspond to hardware for outputting a performance result of the processing module 140.”). Gu is silent to the language of
a classification processing unit that classifies the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index, using a predetermined classification method for classification;
a comparison target setting unit that sets a reference value of a comparison target to be compared to the classified measurement values of the motion analysis index based on a user input indicating the reference value;
a comparison processing unit that compares the classified measurement values of the motion analysis index to the reference value of the comparison target;
a mode determination unit that determines a configuration of a user interface analyzing the run of the runner based on a result of the comparison processing unit comparing the classified measurement values of the motion analysis index to the reference value of the predetermined comparison target.
Ten Kate teaches
a classification processing unit (See Para[0025] “there is provided a computer program product comprising computer-readable code that, when executed on a suitable computer or processor (i.e. a classification processing unit), is configured to cause the computer or processor to perform the steps in the method described above”) that classifies the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index, using a predetermined classification method for classification (See Para[0061] “First, so-called clusters are identified (i.e. classifies the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index). Second, the maximum value in each cluster is identified as the step boundary. The clusters are found as the range of samples that are above a certain threshold (typically 2 ms.sup.-2 above gravity, i.e. .about.12 ms.sup.-2), where a small gap of samples not surpassing that threshold is permitted (typically 0.3 times a typical step time (which is around 0.5 seconds), i.e. 0.15 sec).” The clustering method is a predetermined classification method for classification, see also Fig. 4 where the data points above a threshold of 12 m/s2 are part of the clusters.) and
a comparison processing unit (See Para[0025] “there is provided a computer program product comprising computer-readable code that, when executed on a suitable computer or processor (i.e. a comparison processing unit), is configured to cause the computer or processor to perform the steps in the method described above”) that compares the classified measurement values of the motion analysis index to the reference value of the comparison target (See Para[0061] “Second, the maximum value in each cluster is identified as the step boundary. (i.e. compares the classified measurement values (via the clustering) of the motion analysis index to the reference value of the comparison target (via the maximum value).)” As this step happens after the clusters are identified, the classified measurement values themselves are compared via the identification of the maximum value, as the maximum value is larger than all the other values in the cluster by comparison.).
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 that classifies the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index, using a predetermined classification method for classification and a comparison processing unit that compares the classified measurement values of the motion analysis index to the reference value of the comparison target is used like in Ten Kate in order to efficiently classify and compare the measurement values of Gu to determine anomalous behaviors of the user.
Gu and Ten Kate are silent to the language of
a comparison target setting unit that sets a reference value of a comparison target to be compared to the classified measurement values of the motion analysis index based on a user input indicating the reference value and
a mode determination unit that determines a configuration of a user interface analyzing the run of the runner based on a result of the comparison processing unit comparing the classified measurement values of the motion analysis index to the reference value of the predetermined comparison target.
Aibara teaches
a comparison target setting unit (See Para[0095] “the input interface section 120”) that sets a reference value of a comparison target to be compared to the measurement values of the motion analysis index based on a user input indicating the reference value (See Para[0095] “ The upper-limit value (i.e. that sets a reference value of a comparison target), the lower-limit value, and the standard value in each of these numerical value ranges may be set by, for example, the user inputting a value (in advance) prior to the start of exercise motion (i.e. based on a user input indicating the reference value) by using the operation switch 121 or the touch panel 122 of the input interface section 120”. See also para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range (i.e. to be compared to the measurement values of the motion analysis index), the CPU 141 judges that this item has a problem) and
a mode determination unit that determines a configuration of a user interface analyzing the run of the runner based on a result of the comparison processing unit comparing the measurement values of the motion analysis index to the reference value of the predetermined comparison target (See Para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 (i.e. a mode determination unit and a classification processing unit as the CPU 141 classifies the pace, pitch, and stride as either having a problem or not) judges that this item has a problem (i.e. based on a result of the comparison processing unit comparing the measurement values of the motion analysis index (that of the pace, the pitch, and the stride) to the reference value of the predetermined comparison target (the predetermined comparison target is the numerical value range for either the pace, pitch, or stride that is compared, and the reference value is the upper bound of this numerical value range.)), 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 (i.e. a mode determination unit (the CPU 141) that determines a configuration of a user interface analyzing the run of the runner).” See also 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 comparison target setting unit that sets a reference value of a comparison target to be compared to the measurement values of the motion analysis index based on a user input indicating the reference value and a mode determination unit that determines a configuration of a user interface analyzing the run of the runner based on a result of the comparison processing unit comparing the measurement values of the motion analysis index to the reference value of the predetermined comparison target is used like in Aibara in order to have more user interaction via the comparison target setting unit to set the threshold value in Ten Kate to compare to the classified measurement values of Ten Kate and to have an automated output of the type of relevant information about the performance of a user via the mode determination unit.
With respect to Claim 2, Gu, Ten Kate, and Aibara teach the limitations of Claim 1. Gu is silent to the language of
the classification processing unit classifies the plurality of measurement sections for each motion analysis index using a predetermined classification method for performing classification by a degree of approximation between measurement values for each motion analysis index of the at least one motion analysis index.
Ten Kate teaches
the classification processing unit classifies the plurality of measurement sections for each motion analysis index using a predetermined classification method for performing classification by a degree of approximation between measurement values for each motion analysis index of the at least one motion analysis index (See Para[0025] “there is provided a computer program product comprising computer-readable code that, when executed on a suitable computer or processor (i.e. a classification processing unit), is configured to cause the computer or processor to perform the steps in the method described above”. See also para[0014] “identifying a step boundary comprises identifying clusters of contiguous measurements (i.e. classifies the plurality of measurement sections for each motion analysis index, as the clusters are classifications for the measurements, which are in a plurality of measurement sections as there are contiguous measurements, and the measurements themselves are motion analysis indices as they are gait parameters, See Abstract) in the collected measurements in which the magnitude of each of the measurements exceeds a threshold, apart from a subset of the measurements whose magnitude is less than the threshold, provided that the subset covers a time period less than a time threshold”. The identification of the clusters is the predetermined classification method for classification, and since the measurement values are clustered together, they are classified by a degree of approximation for each of the measurement values as well.)
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 the plurality of measurement sections for each motion analysis index using a predetermined classification method for performing classification by a degree of approximation between measurement values for each motion analysis index of the at least one motion analysis index like in Ten Kate in order for a more accurate analysis of the running state of a runner as the classification scheme takes into account the proximity of related measurement values.
With respect to Claim 3, Gu, Ten Kate, and Aibara teach the limitations of Claim 2. Gu is silent to the language of
the classification processing unit classifies the plurality of measurement sections for each motion analysis index based on a range obtained using an average value and a standard deviation of measurement values for each motion analysis index of the at least one motion analysis index.
Ten Kate teaches
the classification processing unit classifies the plurality of measurement sections for each motion analysis index (See Para[0025] “there is provided a computer program product comprising computer-readable code that, when executed on a suitable computer or processor (i.e. a classification processing unit), is configured to cause the computer or processor to perform the steps in the method described above”. See also para[0014] “identifying a step boundary comprises identifying clusters of contiguous measurements (i.e. classifies the plurality of measurement sections for each motion analysis index, as the clusters are classifications for the measurements, which are in a plurality of measurement sections as there are contiguous measurements, and the measurements themselves are motion analysis indices as they are gait parameters, See Abstract)”) based on a range obtained using an average value and a standard deviation of measurement values for each motion analysis index of the at least one motion analysis index (See Para[0047] “the comparison (i.e. classification) between the estimated values and the normal values is weighted according to the standard deviation of the normal gait parameter values”. The gait parameter values are the motion analysis indices as they dictate the motion of the 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.” The range is defined by the standard deviation and the mean of the gait parameter values.)
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 the plurality of measurement sections for each motion analysis index based on a range obtained using an average value and a standard deviation of measurement values for each motion analysis index of the at least one motion analysis index like in Ten Kate in order to implement a more efficient process to identify outliers in measurement data for subsequent running analysis of a user (See Ten Kate Para[0045] “A method of determining a dynamic risk of falling is shown in FIG. 3.”).
With respect to Claim 4, Gu, Ten Kate, and Aibara teach the limitations of Claim 2. Gu is silent to the language of
the classification processing unit classifies the plurality of measurement sections for each motion analysis index by cluster analysis for each motion analysis index of the at least one motion analysis index.
Ten Kate teaches
the classification processing unit classifies the plurality of measurement sections for each motion analysis index (See Para[0025] “there is provided a computer program product comprising computer-readable code that, when executed on a suitable computer or processor (i.e. a classification processing unit), is configured to cause the computer or processor to perform the steps in the method described above”. See also para[0014] “identifying a step boundary comprises identifying clusters of contiguous measurements (i.e. classifies the plurality of measurement sections for each motion analysis index, as the clusters are classifications for the measurements, which are in a plurality of measurement sections as there are contiguous measurements, and the measurements themselves are motion analysis indices as they are gait parameters, See Abstract)”) by cluster analysis for each motion analysis index of the at least one motion analysis index (See Para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements in the collected measurements”. Since the clusters identify a step boundary, Ten Kate applies cluster analysis for the motion analysis index of steps.).
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 the plurality of measurement sections for each motion analysis index by cluster analysis for each motion analysis index of the at least one motion analysis index like in Ten Kate in order to implement a more efficient process to identify outliers in measurement data for subsequent running analysis of a user.
With respect to Claims 5 and 6, Gu, Ten Kate, and Aibara teach the limitations of Claims 1 and 2, respectively. Gu is silent to the language of
the mode determination unit determines the configuration of the user interface analyzing the run of the runner such that a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Aibara teaches
the mode determination unit determines the configuration of the user interface analyzing the run of the runner (See Para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 (i.e. a mode determination unit) 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 (i.e. a mode determination unit (the CPU 141) that determines a configuration of a user interface analyzing the run of the runner).” See also 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 and Ten Kate wherein the mode determination unit determines the configuration of the user interface analyzing the run of the runner such as that of Aibara in order to implement a more efficient way to determine how to output certain exercise data that is relevant for the given user.
Gu and Aibara are silent to the language of
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Ten Kate teaches
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index. (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 (i.e. a measurement in such a cluster would contain a first measurement value of the classified measurement values of the motion analysis index.), apart from a subset of the measurements whose magnitude is less than the threshold (i.e. distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index)”. The change that meets a predetermined change condition is the change in the values of the measurements in the cluster that exceed the threshold versus the measurements in the clusters that are less than the threshold, where the threshold is the predetermined change condition. In addition, both the first and second measurements are classified as they are part of clusters, and they are 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.” All of these are motion analysis indices as they dictate the running motion state of the user.).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu and Aibara wherein a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index such as that of Ten Kate in order for implementing a more efficient process to identify outliers in measurement data for subsequent running analysis of a user.
With respect to Claims 7 and 8, Gu, Ten Kate, and Aibara teach the limitations of Claims 1 and 2, respectively. Gu further teaches
the output target determination unit sets, as the output target for analysis and comparison, two or more motion analysis indices among the at least one of motion analysis index (See Para[0063] “when a user enters a workout route or a specific target section, the electronic device 100 may notify that the workout route or the specific target section (for example, a target route) starts before entering. For example, the electronic device 100 (i.e. an output target determination unit) may provide a notification “1.6 km uphill section starts soon. Target passing time is 5 min””. Both the 1.6 km and the 5 min serve as two or more motion analysis indices among the at least one of motion analysis index as they indicate the running state of the user and they are both identified and set by the electronic device 100.).
Gu is silent to the language of
the mode determination unit determines the configuration of the user interface analyzing the run of the runner such that a first motion analysis index of two or more motion analysis indices in which a change that meets a predetermined change condition has been detected is distinguished from second motion analysis indices other than the first motion analysis index of the two or more motion analysis indices.
Aibara teaches
the mode determination unit determines the configuration of the user interface analyzing the run of the runner (See Para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 (i.e. a mode determination unit) 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 (i.e. a mode determination unit (the CPU 141) that determines a configuration of a user interface analyzing the run of the runner).” See also 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 and Ten Kate wherein the mode determination unit determines the configuration of the user interface analyzing the run of the runner such as that of Aibara in order to implement a more efficient way to determine how to output certain exercise data that is relevant for the given user.
Gu and Aibara are silent to the language of
a first motion analysis index of two or more motion analysis indices in which a change that meets a predetermined change condition has been detected is distinguished from second motion analysis indices other than the first motion analysis index of the two or more motion analysis indices.
Ten Kate teaches
a first motion analysis index of two or more motion analysis indices in which a change that meets a predetermined change condition has been detected is distinguished from second motion analysis indices other than the first motion analysis index of the two or more 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.” A first motion analysis index of two or more motion analysis indices and second motion analysis indices other than the first motion analysis index of the two or more motion analysis indices is a bisection of the set of gait parameters, see Para[0043] “Gait parameters can include measures such as step size (e.g. a first motion analysis index), step width, step time, double support time (i.e. the time that both feet are in contact with the ground), gait velocity, and cadence. (e.g. the rest are second motion analysis indices)” The threshold is the predetermined change condition, and a change of “a” such that the value drops to below the threshold is the change that meets a predetermined change condition that has been detected. The individual values between 0 and 1 for each gait parameter is distinguished as they belong to different gait parameters.).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu and Aibara wherein a first motion analysis index of two or more motion analysis indices in which a change that meets a predetermined change condition has been detected is distinguished from second motion analysis indices other than the first motion analysis index of the two or more motion analysis indices such as that of Ten Kate, 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 Claims 9 and 10, Gu, Ten Kate, and Aibara teach the limitations of Claims 1 and 2, respectively. Gu is silent to the language of
the mode determination unit determines the configuration of the user interface analyzing the run of the runner such that a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a change condition specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Aibara teaches
the mode determination unit determines the configuration of the user interface analyzing the run of the runner (See Para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 (i.e. a mode determination unit) 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 (i.e. a mode determination unit (the CPU 141) that determines a configuration of a user interface analyzing the run of the runner).” See also 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 and Ten Kate wherein the mode determination unit determines the configuration of the user interface analyzing the run of the runner such as that of Aibara in order to implement a more efficient way to determine how to output certain exercise data that is relevant for the given user.
Gu and Aibara are silent to the language of
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a change condition specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Ten Kate teaches
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a change condition specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index (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.” Therefore, a first measurement value is the measurement “a” that generates a value of 1 which is distinguished from the second measurement values, which are the measurements “a” that generates any value less than 0.7. The threshold is the change condition, and a change of “a” such that the value drops to below the threshold is the change that meets the change condition that has been detected. The values of 0 to 1 are user dependent, and the threshold is determined based on the user’s performance via the mean and standard deviation from a calibration step, see para[0046] “The normal or usual values for the gait parameters can be obtained during a calibration session before the fall prevention device 2 is used (for example the user 4 can wear the fall prevention device 2 while it is in a calibration mode, and the fall prevention device 2 can determine values for each gait parameter while the user 4 is walking normally).” Therefore a change condition specified by the user is done.). Examiner notes that the measurement value “a” is classified before the steps mentioned in Paras[0046]-[0049], see Fig. 4 step 103, which involves classifying the measurement values (See Para[0055] “In order to obtain an estimate of the step size, a number of processing steps are required. In particular, it is necessary to estimate the step boundaries” and para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu and Aibara wherein a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a change condition specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index like in Ten Kate in order to implement a more efficient process to identify outliers in the measurement values for subsequent running analysis of a user.
With respect to Claims 11 and 12, Gu, Ten Kate, and Aibara teach the limitations of Claims 1 and 2, respectively. Gu is silent to the language of
the mode determination unit determines the configuration of the user interface analyzing the run of the runner such that a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Aibara teaches
the mode determination unit determines the configuration of the user interface analyzing the run of the runner (See Para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 (i.e. a mode determination unit) 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 (i.e. a mode determination unit (the CPU 141) that determines a configuration of a user interface analyzing the run of the runner).” See also 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 and Ten Kate wherein the mode determination unit determines the configuration of the user interface analyzing the run of the runner such as that of Aibara in order to implement a more efficient way to determine how to output certain exercise data that is relevant for the given user.
Gu and Aibara are silent to the language of
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Ten Kate teaches
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index (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.” Therefore, a first measurement value is the measurement “a” that generates a value of 1 which is distinguished from the second measurement values, which are the measurements “a” that generates any value less than 0.7. The threshold of .7 is the predetermined change condition, and a change of “a” such that the value drops to below .7 is the change that meets a predetermined change condition that has been detected. Since the values of 0 to 1 and .7 are pre-set, the change condition of a measurement value going below .7 is predetermined. The gait is a motion analysis index as it determines the motion of the user, so it is specified by the user as well. Examiner notes that the measurement value “a” is classified before the steps mentioned in Paras[0046] - [0049], see Fig. 4 step 103, which involves classifying the measurement values (See Para[0055] “In order to obtain an estimate of the step size, a number of processing steps are required. In particular, it is necessary to estimate the step boundaries” and para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu and Aibara wherein a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index like in Ten Kate in order to implement a more efficient and predefined process to identify outliers in the measurement values for subsequent running analysis of a user.
With respect to Claims 13 and 14, Gu, Ten Kate, and Aibara teach the limitations of Claims 1 and 2, respectively. Gu further teaches
the motion analysis index specified by the user (See Para[0064] “If the target route is completed, for example, when a user completes the 1.6 km uphill section in 5 min, in operation 213, the electronic device 100 may provide a screen or a comment for notifying reward or target accomplishment. If the target route is not completed, for example, when a user does not complete the 1.6 km uphill section or exceeds a time, in operation 215, the electronic device 100 may provide failure related feedback.”).
Gu is silent to the language of
the mode determination unit determines the configuration of the user interface analyzing the run of the runner such that a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in a measurement section among the measurement sections of the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Aibara teaches
the mode determination unit determines the configuration of the user interface analyzing the run of the runner (See Para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range, the CPU 141 (i.e. a mode determination unit) 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 (i.e. a mode determination unit (the CPU 141) that determines a configuration of a user interface analyzing the run of the runner).” See also 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 and Ten Kate wherein the mode determination unit determines the configuration of the user interface analyzing the run of the runner such as that of Aibara in order to implement a more efficient way to determine how to output certain exercise data that is relevant for the given user.
Gu and Aibara are silent to the language of
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in a measurement section among the measurement sections of the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index.
Ten Kate teaches
a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in a measurement section among the measurement sections of the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index (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.” Therefore, a first measurement value is the measurement “a” that generates a value of 1 which is distinguished from the second measurement values other than the first measurement value of the classified measurement values of the motion analysis index, which are the measurements “a” that generates any value less than the threshold. The threshold is the predetermined change condition, and a change of “a” such that the value drops to below the threshold is the change that meets the change condition that has been detected. The values of 0 to 1 are user dependent, and the threshold is determined based on the user’s performance via the mean and standard deviation from a calibration step, see para[0046] “The normal or usual values for the gait parameters can be obtained during a calibration session before the fall prevention device 2 is used (for example the user 4 can wear the fall prevention device 2 while it is in a calibration mode, and the fall prevention device 2 can determine values for each gait parameter while the user 4 is walking normally).” Therefore, a predetermined change condition specified by the user is done.). Examiner notes that the measurement value “a” is classified before the steps mentioned in Paras[0046]-[0049], see Fig. 4 step 103, which involves classifying the measurement values (See Para[0055] “In order to obtain an estimate of the step size, a number of processing steps are required. In particular, it is necessary to estimate the step boundaries” and para[0014] “the step of identifying a step boundary comprises identifying clusters of contiguous measurements”) In addition, since the measurements are contiguous, the measurement sections are defined by the contiguous measurements, and the corresponding change that meets a predetermined change condition happens within one of the measurement sections.).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu and Aibara wherein a first measurement value of the classified measurement values of the motion analysis index in which a change that meets a predetermined change condition in a measurement section among the measurement sections of the motion analysis index specified by the user has been detected is distinguished from second measurement values other than the first measurement value of the classified measurement values of the motion analysis index such as that of Ten Kate in order to implement a more efficient process of identifying outlier measurement values for subsequent analysis of a running profile of a runner.
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 at least one motion analysis index 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 (i.e. at least one motion analysis index). 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;
setting, as an output target for analysis and comparison, a motion analysis index of the at least one motion analysis index based on a user input indicating the motion analysis index (See Para[0063] “when a user enters a workout route or a specific target section, the electronic device 100 may notify that the workout route or the specific target section (for example, a target route) starts before entering. For example, the electronic device 100 may provide a notification “1.6 km uphill section starts soon. Target passing time is 5 min””. Therefore the electronic device 100 sets an output target of 5 minutes that is analyzed and compared, see Para[0064] “If the target route is completed, for example, when a user completes the 1.6 km uphill section in 5 min, in operation 213, the electronic device 100 may provide a screen or a comment for notifying reward or target accomplishment. If the target route is not completed, for example, when a user does not complete the 1.6 km uphill section or exceeds a time, in operation 215, the electronic device 100 may provide failure related feedback.” Therefore, a comparison of time is done, and a corresponding analysis is provided. The output target is a motion analysis index as the running motion state of the user is dependent on time, and the time completed is dependent on the user input via the running of the user (i.e. based on a user input indicating the motion analysis index).);
outputting the user interface (See Para[0054] “The output module 150 may correspond to hardware for outputting a performance result of the processing module 140.”).
Gu is silent to the language of
classifying the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index, using a predetermined classification method for classification;
setting a reference value of a comparison target to be compared to the classified measurement values of the motion analysis index based on a user input indicating the reference value;
comparing the classified measurement values of the motion analysis index to the reference value of the comparison target;
determining a configuration of a user interface analyzing the run of the runner based on a result of the comparing of the classified measurement values of the motion analysis index to the comparison target.
Ten Kate teaches
classifying the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index, using a predetermined classification method for classification (See Para[0014] “identifying a step boundary comprises identifying clusters of contiguous measurements (i.e. classifying the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index, as the clusters are classifications for the measurements, which are in a plurality of measurement sections as there are contiguous measurements, and the measurements themselves are motion analysis indices as they are gait parameters, See Abstract) in the collected measurements in which the magnitude of each of the measurements exceeds a threshold, apart from a subset of the measurements whose magnitude is less than the threshold, provided that the subset covers a time period less than a time threshold”. The identification of the clusters is the predetermined classification method for classification.) and
comparing the classified measurement values of the motion analysis index to the reference value of the comparison target (See Para[0014] “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, apart from a subset of the measurements whose magnitude is less than the threshold (i.e. comparing the classified measurement values (via the clustering) of the motion analysis index to the reference value of the comparison target), provided that the subset covers a time period less than a time threshold”).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Gu wherein classifying the measurement values in a plurality of measurement sections for each motion analysis index of the at least one motion analysis index, using a predetermined classification method for classification and comparing the classified measurement values of the motion analysis index to the reference value of the comparison target is done like in Ten Kate in order to efficiently classify and compare the measurement values of Gu to determine anomalous behaviors of the user.
Gu and Ten Kate are silent to the language of
setting a reference value of a comparison target to be compared to the classified measurement values of the motion analysis index based on a user input indicating the reference value and
determining a configuration of a user interface analyzing the run of the runner based on a result of the comparing of the classified measurement values of the motion analysis index to the comparison target.
Aibara teaches
setting a reference value of a comparison target to be compared to the measurement values of the motion analysis index based on a user input indicating the reference value (See Para[0095] “ The upper-limit value (i.e. setting a reference value of a comparison target), the lower-limit value, and the standard value in each of these numerical value ranges may be set by, for example, the user inputting a value (in advance) prior to the start of exercise motion (i.e. based on a user input indicating the reference value) by using the operation switch 121 or the touch panel 122 of the input interface section 120”. See also para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range (i.e. to be compared to the measurement values of the motion analysis index), the CPU 141 judges that this item has a problem”.) and
determining a configuration of a user interface analyzing the run of the runner based on a result of the comparing of the measurement values of the motion analysis index to the comparison target (See Para[0109] “Then, when judged that one of the pace, the pitch, and the stride has exceeded the set numerical value range (i.e. comparing of the measurement values of the motion analysis index to the comparison target (which is the 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 (i.e. determining a configuration of a user interface analyzing the run of the runner based on a result of the comparing).” 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 setting a reference value of a comparison target to be compared to the measurement values of the motion analysis index based on a user input indicating the reference value and determining a configuration of a user interface analyzing the run of the runner based on a result of the comparing of the measurement values of the motion analysis index to the comparison target is done like in Aibara in order to have more user interaction via setting the threshold value in Ten Kate to compare to the classified measurement values of Ten Kate and to have an automated output of the type of relevant information about the performance of a user via the mode determination unit.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOSTOFA AHMED HISHAM whose telephone number is (571)272-8773. The examiner can normally be reached Monday - Thursday, 7:00 a.m. - 4 p.m. ET, Friday 7:00 a.m. - 3 p.m. ET. Every other Friday off.
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/MOSTOFA AHMED HISHAM/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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