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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/26/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/30/2026 was filed after the mailing date of the Final Rejection on 02/06/2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendment
Applicant’s amendment filed 06/26/2026 has been entered. Claims 1-20 remain pending. Examiner notes that due to the amendments changing the scope of the claims, a new grounds of rejection under 35 U.S.C. 103 is presented.
Response to Arguments
Applicant's arguments filed 06/26/2026 with respect to the 35 U.S.C. 101 rejection have been fully considered but they are not persuasive.
Applicant argues on Page 11 that the claims do not constitute an abstract idea because Claim 1 relates to a specific physiological signal processing device in which motion sensor signals are generated by a 9-axis motion sensor positioned on a subject during running, and position information of the subject that is obtained from a positioning module positioned on the subject, which is used to determine a running speed, and the correlation of the running speed values to generate motion signal data representing motion characteristics of the subject. Applicant argues that these operations are grounded in physical sensor measurements and cannot be performed as mental steps.
Examiner respectfully disagrees. The 9-axis motion sensor positioned on a subject during running and the positioning module that obtains position information are considered to be necessary data gathering. As recited in MPEP section 2106.05(g), necessary data gathering (i.e. acquiring data) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Furthermore, 9-axis motion sensors positioned on a subject and positioning modules are well understood, routine, and conventional in the art, as evidenced by in Kaji (WO2023195461) and Cho (US20130273939). The further limitation of using the determining based on the position information, running speeds of the subject under broadest reasonable interpretation qualifies as an abstract mathematical calculation because speed is determined by the change in position divided by the time it takes for that change to occur. As the MPEP states in 2106.04(a)(2)(I)(C), “A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.”
Applicant argues on Pages 11-12 that the Claim 1 as amended is analogous to the claim discussed in the Federal Circuit decision in CardioNet LLC v. InfoBionic Inc., 955 F.3D 1358.
Examiner respectfully disagrees. The fact patterns between CardioNet and the instant application are different. As Applicant details with Claim 1 of CardioNet, the claim is directed towards a beat detector with a ventricular beat detector. The instant application is directed towards performing mathematical calculations to determine the speed from position information, determine slopes of variables (step frequency change with respect to change in running speed; step length change with respect to a change in running speed), generating a numerical score, and determining from that score the running style type. Thus the instant application details abstract concepts encompassing mathematical calculations and mental processing steps.
Applicant argues on pages 12-13 that the written description supports the conclusion that claim 1 is not directed to an abstract idea, with paragraph [0005] of the specification detailing that “…Accordingly, such determining has had to rely on subjective judgment”. Applicant argues that the specification describes the technical improvement with [0006] detailing objective criteria for distinguishing between the high cadence running type and the long stride running type.
Examiner respectfully disagrees. Claim 1 details a plurality of mathematical calculations and mental processing steps. Applicant details in [0005] of the instant application that “However, except in cases…Accordingly, such determining has had to rely on subjective judgment”. Examiner notes that the claim limitation “determine, based on generated running style score, a running style type for the subject of a plurality of running style types, including a long stride type and a high cadence type” falls under an abstract concept of mental processing, as the claim limitation under broadest reasonable interpretation is a judgment.
Applicant argues on Page 13 that the claims include additional elements that meaningfully limit the claims and that the claims are integrated into a practical application with examples towards the 9-axis motion sensor and positioning module positioned on the subject to determine the running speed values and that such features define body worn aspects of a biomechanical measurement system and not generic computation.
Examiner respectfully disagrees. As detailed above, the 9-axis motion sensor and positioning module are considered to be mere data gathering and well understood, routine, and conventional in the art. Furthermore, having sensors that are worn are also well understood, routine, and conventional in the art, as evidenced by Kaji (WO2023195461) and Sazuka (US20180039751).
Applicant argues on Page 13 that the claim relates to signal correlation based on the physiological movement, with claim 1 reciting the computing device configured to correlate the motion sensor signals with the running speed values and that this constitutes a technical signal processing operation tied to physical motion and not an abstract analysis.
Examiner respectfully disagrees. As the claim limitation details that the correlation is of motion sensor signals with the running speed values to generate motion signal data that represents motion characteristics of the subject at different running speeds, this limitation under broadest reasonable interpretation details taking a sensor signal, a running speed value, and generates another signal that represents a “motion characteristic of the subject at different running speeds”. Thus the claim limitation is detailing a mental processing step as a correlation would be an observation and evaluation occurring, that the motion signal data has a relationship to the speed, thus making a motion characteristic. Furthermore, the limitation would be considered a mathematical relationship as it is taking one measurement value (motion signal data), a second value (speed), and outputs a third value (motion characteristic). Thus it is an abstract step.
Applicant argues on page 14 that the model based scoring applied to sensor derived running data in Claim 1 reflects a structured processing that converts physiological running data into a biomechanical classification metric and since Claim 1 relates to wearable components and signal processing architecture and not abstract reasoning that the claim as a whole integrates any mathematical concepts into a practical application.
Examiner respectfully disagrees. As detailed above, the claim limitations are directed at well understood, routine, and conventional (wearable components) in combination with mental processing mathematical abstract ideas. As detailed in the 35 U.S.C. 101 rejection, none of the additional limitations of the Claims (9-axis motion sensor [well understood, routine, and conventional], computing device [generic computing element], generating and receiving motion sensor signals [mere data gathering], positioning module [well understood, routine, and conventional], obtaining position information [mere data gathering], and outputting results [insignificant extra-solution activity]) integrate the judicial exception into a practical application.
Applicant argues on Page 14 that MPEP section 2106.04(d)1) that “the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement”.
Examiner respectfully disagrees. As the MPEP recites in 2106.04(d) cites “Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. Whether or not a claim integrates a judicial exception into a practical application is evaluated using the considerations set forth in subsection I below, in accordance with the procedure described below in subsection II.” Thus Examiner notes that the claim as a whole does not integrate the judicial exception into a practical application, and instead it is a drafting effort to attempt to monopolize the judicial exception itself as the claim is directed towards taking measurements from a person running, then performs mathematical and mental processing steps to output a result. Furthermore, the claim limitation are analogous to the interactions between the runner and a specialist who is trained in gait analysis or a physical therapist/podiatrist with expertise in running biomechanics. That is the specialist, physical therapist, or podiatrist can perform the mental processing as detailed in the limitation that yields the determination of a running style type and outputs information to the subject the results thereof. The MPEP further recites in 2106.04(d) (I), “The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).”
Examiner notes that the additional elements as detailed above and in the 35 U.S.C. 101 rejection do not integrate the judicial exception into a practical application.
Applicant argues on pages 14-15 that the MPEP 2106.05 section II (citing MPEP 2106.05(d)) that examiners should evaluate whether any additional element or combination of elements are other than that is well understood, routine, conventional activity in the field, and that the certain elements recited in the claims are other than what is well understood, routine, conventional activity in the field of running analysis.
Applicant argues on Page 16 that the dependent claims add additional features, with Claims 7-8 reciting the computing device is further configured to output information recommending at least one shoe suitable for the subject and Claim 8 reciting the use of a mixed Gaussian model.
Examiner respectfully disagrees. Under broadest reasonable interpretation, a Gaussian model is a mathematical concept, as a Gaussian model is a probability distribution. The computing device is as detailed a generic computer element, and generic computer elements are not considered significantly more than the abstract idea and do not integrate the abstract idea into a practical application. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94. Providing a recommendation based on data is a mental processing step as it is a judgment and evaluation.
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 1-20 are 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. Independent Claims 1 and 9-10 are amended to detail the limitation “correlate the motion sensor signals with the running speed values to generate motion signal data representing motion characteristics of the subject at different running speeds”. [0023] of the specification details Figure 1 with motion sensor 14 with the motion sensor including a positioning module and 9-axis motion sensor, with further details towards the running speed is acquired based on the relationship between time and position and step frequency is acquired based on information detected by the 9 axis motion sensor. The specifications are silent with regards to the language of correlating motion sensor signals with running speed values to generate a motion signal data that represents motion characteristics of the subject at different running speeds.
Claims 2-8 and 11-20 are rejected due to dependence on Claims 1 and 9-10.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101. The claimed invention is directed to the abstract concept of performing abstract steps without significantly more. The claim(s) recite(s) the following abstract concepts in BOLD of
1. (Currently Amended) A running style analysis device, comprising:
a motion sensor comprising a 9-axis motion sensor positioned on a subject and configured to generate motion sensor signals during running of the subject; and
a computing device configured to:
receive the motion sensor signals from the motion sensor;
obtain position information of the subject from a positioning module positioned on the subject during the running;
determine, based on the position information, running speed values of the subject corresponding to a plurality of running speeds during the running;
correlate the motion sensor signals with the running speed values to generate motion signal data representing motion characteristics of the subject at different running speeds;
determine a step frequency change with respect to a change in running speed of the subject and a step length change with respect to a change in running speed of the subject;
apply a running style analysis model, generated in advance based on data from a plurality of runners, to the step frequency change and the step length change, to generate a running style score for the subject;
determine, based on the generated running style score, a running style type for the subject of a plurality of running style types, including a long stride type and a high cadence type; and
output information corresponding to the determined running style type for the subject.
9. (Currently Amended) A running style analysis method, comprising:
positioning a motion sensor comprising a 9-axis motion sensor on a subject, the motion sensor configured to generate motion sensor signals during running of the subject;
receiving the motion sensor signals from the motion sensor;
obtaining position information of the subject from a positioning module positioned on the subject during the running;
determining, based on the position information, running speed values of the subject corresponding to a plurality of running speeds during the running;
correlating the motion sensor signals with the running speed values to generate motion signal data representing motion characteristics of the subject at different running speeds;
determining a step frequency change with respect to a change in running speed of the subject and a step length change with respect to a change in running speed of the subject;
applying a running style analysis model based on data from a plurality of runners, to the step frequency change and the step length change, to generate a running style score for the subject;
determining, based on the generated running style score, a running style type for the subject of a plurality of running style types, including a long stride type and a high cadence type; and
outputting information corresponding to the determined running style type for the subject.
10. (Currently Amended) A non-transitory computer-readable storage medium storing a running style analysis program causing a computer to implement:
receiving motion sensor signals from a motion sensor comprising a 9-axis motion sensor positioned on a subject; obtaining position information of the subject from a positioning module positioned on the subject during the running;
determining, based on the position information, running speed values of the subject corresponding to a plurality of running speeds during the running;
correlating the motion sensor signals with the running speed values to generate motion signal data representing motion characteristics of the subject at different running speeds;
determining a step frequency change with respect to a change in running speed of the subject and a step length change with respect to a change in running speed of the subject;
applying a running style analysis model based on data from a plurality of runners, to the step frequency change and the step length change, to generate a running style score for the subject;
determining, based on the generated running score, a running style type for the subject of a plurality of running style types, including a long stride type and a high cadence type; and
outputting information corresponding to the determined running style type for the subject.
Under step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. The above claims are considered to be in a statutory category.
Under Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitation the fall into/recite abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter that, when recited as such in a claim limitation, covers performing mathematics or mental steps.
Next, under Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application. In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
This judicial exception is not integrated into a practical application because there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; effecting a transformation or reduction of a particular article to a different state or thing. Examiner notes that since the claimed methods and system are not tied to a particular machine or apparatus, they do not represent an improvement to another technology or technical field. Similarly there are no other meaningful limitations linking the use to a particular technological environment. Finally, there is nothing in the claims that indicates an improvement to the functioning of the computer itself or transform a particular article to a new state.
Finally, under Step 2B, we consider whether the additional elements are sufficient to amount to significantly more than the abstract idea. Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because a computing device is considered to be a generic computer element. Generic computer elements are not considered significantly more than the abstract idea and do not integrate the abstract idea into a practical application. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94. The additional limitation of Claims 1, and 9-10 to “outputting to the subject a result corresponding to the determined running style type for the subject” is considered to be an insignificant extra-solution activity due to the limitation detailing a generic outputting of a result that does not impose any meaningful limit on the claim and it is well known in the art to output a result, as evidenced by Kawai (JP2007185328A) in [0032] and Winter (US20170354348) in [0073]. The data acquisition device is considered necessary data gathering. The additional limitation of Claims 1 and 9-10 of the 9 axis motion sensor that obtains motion sensor data relating to a subject is considered to be necessary data gathering. As recited in MPEP section 2106.05(g), necessary data gathering (i.e. acquiring data) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). This is further evidenced in Kaji (WO2023195461) in [0019] and Cho (US20130273939) in [0003]. The additional limitations of Claims 1 and 9-10 of generating motion sensor signals, receiving the motion sensor signals, and obtaining position information is considered necessary data gathering. As recited in MPEP section 2106.05(g), necessary data gathering (i.e. acquiring a detection value) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015).
Claims 2-8, 11-15, 18, and 20 further limit the abstract ideas without integrating the abstract concept into a practical application or including additional limitations that can be considered significantly more than the abstract idea.
The additional limitation of Claims 16-17 and 19 of the computing device/storage medium being positioned on the subject is considered to be well-understood, routine, and conventional in the art. This is evidenced by Sazuka (US20180039751) in Figure 12 of a wearable terminal with a CPU 401 and storage unit 402 and Diggelen (US20180156920) in [0018] and Figure 1.
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.
Claims 1, 4, 7, 9-10, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kaji (WO2023195461) in view of Kawai (JP2007185328A) and Sazuka (US20180039751)
In regards to Claims 1, 9, and 10, Kaji teaches “a motion sensor comprising a 9-axis motion sensor positioned on a subject and configured to generate motion sensor signals during running of the subject (In this embodiment, the body motion sensor and the information terminal are described as separate components that communicate with each other in real time and cooperate. However, the present invention is not limited to this, and a memory device and a processing device may be built into the body motion sensor, and a module related to running form analysis may be integrated into the body motion sensor. Alternatively, instead of communicating in real time as in this embodiment, the motion sensor may be equipped with a storage device to record the sensor's detected values, which can then be collected and analyzed on the information terminal side through post-processing. (1) Body movement sensor The lumbar body movement sensor 40a is attached to the back of the wearer's waist and is a sensor that detects three-dimensional displacement or rotation in the waist. This lumbar motion sensor 40a is equipped with a 3-axis accelerometer to measure the acceleration of an object, a 3-axis gyroscope to detect the angular velocity of an object, and a 3-axis magnetic sensor to measure the magnitude and direction of a magnetic field, enabling the detection of movement in 9 axes. Furthermore, the lumbar movement sensor 40a can be attached to and detached from the wearer's belt or clothing using a clip or other component, allowing for easy attachment and detachment of the sensor for measurement, and enabling continuous measurement without burdening the wearer. – [0019]; Here, the motion data, which is the detection result by the lumbar motion sensor 40a, is a value measured by a so-called 9-axis sensor, and in this embodiment, it is the acceleration acting on an object (including gravitational acceleration). These are the direction and magnitude of the magnetic field, the angular velocity of the object (magnitude, direction, and center position), and the magnitude and direction (direction) of the magnetic field - [0033]); and
a computing device (computer processor – [0011]) configured to:
receive the motion sensor signals from the motion sensor (The communication interface 113 is a module that controls the transmission and reception of various information via a communication network, as well as short-range wireless communication such as Wi-Fi and Bluetooth (registered trademark). It communicates with the lumbar movement sensor 40a using various protocols and transmits and receives data with the server device, etc., via 3G to 5G communication. - [0026]);
obtain position information of the subject from a positioning module positioned on the subject during the running (The analysis unit 117d includes an index calculation unit 117g and a stride length detection unit 117h as modules related to running form analysis processing – [0043]; In this embodiment, the stride length detection unit 117h has a function to calculate cadence (pitch) from periodic vertical movement detected by the waist body movement sensor 40a, and also has a function to calculate the distance traveled per predetermined time from the displacement of the wearer's position information acquired by the position information acquisition unit 115, and to calculate the stride length from that distance traveled and the number of pitches within the predetermined time. The cadence (pitch) and stride (step length) calculated by the stride length detection unit 117h are input to the index calculation unit 117g as body movement reproduction data. - [0043]);
determine, based on the position information, running speed values of the subject corresponding to a plurality of running speeds during the running (In this embodiment, the body movement calculation unit 117b calculates the wearer's body movements as body movement reproduction data based on the body movement data, which is the detection result from the lumbar body movement sensor 40a, and the amount of deviation from the reference value of the lumbar body movement sensor 40a. At this time, the body motion calculation unit 117b calculates body motion reproduction data based on the trajectory of the displacement (body motion) of each part of the body, based on the three-dimensional coordinates, velocity, and acceleration of the lumbar body motion sensors 40a, and based on the relative displacement, velocity, acceleration, and rotation (angular momentum) between the lumbar body motion sensors 40a. - [0035]; The body motion data acquired by the body motion calculation unit 117b described above is input to the analysis unit 117d, and based on relative displacement, velocity, acceleration, angular velocity, etc., body motion reproduction data is generated from the instantaneous relative displacement (distance and rotation) of the wearer's waist and the three-dimensional periodic motion of the waist. The analysis unit 117d then uses primary data such as body movement data and ground contact data, and secondary data such as body movement reproduction data, to evaluate the running form based on the timing of body movements, posture breakdown, etc. - [0039]; In this embodiment, the stride length detection unit 117h has a function to calculate cadence (pitch) from periodic vertical movement detected by the waist body movement sensor 40a, and also has a function to calculate the distance traveled per predetermined time from the displacement of the wearer's position information acquired by the position information acquisition unit 115, and to calculate the stride length from that distance traveled and the number of pitches within the predetermined time. The cadence (pitch) and stride (step length) calculated by the stride length detection unit 117h are input to the index calculation unit 117g as body movement reproduction data. - [0043]; The index calculation unit 117g can use various types of exercise information stored in the memory 114 to compare and analyze the wearer's past running results over multiple occasions, or to compare and analyze the wearer's past running results with the running results of other wearers, and include comparative analysis information, which is the result of the analysis, in the index. Specifically, the index calculation unit 117g generates comparative analysis information similar to detailed analysis information for each of the multiple dates selected by the wearer, or generates comparative analysis information similar to detailed analysis information for the date selected by the wearer and the past driving of other wearers.- [0050]);
correlate the motion sensor signals with the running speed values to generate motion signal data representing motion characteristics of the subject at different running speeds In this embodiment, the stride length detection unit 117h has a function to calculate cadence (pitch) from periodic vertical movement detected by the waist body movement sensor 40a, and also has a function to calculate the distance traveled per predetermined time from the displacement of the wearer's position information acquired by the position information acquisition unit 115, and to calculate the stride length from that distance traveled and the number of pitches within the predetermined time. The cadence (pitch) and stride (step length) calculated by the stride length detection unit 117h are input to the index calculation unit 117g as body movement reproduction data. - [0043]; The index calculation unit 117g can use various types of exercise information stored in the memory 114 to compare and analyze the wearer's past running results over multiple occasions, or to compare and analyze the wearer's past running results with the running results of other wearers, and include comparative analysis information, which is the result of the analysis, in the index. Specifically, the index calculation unit 117g generates comparative analysis information similar to detailed analysis information for each of the multiple dates selected by the wearer, or generates comparative analysis information similar to detailed analysis information for the date selected by the wearer and the past driving of other wearers.- [0050]);
determine a step frequency change of the subject and a step length change of the subject (More specifically, the ground contact state detection unit 117e in this embodiment uses, for example, the detected values (motion data) from the acceleration sensor and angular velocity sensor that constitute the motion sensor, which show characteristic behavior, as well as the changes therein and characteristic points detected based on time (time). Using this timing as a reference, it identifies the time range of the grounded state or the off-ground state according to the ground contact time, impact time, their rate of change, and periodicity, and sets a flag for the data corresponding to the time length included in each range separated as the grounded state or the off-ground state - [0038]; In this embodiment, the stride length detection unit 117h has a function to calculate cadence (pitch) from periodic vertical movement detected by the waist body movement sensor 40a, and also has a function to calculate the distance traveled per predetermined time from the displacement of the wearer's position information acquired by the position information acquisition unit 115, and to calculate the stride length from that distance traveled and the number of pitches within the predetermined time. The cadence (pitch) and stride (step length) calculated by the stride length detection unit 117h are input to the index calculation unit 117g as body movement reproduction data. - [0043]; Furthermore, the stability calculation function of the analysis unit 117d analyzes the wearer's movements using motion reproduction data and reference values, and performs a process to detect points of change in the calculated running form in order to evaluate the reproducibility and sustainability of the wearer's running form. In particular, in this embodiment, the stability calculation function of the analysis unit 117d can analyze the past running form of the wearer or others using body movement reproduction data, and generate overall analysis information as an analysis result – [0048]);
apply a running style analysis model, generated in advance based on data from a plurality of runners, to the step frequency change and the step length change, to generate a running style score for the subject (an index calculation unit [i.e. running style analysis model] that calculates an index [i.e. running score] for evaluating the running form based on the ratio of vertical motion during ground contact and overall vertical motion detected by the vertical motion detection unit - [0007]; Furthermore, when the index calculation unit 117g compares the results with those of top performers or ideal values, the parameters to be compared can be set according to the application, such as selecting the average value, maximum value, minimum value, or any representative value within a predetermined period, based on the settings performed by the wearer. - [0047]; The index calculation unit 117g can use various types of exercise information stored in the memory 114 to compare and analyze the wearer's past running results over multiple occasions, or to compare and analyze the wearer's past running results with the running results of other wearers, and include comparative analysis information, which is the result of the analysis, in the index. Specifically, the index calculation unit 117g generates comparative analysis information similar to detailed analysis information for each of the multiple dates selected by the wearer, or generates comparative analysis information similar to detailed analysis information for the date selected by the wearer and the past driving of other wearers.- [0050]);
Kaji is silent with regards to the language of “determine, based on the generated running style score, a running style type for the subject of a plurality of running style types, including a long stride type and a high cadence type; output information corresponding to the determined running style type for the subject.”
Kawai teaches “determine, based on the generated running style score, a running style type for the subject of a plurality of running style types, including a long stride type and a high cadence type (determining whether the running style is a stride running style or pitch running style – [0024]; stride running style is a running style with a wide stride, i.e. long stride type – [0030]; The running style data determination means can determine whether a customer's running style is a stride running style or a pitch running style by calculating stride length/height or stride length/leg length*2 based on stride length and height or leg length. – [0049]); and
output information corresponding to the determined running style type for the subject (selection of athletic/running shoes suitable, i.e. recommending, based on the running style, i.e. outputs a result – [0032]).”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kaji to incorporate the teaching of Kawai to determine the running style type and output the type. By determining the running type this is an improvement in the analysis of the running style of a subject so that an improvements can be made to the performance of the subject.
Kaji in view of Kawai is silent with regards to the language of “determine a step frequency change with respect to a change in running speed of the subject and a step length change with respect to a change in running speed of the subject”
Sazuka teaches “determine a step frequency change with respect to a change in running speed of the subject (Figure 5 details two dimensional graph that illustrates a speed-pitch [i.e. step frequency] characteristic, i.e. slope – [0143], Figure 5; Server 111 receives data – Figure 7) and a step length change with respect to a change in running speed of the subject (Figure 3 details a two-dimensional graph that illustrates a relation, i.e. slope, between the speed and stride, i.e. step length, at the time of a person’s running – [0120], Figure 3; Server 111 receives data – Figure 7)”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kaji in view of Kawai to incorporate the teaching of Sazuka to use the speed-pitch and speed-stride relations in the evaluation of a user’s running state. By using the speed-pitch and speed-stride relations, this is an improvement to the analysis of a user’s running state based on the pitch and stride so as to provide advice and training that is appropriate to the user based on the analysis.
In regards to Claims 4, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji further teaches “wherein the computing device is further configured to determine the running style type for the subject by using, as a reference, an average value in a range of scores calculated as a running style score with the running style analysis model and comparing the generated running style score for the subject and the average value (Furthermore, when the index calculation unit 117g compares the results with those of top performers or ideal values, the parameters to be compared can be set according to the application, such as selecting the average value, maximum value, minimum value, or any representative value within a predetermined period, based on the settings performed by the wearer. - [0047]).”
In regards to Claims 7, 18, and 20, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji is silent with regards to the language of “wherein the computing device is further configured to output to the subject, based on the determined running style type for the subject, information recommending at least one shoe suitable for the subject that includes at least one of a plurality of shoes selected from the group consisting of a shoe suitable for a high cadence type runner and a shoe suitable for a long stride type runner.”
Kawai further teaches ““wherein the computing device is further configured to output to the subject, based on the determined running style type for the subject, information recommending at least one shoe suitable for the subject that includes at least one of a plurality of shoes selected from the group consisting of a shoe suitable for a high cadence type runner and a shoe suitable for a long stride type runner (selection of athletic/running shoes suitable, i.e. recommending, based on the running style, i.e. outputs a result – [0032]).”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kaji in view of Kawai and Sazuka to incorporate the further teaching of Kawai to determine the running style type and output the recommendation of shoe based on the type. By determining the running type this is an improvement in the analysis of the running style of a subject so that an improvements can be made to the performance of the subject.
In regards to Claims 16 and 19, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji further teaches “wherein the motion sensor and the computing device are positioned on the subject at one or more locations selected from the group consisting of a waist and at least one arm of the subject (The running form analysis system according to this embodiment consists of an information processing terminal 100 used by the wearer 1, and a lumbar movement sensor 40a that is attached to the waist of the wearer 1 and wirelessly connected to the information processing terminal 100, as shown in Figure 1. In this embodiment, the example given is that the body movement sensor is attached to the wearer's waist. However, the present invention is not limited to this, and the sensor can be attached to any part of the body where it is possible to acquire vertical movement of the body axis, such as the chest, abdomen, head, arms, or legs, in addition to the waist. It may be attached as a single body movement sensor to these attachment points, or it may be attached in pairs to symmetrical parts of the body, such as the arms or legs. - [0017]).”
In regards to Claim 17, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji further teaches “further comprising positioning a computing device at one or more locations on the subject selected from the group consisting of a waist and at least one arm of the subject, to carry out the applying the running style analysis model to generate the running style score for the subject, the determining the running style type for the subject (By installing such a program of the present invention onto the IC chip or memory device of a mobile terminal device, smartphone, wearable device, tablet PC or other information processing terminal, or a general-purpose computer such as a personal computer or server computer, and executing it on the CPU, a system having the above-described functions can be constructed, and the method of the present invention can be implemented - [0011]; The running form analysis system according to this embodiment consists of an information processing terminal 100 used by the wearer 1, and a lumbar movement sensor 40a that is attached to the waist of the wearer 1 and wirelessly connected to the information processing terminal 100, as shown in Figure 1. In this embodiment, the example given is that the body movement sensor is attached to the wearer's waist. However, the present invention is not limited to this, and the sensor can be attached to any part of the body where it is possible to acquire vertical movement of the body axis, such as the chest, abdomen, head, arms, or legs, in addition to the waist. It may be attached as a single body movement sensor to these attachment points, or it may be attached in pairs to symmetrical parts of the body, such as the arms or legs. - [0017]).”
Examiner’s Note
Claims 2-3, 5-6, 8, and 11-15 are not rejected under a prior art rejection (35 U.S.C. 102 or 35 U.S.C. 103).
In regards to Claim 2, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji in view of Kawai and Sazuka are silent with regards to the language of “wherein the computing device stores, as the running style analysis model, an equation to calculate the running style score based on principal component loading obtained by performing principal component analysis in advance on a data group of data related to a step frequency change and a step length change with respect to a change in running speed in measurement values of the plurality of runners.”
Claims 3 and 11-15 are dependent on Claim 2.
In regards to Claims 5, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji in view of Kawai and Sazuka are silent with regards to the language of “wherein the computing device is further configured to determine that when the generated running style score of the subject is higher than or equal to the average value, the high cadence type is applicable, and, when the generated running style score of the subject is lower than or equal to the average value, the long stride type is applicable.”
In regards to Claims 6, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji in view of Kawai and Sazuka are silent with regards to the language of “wherein the computing device is further configured to determine that the high cadence type is applicable when the generated running style score of the subject is within a predetermined first reference range, which is higher than the average value, determine that the long stride type is applicable when the generated running style score of the subject is within a predetermined second reference range, which is lower than the average value, and determine that an intermediate type is applicable when the generated running style score of the subject is within a predetermined third reference range, which is lower than the predetermined first reference range and higher than the second predetermined reference range.”
In regards to Claims 8, Kaji in view of Kawai and Sazuka discloses the claimed invention as detailed above. Kaji in view of Kawai and Sazuka are silent with regards to the language of “wherein the computing device is further configured to output to the subject information including recommending at least one shoe based on a mixed Gaussian model in which a plurality of Gaussian distributions are used, each corresponding to a running style score associated with one of a plurality of shoes selected from the group consisting of a shoe suitable for a high cadence type runner, a shoe suitable for a long stride type runner, and a shoe suitable for both the high cadence type and the long stride type, wherein the recommending comprises selecting at least one shoe based on which of the Gaussian distributions corresponds to the running style score of the subject.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YOSSEF KORANG-BEHESHTI whose telephone number is (571)272-3291. The examiner can normally be reached Monday - Friday 10:00 am - 6:30 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached at (571) 270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/YOSSEF KORANG-BEHESHTI/ Primary Examiner, Art Unit 2857
Prosecution Insights