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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on January 17, 2024 and July 24, 2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendment
The Amendment filed December 17, 2025 has been entered. Claims 1, 3-9, 11-15 & 17-21 remain pending in the application. Claims 1, 3-6, 9, 11-13, 15 & 17-19 have been amended. Claims 2, 10 & 16 have been cancelled and claim 21 has been newly presented. Applicant’s amendments to the Claims have overcome each and every objection and 35 U.S.C. § 112(b) rejections previously set forth in the Non-Final Office Action mailed September 17, 2025, hereafter referred to as the Non-Final Office Action.
Response to Arguments
Applicant's arguments filed December 17, 2025 have been entered and fully considered but they are not persuasive. In light of the amendments, the rejection(s) have been withdrawn. However, upon further reconsideration, new grounds of rejections have been made, and applicant’s arguments are rendered moot.
In response to applicant's argument, please see pages 9-14 of applicant’s remarks, with respect to the rejection of amended independent claim 1, under U.S.C. § 102(a)(1), that the prior reference, Matsumoto (JP 2020101849 A), and with respect to the rejections of amended independent claims 9 & 15, under U.S.C. § 103, that prior art references, Matsumoto, in view of Unuma (US 6941239 B2), fail to disclose, teach and/or suggest individually or in combination, each and every limitation of the claimed invention, to include the amended features of the invention: “determining a state of a user wearing the acceleration sensor…and a count value of zero-crossing points within predetermined time of…, wherein the determining the state of the user includes:”, “determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value,” and “determining a reference range for a time width from the first timing to the second timing based on the determined state of the user;”, the following arguments related to a count value, “never identifies or counts the number of timing events within a period of time”, “does not compare such a count to a threshold or use that comparison to change the lower-limit value of the reference range”, and the following arguments related to amplitude, “amplitude alone is insufficient to clearly distinguish between the walking state and the running downstairs state. Therefore, the walking pitch is also used to determine the user state.”, and “nor of applying the identification result to the dynamic adjustment of the reference range of the time width”.
The examiner respectfully disagrees and would like to break the arguments presented into two sections. The first part the examiner would like to highlight is regarding the submissions of what the applicant states as the prior art reference, Matsumoto, determines amplitude “only by looking at the amplitude of the acceleration waveform”. The examiner appreciates the explanation and additional evidence; however, it is noted that the features upon which applicant relies (i.e., Pages. 12-13 of applicant’s remarks, points to the specification paragraphs [0038]-[0039]) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Circ. 1993). Currently, the claims do not recite or define that “a reference range for time width between the first and second timing events,” cannot be de determined “only by looking at the amplitude of the acceleration waveform.”, or “applying the identification result to the dynamic adjustment of the reference range of the time width”. The applicant may believe that their terminology defines the claimed limitation(s) to a particular methodology, but when the claims are examined, they are given the broadest reasonable interpretation. In the immediate case of this application the examiner has taken the interpretation that other methodologies and techniques with increased accuracy and precision can be applied to determine “a reference range for the time width between the first and second timing events”, as in the case of Matsumoto, who does so “only by looking at the amplitude of the acceleration waveform”. This definition leads to the second part the examiner would like to highlight is how the prior art reference, Matsumoto, reads on the claims. Matsumoto on Pages 7-11 of the Non-Final Office Action mentions the methodology and steps taken to count the first and second timing events, “(i.e., number of zero-crossing events that would produce a count value”, generating a count value, and “compare such a count to a threshold”. Further, Matsumoto, in view of Unuma, on Pages 28-30 & 39-42 of the Non-Final Office Action, disclose “identifying a particular motion such as “downstairs running” using a specific threshold logic”.
In light of the amended independent claims 1, 9 & 15, a new ground of rejection is made over Taniguchi (JP 2007075428 A, Pub. Date Mar. 03, 2007, hereinafter Taniguchi). The examiner respectfully disagrees with the applicant’s contentions that Matsumoto, in light of new prior art reference Taniguchi, in amended independent claim 1, and Matsumoto, in view of Unuma, and in light of new prior art reference, Taniguchi, in amended independent claims 9 & 15, fail to disclose, teach, and or suggest, individually or in combination, each and every limitation of independent claims 1, 8 & 15, to include the amended features of the invention, in particular, “determining a state of a user wearing the acceleration sensor…and a count value of zero-crossing points within predetermined time of…, wherein the determining the state of the user includes:”, “determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value,” and “determining a reference range for a time width from the first timing to the second timing based on the determined state of the user;”.
Matsumoto, in view of Taniguchi, in amended independent claim 1, and Matsumoto, in view of Unuma, and further in view of Taniguchi, further disclose the additional limitations that have been amended, and also further identify the “running downstairs state”, and meeting these requirements. Therefore, the applicant’s arguments are unconvincing and the rejection of amended independent claim 1, and dependent claims 3-8 & 21, which depend from and incorporate the limitations of amended independent claim 1, the rejection of amended independent claim 9, and dependent claims 11-14, which depend from and incorporate the limitations of amended independent claim 9, and the rejection of amended independent claim 15, and dependent claims 17-20, which depend from and incorporate the limitations of amended independent claim 15, are respectively maintained. Rejections based on the newly cited prior art reference follow below.
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 & 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Matsumoto (JP 2020101849 A, Pub. Date Jul. 02, 2020, hereinafter Matsumoto), in view of Taniguchi (JP 2007075428 A, Pub. Date Mar. 03, 2007, hereinafter Taniguchi).
Regarding independent claim 1, Matsumoto, teaches:
A measurement device comprising (Fig. 2; [0011] & [0015]: “The measurement device 1 includes a CPU (Central Processing Unit) 11, an operation unit 12, a RAM (Random Access Memory) 13, a sensor unit 14, a display unit 15, a storage unit 16, and a communication unit 17”):
an acceleration sensor (Fig. 2; [0011] & [0015]: specifies that the “sensor unit 14 includes a motion sensor capable of detection a motion of the measuring device 1 such as a three axis acceleration sensor…”);
a memory (Fig. 2; [0011] & [0015]: “The measurement device 1 includes a CPU (Central Processing Unit) 11, an operation unit 12, a RAM (Random Access Memory) 13 (memory)); and
one or more processors (Fig. 2; [0011]: “The measurement device 1 includes a CPU (Central Processing Unit) 11…” (one or more processors)), wherein the one or more processors follow instructions saved in the memory to execute following processing of ([0011]-[0012]):
acquiring time-series acceleration data output by the acceleration sensor (Fig. 1; [0006]-[0008], [0010]-[0011], [0015] & [0020]: “the CPU 11 of the measurement device 1 sequentially acquires the acceleration values in the three axial directions from the sensor unit 14 (step S1), and generates a combined acceleration value by combining the acceleration values in the three axial directions (step S2)”);
specifying, based on the acquired time-series acceleration data, first timing at which acceleration goes above an acceleration reference value (Figs. 1 & 3a; [0012], [0015] & [0022]-[0024]: uses zero-crossing point as the acceleration reference value, the “first timing” is when the waveform crosses from negative to positive value, figure 3a illustrates timing t1 at the zero-crossing point) and second timing at which the acceleration goes below the acceleration reference value (Figs. 1 & 3a-3b; [0012], [0015] & [0023]-[0028]: the “second timing” is when the waveform crosses from positive to negative value, establishing “zero” as the reference value, Fig. 3b illustrates timings t1 and t2 at the zero-crossing point);
determining a reference range for a time width from the first timing to the second timing (Figs. 3b & 4; [0020]-[0028]: reference range is defined by a lower limit TH_S and upper limit TH_L for the time width T (time span), delineates walking or running states from noise and other factors) based on the determined state of the user ([0006]-[0008], [0015], [0020]-[0028], [0031]-[0033] & [0035]-[0038]);
determining whether the time width falls within the determined reference range (Fig. 4; [0024]-[0028] discloses “determine whether or not the time span falls within a predetermined range (Step 6)” from TH_S to TH_L, T of a potential step must fall within TH_S ≤ T ≤ TH_L); and
counting one step for a partial waveform from the first timing to the second timing in the acceleration waveform when the time width is determined as falling within the reference range (Figs. 2-3; [0022]-[0030]: teaches in step S8 that if the time width is within the range the waveform is determined to be from walking/running and counted as a step, if not, process loops back, waveform is not counted, Fig. 2, flowchart of step count measurement process).
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Matsumoto, is silent in regard to:
determining a state of a user wearing the acceleration sensor based on amplitude of an acceleration waveform corresponding to the time-series acceleration data and a count value of zero-crossing points within predetermined time of at least either the first timing or the second timing, wherein the determining the state of the user includes:
determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value,
However, Taniguchi, further teaches:
determining a state of a user wearing the acceleration sensor based on amplitude of an acceleration waveform corresponding to the time-series acceleration data (Fig. 1; [0013]-[0015], [0030], [0034], [0038], [0048]-[0057], [0061]-[0070], [0074], [0083]-[0085] & [0116]-[0118]: teaches body motion determination unit 9 determines the user’s state (e.g., walking, running, ascending stairs, descending stairs) using the PIM value (based on amplitude) and the ZC value (zero-crossing count)) and a count value of zero-crossing points within predetermined time of at least either the first timing or the second timing (Figs. 1 & 10-13; [0013]-[0015], [0030], [0034], [0038], [0048]-[0057], [0061]-[0070], [0074], [0083]-[0085] & [0116]-[0120]: teaches body motion determination unit 9 determines the user’s state (e.g., walking, running, ascending stairs, descending stairs) using the PIM value (based on amplitude) and the ZC value (zero-crossing count), Figs. 10-12 show classification based on PIM values, Fig. 13 shows using DC values for further distinction, the classification determines the user’s state based on amplitude and a zero-crossing count), wherein the determining the state of the user includes:
determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value (Figs. 9 & 11; [Abstract], [0010]-[0014], [0045]-[0046], [0116]-[0120] & [0125]-[0127]: teaches the system is designed to classify motions like “descending stairs”, Figs. 9 & 11 identify the PIM region for “descending stairs”, PIM 95, “quickly descending stairs”, PIM 96, and “slowly descending stairs”, PIM 97, the classification is based on the PIM values (magnitude) and using ZC values (zero-crossing count) in its processing, state is determined by checking if ZC/PIM values fall within specific thresholds),
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the step-counting method of Matsumoto with Taniguchi’s “ZC/Amplitude-based” state determination, incorporating the advanced state-determination logic of Taniguchi, that can distinguish different types of motion using a ZC calculation unit to count zero-crossings and a PIM calculation unit to measure intensity/amplitude. A POSITA would have been motivated to combine the precision of Matsumoto’s timing-based step counting methodology with Taniguchi’s methodology to improve the method to identify a “running downstairs” state that would provide the logical trigger to select the specific TH_S range for that motion in Matsumoto, improving the counting accuracy and functionality of the wearable device, allowing the system to distinguish between descending stairs slowly, normal pace, or quickly for more precise fitness tracking and calculation. The modification includes the combination of the prior art references to yield predictable results of enhanced user state detection (KSR).
Regarding dependent claim 7, Matsumoto, teaches:
The measurement device according to claim 1 (Figs. 1 & 2; [0011]-[0019], wherein the one or more processors further determine whether amplitude of the partial waveform is equal to or more than an amplitude threshold value (Figs. 2 & 5-6; [0011], [0025]-[0029], & [0040]: CPU 11 performs this function, in step S7, determines whether the amplitude of the waveform between the first and second timings (partial waveform) is equal to or more than a predetermined threshold (third threshold TH_A), Fig. 5 depicts the amplitude threshold concept), and,
in the counting, count one step for the partial waveform ([0025]-[0029]: step S8 of the flowchart) when the time width is determined as falling within the reference range ([0025]-[0029]: step S6 is a required condition that checks if the first width is within a predetermined range) and amplitude of the partial waveform is determined as being equal to or more than the amplitude threshold value (Figs. 2 & 6b; [0025]-[0029] & [0040]: CPU 11 performs this function, if both the time width check (S6) where time width (T) is determined to fall within the predetermined range, and the amplitude check (S7), where the amplitude of the waveform is determined to be equal to or more than the amplitude threshold TH_A, proceed to the counting step (S8), requires both conditions to be satisfied before counting the step).
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Regarding dependent claim 8, Matsumoto, teaches:
The measurement device according to claim 7 (Figs. 1 & 2; [0011]-[0019], wherein the one or more processors further determine the amplitude threshold value (Figs. 1, 2, & 6b; [0011], [0025]-[0029], & [0040]: CPU 11 performs this function, determines the value of the amplitude threshold, which is referred to as the third threshold TH_A) based on amplitude of the acceleration waveform (Figs. 6a-6b; [0025]-[0029] & [0040]: figure further illustrates the threshold TH_A being determined based on RACC_F_max-min, which is a measure of the amplitude of the recent acceleration waveform, where CPU 11 varies the amplitude threshold TH_A based on RACC_F_max-min (measure of the amplitude of the acceleration waveform), which is the difference between the maximum and minimum values of the acceleration waveform RACC_F over a recent period (e.g., the last 1 second), Fig. 6a established TH_A as the amplitude threshold value on the Y-axis used to evaluate the partial waveform, Fig. 6b defines the mathematical/logical relationship where TH_A is a function of RACC_F_max-min (amplitude of the acceleration waveform on the X-axis)).
Claims 3-6, 9, 11-15, & 17-21 are rejected under 35 U.S.C. 103 as being unpatentable over Matsumoto, in view of Unuma et al. (US 6941239 B2, Pat. Date Sep. 6, 2005, hereinafter Unuma), and further in view of Taniguchi.
Regarding dependent claim 3, Matsumoto, teaches:
The measurement device according to claim 1 (Fig. 2; [0011]-[0012], [0015] & [0020]) wherein determining the state of the user (Figs. 3b & 4; ([0006]-[0008], [0011]-[0012], [0015], [0020]-[0028], [0031]-[0033] & [0035]-[0038]) includes determining the state of the user to be a walking state (Fig. 6a; [Overview], [0006]-[0008], [0015], [0020]-[0028], [0031]-[0033], [0035]-[0038], [Claim 1], [Claim 3] & [Claim 5])
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Matsumoto, is silent in regard to:
when the amplitude of the acceleration waveform is less than the first reference value
However, Unuma, further teaches:
when the amplitude of the acceleration waveform is less than the first reference value (Figs. 5, 7, 33 & 47; [Abstract], [Col. 3, ll. 48-67], [Col. 4, ll. 1-17, 24, & 35-39 ], [Col. 8, ll. 59-67], [Col. 9, ll. 1-2], [Col. 10, ll. 17-32], [Col. 30, ll. 48-67], [Col. 31, ll. 1-67], [Col. 32, ll. 1-65], [Col. 33, ll. 8-18], [Col. 34, ll. 12-26, 37-59 & 62-67], [Col. 35, ll. 1-67], [Col. 36, ll. 1-31], [Col. 40, ll. 58-67], [Col. 41, ll. 1-66] & [Col. 42, ll. 5-46]: teaches motion recognition is achieved by evaluating multiple characteristics of the acceleration signal, including time-domain properties (amplitude), and teaches that an amplitude less than a first reference value (0.8 G for running) but above a very low threshold (0.006 G) indicates walking, further defines “leisurely walking” with a peak likelihood at S = 0.1 G, and “brisk walking” with a peak at S = 0.5 G, both subsets of the broader “walking” state, and teaches that lower acceleration amplitudes (e.g., less that the second reference value of 0.5G used for running) are associated with walking states, and teachings determining a step frequency, where a step count (count value) that is less than the threshold for running would correspond to a walking state)
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining a state of the user to be a walking state when amplitude of the acceleration waveform is less than the first reference value, of Unuma to Matsumoto, to attain by combination of teachings, using a step-counting device that adjusts its parameters based on a user state, using the maximum acceleration amplitude over the last second to distinguish between low-intensity motion (walking) and high-intensity motion (running), and setting the valid time-width range for a step, of Matsumoto. To improve by modifying with the teachings of Unuma, that combines characteristics such as amplitude, frequency, and step-derived timing, to recognize “more complicated motions”, recognizing that “running downstairs” would have a high step rate (count) similar to running on a flat ground, but a different impact profile (acceleration amplitude) due to the descent, and a decision rule that can distinguish between a high-step-rate motion with low amplitude (downstairs running) and a high-step rate motion with high amplitude (flat-ground running),using selection and combination of pre-existing threshold values, to yield predictable results (KSR).
Matsumoto, in combination with Unuma, are silent in regard to:
and the count value is less than the piece count threshold value.
However, Taniguchi, further teaches:
and the count value is less than the piece count threshold value (Figs. 7 & 9; [0045]-[0050], [0054]-[0055], [0061]-[0062], [0074]-[0076], [0083], [0085], [0091]-[0093], [0095]-[0096] & [0108]-[0118]: teaches using a count value to distinguish between walking and other states like resting body movement, the calculation unit calculates a step count based on the number of vibrations, determines whether to output a step count for a walking sate or a resting body movement count by comparing a Y-axis PIM value (analogous to amplitude) against a walking threshold value (Th), establishing using a count value and a threshold to identify a walking state).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Matsumoto’s measurement device and step counting logic with Taniguchi’s use of zero-crossing counts (ZC) and teachings of classifying walking sub-states (i.e., such as slow walking) using vibration intensity (amplitude) thresholds, and Unuma’s amplitude boundaries (technical methodology) to ensure that a walking state is determined when the frequency/count of events is below a certain “piece count threshold” (e.g., such as a threshold for running frequency), verifying that an acceleration amplitude is less than a reference value (i.e., threshold for running), motivating experimentation and optimization to accurately distinguish slow/normal walking from fast running and/or erroneous noise, by combining prior art elements according to known methods to yield predictable results (KSR).
Regarding dependent claim 4, Matsumoto, teaches:
The measurement device according to claim 1 (Fig. 2; [0011], [0015] & [0020], wherein determining the state of the user (Figs. 3b & 4; [0024]-[0028]) includes
when the amplitude of the acceleration waveform ([0024]-[0028]: processes the acceleration waveform and uses its amplitude for determinations, the amplitude of the acceleration waveform during the period between the first timing and the second timing is equal to or greater than a third threshold value TH_A) is less than a first reference value (Fig. 4; [0024]-[0028] & [0035]-[0046]: uses a first threshold value TH_S as an upper bound for a valid step’s time width, using the first reference value as an upper bound, Fig. 4 depicts TH_S and TH_L) and equal to or more than a second reference value smaller than the first reference value (Figs. 5 & 6a; [0024]-[0028], [0035]-[0046] & [Claim 6]: discloses using a first (Sa) and second (Sb) reference value form amplitude to determine state (walking/running), the second threshold value TH_L is the lower bound for the time width, analogous to the use of a third threshold value TH_A to ensure the amplitude is high enough to count, Fig. 5 illustrates the amplitude and the concept of a minimum threshold)
Matsumoto, is silent in regard to:
of running down stairs
However, Unuma, further teaches:
of running down stairs ([Col. 18, ll. 45-52], [Col. 31, ll. 28-67], [Col. 32, ll. 1-65], [Col. 33, ll. 6-18], [Col. 35, ll. 66-67] & [Col. 36, ll. 1-31]: defines a “running” state using a performance function Wrun (S:0.5,0.8), where parameter a is a lower threshold (0.5G) and b is an upper threshold (0.8G), state of running is recognized when the amplitude S is greater than b (0.8G), with a likelihood of increasing linearly from a to b (running), also teaches concept of using a first reference value (b=0.8G) and a second, smaller reference value (a=0.5G) to define a range for a specific motion state (running))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining a state of user to be a running downstairs state, of Unuma to Matsumoto, to attain by combination of teachings, using a step-counting device that adjusts its parameters based on a user state, using the maximum acceleration amplitude over the last second to distinguish between low-intensity motion (walking) and high-intensity motion (running), and setting the valid time-width range for a step, of Matsumoto. To improve by modifying with the teachings of Unuma, that combines characteristics such as amplitude, frequency, and step-derived timing, to recognize “more complicated motions”, allowing the system to determine a user’s state (e.g., running walking) based on the amplitude of an acceleration waveform, and using specific amplitude threshold values for the determination (e.g., 0.5 G and 0.8 G), and also based on step count or gait cycle frequency, from which a step count threshold can be derived, and yield predictable results (KSR).
Matsumoto, in combination with Unuma, are silent in regard to:
determining the state of the user to be the running downstairs state and the count value is equal to or more than the piece count threshold value.
However, Taniguchi, further teaches:
determining the state of the user to be the running downstairs state ([0008], [0045] & [Claim 8]: discloses determining a downstairs state and lists general categories) and the count value (Fig. 4a; [0083]-[0085] & [0093]: calculates a “count value” (ZC value) based on the acceleration waveform, Fig. 4a illustrates the method of counting zero-crossings) is equal to or more than the piece count threshold value ([0108]-[0112]: compares the calculated count value (ZC value) against a threshold (i.e., walking threshold Th) to determine if a valid step has occurred, validating the count).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Matsumoto with those of Taniguchi and Unuma, taking Taniguchi’s methodology to apply a downstairs determination and a count value to the threshold-based framework of Matsumoto, and take Unuma as the motivation to break down/separate a general motion (i.e., downstairs) into specific speed states like “running down stairs”. A POSITA trying to create a device that can distinguish between different intensities of stair descent (e.g., walking downstairs vs. running downstairs), would be motivated by experimentation and optimization, to combine the prior art references, and yield predictable results (KSR).
Regarding dependent claim 5, Matsumoto, teaches:
The measurement device according to claim 1 (Figs. 1 & 2; [0011]-[0020], wherein determining the reference range (Fig. 4; [0024]-[0028] & [0038]: describes determining a “predetermined range” for a time width T (i.e., a reference range), range is defined by a lower limit (first threshold TH_S) and an upper limit (second threshold TH_L)) includes determining a lower-limit value of the reference range ([0024]-[0028]: discloses the first threshold value TH_S functions as a lower-limit value for the valid time width T, acting as a lower boundary of acceptable range) as a first lower-limit value ([0024]-[0028] & [0038]: teaches varying the lower limit of the time width range (TH_S) based on the user’s state, setting a lower value for TH_S (63 ms, the “first fixed value Fix 1”) when the user’s state is estimated to be “running” (RACC_F_max >= Sb).
Matsumoto, is silent in regard to:
when the state of the user is determined to be the running downstairs state,
However, Unuma, further teaches:
when the state of the user is determined to be the downstairs state (Figs. 13-14; [Col. 18, ll. 45-52], [Col. 33, ll. 21-67], [Col. 34, ll. 1-49 & 62-67], [Col. 35, ll.1-67] & [Col. 36, ll. 1-31]: teaches motivation and method for creating sub-states like running downstairs),
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Matsumoto (varying thresholds based on a user state) with those of Unuma (subdividing motions into speed-based sub-states), when the state of the user is determined to be the running downstairs state. To attain by modifying the measuring device of Matsumoto, that varies a time-based threshold’s lower limit based on a general walking or running state, with the teachings, of Unuma, that provides a method for determining more specific user states including “walking” and “running downstairs”, extending Matsumoto’s teaching of setting a specific parameter value (a first lower-limit value) for the newly defined state. Optimally selecting tuned lower-limit values (“first lower-limit value” for downstairs and the larger “second lower-limit value” for walking) for the time-width reference range in Matsumoto, improving the analogous parameter, with a predictable variation, that yields expected improvement in accuracy and results (KSR).
Regarding dependent claim 6, Matsumoto, teaches:
The measurement device according to claim 3 (Fig. 2; [0011]-[0019], wherein determining the reference range (Fig. 4; [0024]-[0028] & [0038]: describes determining a “predetermined range” for a time width T (i.e., a reference range), range is defined by a lower limit (first threshold TH_S) and an upper limit (second threshold TH_L)) includes determining a lower-limit value of the reference range (Fig. 4; [0024]-[0028]) as a first lower-limit value ([0024]-[0028] & [0038]: teaches varying the lower limit of the time width range (TH_S) based on the user’s state, setting a lower value for TH_S (63 ms, the “first fixed value Fix 1”) when the user’s state is determined to be “running” (RACC_F_max >= Sb) and determining a lower-limit value of the reference range as a second lower-limit value larger than the first lower-limit value when the state of the user is determined to be the walking state ([0024]-[0028] & [0038]-[0039]: teaches setting the lower limit TH_S to a larger value (125 ms, the “second fixed value Fix2”) when the user’s state is determined to be “walking” (RACC_F_max < Sa), and states that the threshold for walking is larger than the threshold for running).
Matsumoto, is silent in regard to:
when the state of the user is determined to be the running downstairs state,
However, Unuma, further teaches:
when the state of the user is determined to be the running downstairs state (Figs. 13-14; [Col. 18, ll. 45-52], [Col. 33, ll. 21-67], [Col. 34, ll. 1-49 & 62-67], [Col. 35, ll.1-67] & [Col. 36, ll. 1-31]),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Matsumoto (varying thresholds based on a user state) with those of Unuma (subdividing motions into speed-based sub-states), when the state of the user is determined to be the running downstairs state. To attain by modifying the measuring device of Matsumoto, that varies a time-based threshold’s lower limit based on a general walking or running state, with the teachings, of Unuma, that provides a method for determining more specific user states including “walking” and “running downstairs”, extending Matsumoto’s teaching of setting a specific parameter value (a first lower-limit value) for the newly defined state. Matsumoto teaches the concept of varying a lower-limit threshold value based on the user’s determined state, disclosing the first threshold value TH_S is set to a larger value (125 ms) when the user is walking and a smaller value (63 ms) when the user is running. Taniguchi and Unuma teach the downstairs state, and Unuma further teaches the principle of subdividing motions into different intensity/speed sub-states. Then optimally selecting tuned lower-limit values (“first lower-limit value” for downstairs and the larger “second lower-limit value” for walking) for the time-width reference range in Matsumoto, improving the analogous parameter, with a predictable variation, that yields expected improvement in accuracy and results (KSR).
Regarding independent claim 9, Matsumoto, teaches:
A measurement method executed by a measurement device including an acceleration sensor (Fig. 2; [0010]-[0011], [0015], & [0020]), comprising:
acquiring time-series acceleration data output by the acceleration sensor (Fig. 2; [0006]-[0008], [0010]-[0011], [0015], & [0020]: step S1, CPU 11 of measurement device 1 acquires acceleration data for each of the three axes from the sensor unit 14);
specifying, based on the acquired time-series acceleration data, first timing at which acceleration goes above an acceleration reference value (Figs. 3a & 3b; [0012], [0015] & [0022]-[0024]: uses zero-crossing point as the acceleration reference value, the “first timing” is when the waveform crosses from negative to positive value, Fig. 3a illustrates timing t1 at the zero-crossing point) and second timing at which the acceleration goes below the acceleration reference value (Figs. 3a & 3b; [0012], [0015] & [0022]-[0028]: step S4 specifies timing when waveform goes from negative to positive & step S5 specifies when timing goes from positive to negative, a crossing of a zero reference value, and teaches analyzing waveforms with positive and negative components, the “second timing” is when the waveform crosses from positive to negative value, establishing “zero” as the reference value, figure 3b illustrates timings t1 and t2 at the zero-crossing point);
determining a reference range for a time width from the first timing to the second timing (Figs. 3b & 4; [0020]-[0028]: reference range is defined by a lower limit TH_S and upper limit TH_L for the time width T (time span), delineates walking or running states from noise and other factors) based on the determined state of the user ([0006]-[0008], [0015], [0020]-[0028], [0031]-[0033] & [0035]-[0038]);
determining whether the time width falls within the determined reference range (Figs. 3b & 4; [0024]-[0028]: reference range is defined by a lower threshold TH_S and an upper threshold TH_L, time span T is interpreted as time width, delineates walking or running states from noise and other factors); and counting one step for a partial waveform from the first timing to the second timing in the acceleration waveform when the time width is determined as falling within the reference range (Figs. 2-3; [0022]-[0030]: teaches in step S8 that if the time width is within the range the waveform is determined to be from walking/running and counted as a step, if not, process loops back, waveform is not counted, Fig. 2, flowchart of step count measurement process).
Matsumoto, in combination with Unuma, are silent in regard to:
determining a state of a user wearing the acceleration sensor based on amplitude of an acceleration waveform corresponding to the time-series acceleration data and a count value of zero-crossing points within predetermined time of at least either the first timing or the second timing; wherein the determining the state of the user includes:
determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value,
However, Taniguchi, further teaches:
determining a state of a user wearing the acceleration sensor based on amplitude of an acceleration waveform corresponding to the time-series acceleration data (Fig. 1; [0013]-[0015], [0030], [0034], [0038], [0048]-[0057], [0061]-[0070], [0074], [0083]-[0085] & [0116]-[0120]: teaches body motion determination unit 9 determines the user’s state (e.g., walking, running, ascending stairs, descending stairs) using the PIM value (based on amplitude) and the ZC value (zero-crossing count)) and a count value of zero-crossing points within predetermined time of at least either the first timing or the second timing (Figs. 1 & 10-13; [0013]-[0015], [0030], [0034], [0038], [0048]-[0057], [0061]-[0070], [0074], [0083]-[0085] & [0116]-[0118]: teaches body motion determination unit 9 determines the user’s state (e.g., walking, running, ascending stairs, descending stairs) using the PIM value (based on amplitude) and the ZC value (zero-crossing count), Figs. 10-12 show classification based on PIM values, Fig. 13 shows using DC values for further distinction, the classification determines the user’s state based on amplitude and a zero-crossing count); wherein the determining the state of the user includes:
determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value (Figs. 9 & 11; [Abstract], [0010]-[0014], [0045]-[0046], [0116]-[0120] & [0125]-[0127]: teaches the system is designed to classify motions like “descending stairs”, Figs. 9 & 11 identify the PIM region for “descending stairs”, PIM 95, “quickly descending stairs”, PIM 96, and “slowly descending stairs”, PIM 97, the classification is based on the PIM values (magnitude) and using ZC values (zero-crossing count) in its processing, state is determined by checking if ZC/PIM values fall within specific thresholds),
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the step-counting method of Matsumoto with Taniguchi’s “ZC/Amplitude-based” state determination, incorporating the advanced state-determination logic of Taniguchi, that can distinguish different types of motion using a ZC calculation unit to count zero-crossings and a PIM calculation unit to measure intensity/amplitude. Unuma provides a general principle of motion recognition using a database of characteristic quantities, further supporting the motivation to use the determined state (e.g., running downstairs) for subsequent processing. A POSITA would have been motivated to combine the precision of Matsumoto’s timing-based step counting methodology with Taniguchi’s methodology to improve the method to identify different states such as a “running downstairs” state that would provide the logical trigger to select the specific TH_S range for that motion in Matsumoto, improving the counting accuracy and functionality of the wearable device, allowing the system to distinguish between descending stairs slowly, normal pace, or quickly for more precise fitness tracking and calculation. The modification includes the combination of the prior art references to yield predictable results of enhanced user state detection (KSR).
Regarding dependent claim 11, Matsumoto, teaches:
The measurement method according to claim 9 (Fig. 2; [0011]-[0012], [0015], & [0020]: device includes sensor unit 14 with a 3-axis acceleration sensor), wherein determining the state of the user (Figs. 3b & 4; [0006]-[0008], [0011]-[0012], [0015], [0020]-[0028], [0031]-[0033] & [0035]-[0038]) includes determining the state of the user to be a walking state (Fig. 6a; [Overview], [0006]-[0008], [0015], [0020]-[0028], [0031]-[0033], [0035]-[0038], [Claim 1], [Claim 3] & [Claim 5])
Matsumoto, is silent in regard to:
when the amplitude of the acceleration waveform is less than the first reference value
However, Unuma, further teaches:
when the amplitude of the acceleration waveform is less than the first reference value (Figs. 5, 7, 33 & 47; [Abstract], [Col. 3, ll. 48-67], [Col. 4, ll. 1-17, 24, & 35-39 ], [Col. 8, ll. 59-67], [Col. 9, ll. 1-2], [Col. 10, ll. 17-32], [Col. 30, ll. 48-67], [Col. 31, ll. 1-67], [Col. 32, ll. 1-65], [Col. 33, ll. 8-18], [Col. 34, ll. 12-26, 37-59 & 62-67], [Col. 35, ll. 1-67], [Col. 36, ll. 1-31], [Col. 40, ll. 58-67], [Col. 41, ll. 1-66] & [Col. 42, ll. 5-46]: teaches motion recognition is achieved by evaluating multiple characteristics of the acceleration signal, including time-domain properties (amplitude), and teaches that an amplitude less than a first reference value (0.8 G for running) but above a very low threshold (0.006 G) indicates walking, further defines “leisurely walking” with a peak likelihood at S = 0.1 G, and “brisk walking” with a peak at S = 0.5 G, both subsets of the broader “walking” state, and teaches that lower acceleration amplitudes (e.g., less that the second reference value of 0.5G used for running) are associated with walking states, and teachings determining a step frequency, where a step count (count value) that is less than the threshold for running would correspond to a walking state)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining a state of the user to be a walking state when amplitude of the acceleration waveform is less than the first reference value, of Unuma to Matsumoto, to attain by combination of teachings, using a step-counting device that adjusts its parameters based on a user state, using the maximum acceleration amplitude over the last second to distinguish between low-intensity motion (walking) and high-intensity motion (running), and setting the valid time-width range for a step, of Matsumoto. To improve by modifying with the teachings of Unuma, that combines characteristics such as amplitude, frequency, and step-derived timing, to recognize “more complicated motions”, recognizing that “running downstairs” would have a high step rate (count) similar to running on a flat ground, but a different impact profile (acceleration amplitude) due to the descent, and a decision rule that can distinguish between a high-step-rate motion with low amplitude (downstairs running) and a high-step rate motion with high amplitude (flat-ground running),using selection and combination of pre-existing threshold values, to yield predictable results (KSR).
Matsumoto, in combination with Unuma, are silent in regard to:
and the count value is less than the piece count threshold value.
However, Taniguchi, further teaches:
and the count value is less than the piece count threshold value (Figs. 7 & 9; [0045]-[0050], [0054]-[0055], [0061]-[0062], [0074]-[0076], [0083], [0085], [0091]-[0093], [0095]-[0096] & [0108]-[0118]: teaches using a count value to distinguish between walking and other states like resting body movement, the calculation unit calculates a step count based on the number of vibrations, determines whether to output a step count for a walking sate or a resting body movement count by comparing a Y-axis PIM value (analogous to amplitude) against a walking threshold value (Th), establishing using a count value and a threshold to identify a walking state).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Matsumoto’s measurement device and step counting logic with Taniguchi’s use of zero-crossing counts (ZC) and teachings of classifying walking sub-states (i.e., such as slow walking) using vibration intensity (amplitude) thresholds, and Unuma’s amplitude boundaries (technical methodology) to ensure that a walking state is determined when the frequency/count of events is below a certain “piece count threshold” (e.g., such as a threshold for running frequency), verifying that an acceleration amplitude is less than a reference value (i.e., threshold for running), motivating experimentation and optimization to accurately distinguish slow/normal walking from fast running and/or erroneous noise, by combining prior art elements according to known methods to yield predictable results (KSR).
Regarding dependent claim 12, Matsumoto, teaches:
The measurement method according to claim 9 (Fig. 2; [0011], [0015], & [0020]: device includes sensor unit 14 with a 3-axis acceleration sensor), wherein determining the state of the user (Figs. 3b & 4; [0024]-[0028]) includes
when the amplitude of the acceleration waveform ([0024]-[0028]) is less than a first reference value (Fig. 4; [0024]-[0028] & [0035]-[0046]) and equal to or more than a second reference value smaller than the first reference value (Figs. 5 & 6a; [0024]-[0028], [0035]-[0046] & [Claim 6]: discloses using a first (Sa) and second (Sb) reference value form amplitude to determine state (walking/running), the second threshold value TH_L is the lower bound for the time width, analogous to the use of a third threshold value TH_A to ensure the amplitude is high enough to count, Fig. 5 illustrates the amplitude and the concept of a minimum threshold)
Matsumoto, is silent in regard to:
of running down stairs
However, Unuma, further teaches:
of running down stairs ([Col. 18, ll. 45-52], [Col. 31, ll. 28-67], [Col. 32, ll. 1-65], [Col. 33, ll. 6-18], [Col. 35, ll. 66-67] & [Col. 36, ll. 1-31]: defines a “running” state using a performance function Wrun (S:0.5,0.8), where parameter a is a lower threshold (0.5G) and b is an upper threshold (0.8G), state of running is recognized when the amplitude S is greater than b (0.8G), with a likelihood of increasing linearly from a to b (running), also teaches concept of using a first reference value (b=0.8G) and a second, smaller reference value (a=0.5G) to define a range for a specific motion state (running))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining a state of user to be a running downstairs state, of Unuma to Matsumoto, to attain by combination of teachings, using a step-counting device that adjusts its parameters based on a user state, using the maximum acceleration amplitude over the last second to distinguish between low-intensity motion (walking) and high-intensity motion (running), and setting the valid time-width range for a step, of Matsumoto. To improve by modifying with the teachings of Unuma, that combines characteristics such as amplitude, frequency, and step-derived timing, to recognize “more complicated motions”, allowing the system to determine a user’s state (e.g., running walking) based on the amplitude of an acceleration waveform, and using specific amplitude threshold values for the determination (e.g., 0.5 G and 0.8 G), and also based on step count or gait cycle frequency, from which a step count threshold can be derived, and yield predictable results (KSR).
Matsumoto, in combination with Unuma, are silent in regard to:
determining the state of the user to be the running downstairs state and the count value is equal to or more than the piece count threshold value.
However, Taniguchi, further teaches:
determining the state of the user to be the running downstairs state ([0008], [0045] & [Claim 8]: discloses determining a downstairs state and lists general categories) and the count value (Fig. 4a; [0083]-[0085] & [0093]: calculates a “count value” (ZC value) based on the acceleration waveform, Fig. 4a illustrates the method of counting zero-crossings) is equal to or more than the piece count threshold value ([0108]-[0112]: compares the calculated count value (ZC value) against a threshold (i.e., walking threshold Th) to determine if a valid step has occurred, validating the count).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Matsumoto with those of Taniguchi and Unuma, taking Taniguchi’s methodology to apply a downstairs determination and a count value to the threshold-based framework of Matsumoto, and take Unuma as the motivation to break down/separate a general motion (i.e., downstairs) into specific speed states like “running down stairs”. A POSITA trying to create a device that can distinguish between different intensities of stair descent (e.g., walking downstairs vs. running downstairs), would be motivated by experimentation and optimization, to combine the prior art references, and yield predictable results (KSR).
Regarding dependent claim 13, Matsumoto, teaches:
The measurement method according to claim 9 (Fig. 2; [0011]-[0020]: device includes sensor unit 14 with a 3-axis acceleration sensor), wherein determining the reference range ([0024]-[0028] & [0038]: describes determining a “predetermined range” for a time width T (i.e., a reference range), range is defined by a lower limit (first threshold TH_S) and an upper limit (second threshold TH_L)) includes determining a lower-limit value of the reference range ([0024]-[0028]: discloses the first threshold value TH_S functions as a lower-limit value for the valid time width T, acting as a lower boundary of acceptable range) as a first lower-limit value ([0024]-[0028] & [0038]: teaches varying the lower limit of the time width range (TH_S) based on the user’s state, setting a lower value for TH_S (63 ms, the “first fixed value Fix 1”) when the user’s state is estimated to be “running” (RACC_F_max >= Sb)
Matsumoto, is silent in regard to:
when the state of the user is determined to be the running downstairs state,
However, Unuma, further teaches:
when the state of the user is determined to be the downstairs state (Figs. 13-14; [Col. 18, ll. 45-52], [Col. 33, ll. 21-67], [Col. 34, ll. 1-49 & 62-67], [Col. 35, ll.1-67] & [Col. 36, ll. 1-31]: teaches motivation and method for creating sub-states like running downstairs),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Matsumoto (varying thresholds based on a user state) with those of Unuma (subdividing motions into speed-based sub-states), when the state of the user is determined to be the running downstairs state. To attain by modifying the measuring device of Matsumoto, that varies a time-based threshold’s lower limit based on a general walking or running state, with the teachings, of Unuma, that provides a method for determining more specific user states including “walking” and “running downstairs”, extending Matsumoto’s teaching of setting a specific parameter value (a first lower-limit value) for the newly defined state. Optimally selecting tuned lower-limit values (“first lower-limit value” for downstairs and the larger “second lower-limit value” for walking) for the time-width reference range in Matsumoto, improving the analogous parameter, with a predictable variation, that yields expected improvement in accuracy and results (KSR).
Regarding dependent claim 14, Matsumoto, teaches:
The measurement method according to claim 9 (Fig. 2; [0011]-[0020]: device includes sensor unit 14 with a 3-axis acceleration sensor), further comprising:
determining whether amplitude of the partial waveform is equal to or more than an amplitude threshold value (Figs. 2 & 5-6; [0011], [0025]-[0029], & [0040]: CPU 11 performs this function, in step S7, determines whether the amplitude of the waveform between the first and second timings (partial waveform) is equal to or more than a predetermined threshold (third threshold TH_A), Fig. 5 depicts the amplitude threshold concept); and
counting one step for the partial waveform ([0025]-[0029]: step S8 of the flowchart) when the time width is determined as falling within the reference range ([0025]-[0029]: step S6 is a required condition that checks if the first width is within a predetermined range) and amplitude of the partial waveform is determined as being equal to or more than the amplitude threshold value (Figs. 2 & 6b; [0025]-[0029] & [0040]: CPU 11 performs this function, if both the time width check (S6) where time width (T) is determined to fall within the predetermined range, and the amplitude check (S7), where the amplitude of the waveform is determined to be equal to or more than the amplitude threshold TH_A, procced to the counting step (S8), requires both conditions to be satisfied before counting the step).
Regarding independent claim 15, Matsumoto, teaches:
A non-transitory computer readable recording medium ([0010]-[0020]: storage 16 (non-transitory computer readable recording medium), storing a program executable by one or more processors in a measurement device ([0010]-[0020]: measurement device 1 with a CPU 11 and a sensor unit 14, device executes a program stored in memory, storage unit 16, to perform),
wherein the measurement device includes an acceleration sensor ([0010]-[0020]: measurement device 1 with a CPU 11 and a sensor unit 14 including an acceleration sensor, device executes a program stored in memory, storage unit 16, to perform), and
wherein the program causes the one or more processors to perform ([0010]-[0030]: measurement device 1 with a CPU 11 and a sensor unit 14 including an acceleration sensor, device executes a program stored in memory, storage unit 16, to perform the methodology below):
acquiring time-series acceleration data output by the acceleration sensor (Figs. 1-2; [0006]-[0008], [0010]-[0011], [0015], & [0020]: step S1, CPU 11 of measurement device 1 acquires acceleration data for each of the three axes from the sensor unit 14); specifying, based on the acquired time-series acceleration data, first timing at which acceleration goes above an acceleration reference value (Figs. 3a & 3b; [0012], [0015] & [0022]-[0024]: uses zero-crossing point as the acceleration reference value, the “first timing” is when the waveform crosses from negative to positive value, Fig. 3a illustrates timing t1 at the zero-crossing point) and second timing at which the acceleration goes below the acceleration reference value (Figs. 3a & 3b; [0012], [0015] & [0022]-[0024]: step S4 specifies timing when waveform goes from negative to positive & step S5 specifies when timing goes from positive to negative, a crossing of a zero reference value, and teaches analyzing waveforms with positive and negative components, the “second timing” is when the waveform crosses from positive to negative value, establishing “zero” as the reference value, figure 3b illustrates timings t1 and t2 at the zero-crossing point);
determining a reference range for a time width from the first timing to the second timing ( Figs. 3b & 4; [0020]-[0028]: step S6, the CPU determines a permissible range for the time width T between t1 and t2, the range is defined by a first threshold TH_S and a second threshold TH_L for the time width T (time span), delineates walking or running states from noise and other factors) based on the determined state of the user (Fig. 6a; [0006]-[0008], [0015], [0020]-[0028], [0031]-[0033] & [0035]-[0038]);
determining whether the time width falls within the determined reference range (Figs. 3b & 4; [0024]-[0028]: reference range is defined by a lower threshold TH_S and an upper threshold TH_L, time span T is interpreted as time width and CPU determines a permissible reference range for the time width T between t1 and t2, step S6, where the CPU judges whether the calculated time width T falls within the range TH_S/TH_L); and counting one step for a partial waveform from the first timing to the second timing in the acceleration waveform when the time width is determined as falling within the reference range (Figs. 2-3; [0022]-[0030]: teaches in step S8 that if the time width is within the range the waveform is determined to be from walking/running and counted as a step, if not, process loops back, waveform is not counted, Fig. 2, flowchart of step count measurement process).
Matsumoto, in combination with Unuma, are silent in regard to:
determining a state of a user wearing the acceleration sensor based on amplitude of an acceleration waveform corresponding to the time-series acceleration data and a count value of zero-crossing points within predetermined time of at least either the first timing or the second timing; wherein the determining the state of the user includes:
determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value,
However, Taniguchi, further teaches:
determining a state of a user wearing the acceleration sensor based on amplitude of an acceleration waveform corresponding to the time-series acceleration data (Fig. 1; [0013]-[0015], [0030], [0034], [0038], [0048]-[0057], [0061]-[0070], [0074], [0083]-[0085] & [0116]-[0120]: teaches body motion determination unit 9 determines the user’s state (e.g., walking, running, ascending stairs, descending stairs) using the PIM value (based on amplitude) and the ZC value (zero-crossing count)) and a count value of zero-crossing points within predetermined time of at least either the first timing or the second timing (Figs. 1 & 10-13; [0013]-[0015], [0030], [0034], [0038], [0048]-[0057], [0061]-[0070], [0074], [0083]-[0085] & [0116]-[0118]: teaches body motion determination unit 9 determines the user’s state (e.g., walking, running, ascending stairs, descending stairs) using the PIM value (based on amplitude) and the ZC value (zero-crossing count), Figs. 10-12 show classification based on PIM values, Fig. 13 shows using DC values for further distinction, the classification determines the user’s state based on amplitude and a zero-crossing count); wherein the determining the state of the user includes:
determining the state of the user to be a running downstairs state of running down stairs when the amplitude of the acceleration waveform is less than a first reference value and the count value is equal to or more than a piece count threshold value (Figs. 9 & 11; [Abstract], [0010]-[0014], [0045]-[0046], [0116]-[0120] & [0125]-[0127]: teaches the system is designed to classify motions like “descending stairs”, Figs. 9 & 11 identify the PIM region for “descending stairs”, PIM 95, “quickly descending stairs”, PIM 96, and “slowly descending stairs”, PIM 97, the classification is based on the PIM values (magnitude) and using ZC values (zero-crossing count) in its processing, state is determined by checking if ZC/PIM values fall within specific thresholds),
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the step-counting method of Matsumoto with Taniguchi’s “ZC/Amplitude-based” state determination, incorporating the advanced state-determination logic of Taniguchi, that can distinguish different types of motion using a ZC calculation unit to count zero-crossings and a PIM calculation unit to measure intensity/amplitude. Unuma provides a general principle of motion recognition using a database of characteristic quantities, further supporting the motivation to use the determined state (e.g., running downstairs) for subsequent processing. A POSITA would have been motivated to combine the precision of Matsumoto’s timing-based step counting methodology with Taniguchi’s methodology to improve the method to identify different states such as a “running downstairs” state that would provide the logical trigger to select the specific TH_S range for that motion in Matsumoto, improving the counting accuracy and functionality of the wearable device, allowing the system to distinguish between descending stairs slowly, normal pace, or quickly for more precise fitness tracking and calculation. The modification includes the combination of the prior art references to yield predictable results of enhanced user state detection (KSR).
Regarding dependent claim 17, Matsumoto, teaches:
The non-transitory computer readable recording medium according to claim 15 ([0010]-[0020]), wherein determining the state of the user (Figs. 3b & 4; [0006]-[0008], [0011]-[0012], [0015], [0020]-[0028], [0031]-[0033] & [0035]-[0038]) includes determining a state of the user to be a walking state (Fig. 6a; [Overview], [0006]-[0008], [0015], [0020]-[0028], [0031]-[0033], [0035]-[0038], [Claim 1], [Claim 3] & [Claim 5])
Matsumoto, is silent in regard to:
when the amplitude of the acceleration waveform is less than the first reference value
However, Unuma, further teaches:
when the amplitude of the acceleration waveform (Figs. 48A, 48B, & 49; [Abstract], [Col. 3, ll. 48-67], [Col. 4, ll. 1-17, 24, & 35-39 ], [Col. 8, ll. 59-67], [Col. 9, ll. 1-2], [Col. 10, ll. 17-32], [Col. 30, ll. 48-67], [Col. 31, ll. 1-67], [Col. 32, ll. 1-65], [Col. 33, ll. 8-18], [Col. 34, ll. 12-26, 37-59 & 62-67], [Col. 35, ll. 1-67], [Col. 36, ll. 1-31], [Col. 40, ll. 58-67], [Col. 41, ll. 1-66] & [Col. 42, ll. 5-46]: discloses using the magnitude (amplitude) of the acceleration signal as a key parameter for motion recognition, which is achieved by evaluating multiple characteristics of the acceleration signal, including time-domain properties (amplitude), and teaches that an amplitude less than a first reference value (0.8 G for running) but above a very low threshold (0.006 G) indicates walking, further defines “leisurely walking” with a peak likelihood at S = 0.1 G, and “brisk walking” with a peak at S = 0.5 G, both subsets of the broader “walking” state, and teaches that lower acceleration amplitudes (e.g., less that the second reference value of 0.5G used for running) are associated with walking states, and teachings determining a step frequency, where a step count (count value) that is less than the threshold for running would correspond to a walking state) is less than a first reference value (Fig. 48B; [Col. 33, ll. 8-18] & [Col. 34, ll. 50-52: defines a specific amplitude (or equivalent spectrum power) threshold values to classify different states of motion, amplitude is the criteria for distinction, a “first reference value” (e.g., 0.8G for amplitude or a corresponding power value))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining a state of the user to be a walking state when amplitude of the acceleration waveform is less than the first reference value, of Unuma to Matsumoto, to attain by combination of teachings, using a step-counting device that adjusts its parameters based on a user state, using the maximum acceleration amplitude over the last second to distinguish between low-intensity motion (walking) and high-intensity motion (running), and setting the valid time-width range for a step, of Matsumoto. To improve by modifying with the teachings of Unuma, that combines characteristics such as amplitude, frequency, and step-derived timing, to recognize “more complicated motions”, recognizing that “running downstairs” would have a high step rate (count) similar to running on a flat ground, but a different impact profile (acceleration amplitude) due to the descent, and a decision rule that can distinguish between a high-step-rate motion with low amplitude (downstairs running) and a high-step rate motion with high amplitude (flat-ground running),using selection and combination of pre-existing threshold values, to yield predictable results (KSR).
Matsumoto, in combination with Unuma, are silent in regard to:
and the count value is less than the piece count threshold value.
However, Taniguchi, further teaches:
and the count value is less than the piece count threshold value (Figs. 7 & 9; [0045]-[0050], [0054]-[0055], [0061]-[0062], [0074]-[0076], [0083], [0085], [0091]-[0093], [0095]-[0096] & [0108]-[0118]: teaches using a count value to distinguish between walking and other states like resting body movement, the calculation unit calculates a step count based on the number of vibrations, determines whether to output a step count for a walking sate or a resting body movement count by comparing a Y-axis PIM value (analogous to amplitude) against a walking threshold value (Th), establishing using a count value and a threshold to identify a walking state).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Matsumoto’s measurement device and step counting logic with Taniguchi’s use of zero-crossing counts (ZC) and teachings of classifying walking sub-states (i.e., such as slow walking) using vibration intensity (amplitude) thresholds, and Unuma’s amplitude boundaries (technical methodology) to ensure that a walking state is determined when the frequency/count of events is below a certain “piece count threshold” (e.g., such as a threshold for running frequency), verifying that an acceleration amplitude is less than a reference value (i.e., threshold for running), motivating experimentation and optimization to accurately distinguish slow/normal walking from fast running and/or erroneous noise, by combining prior art elements according to known methods to yield predictable results (KSR).
Regarding dependent claim 18, Matsumoto, teaches:
The non-transitory computer readable recording medium according to claim 15 ([0010]-[0020]), wherein determining the state of the user (Figs. 3b & 4; [0024]-[0028]) includes
when the amplitude of the acceleration waveform ([0024]-[0028]) is less than a first reference value (Fig. 4; [0024]-[0028] & [0035]-[0046]) and equal to or more than a second reference value smaller than the first reference value (Figs. 5 & 6a; [0024]-[0028], [0035]-[046] & [Claim 6]: discloses using a first (Sa) and second (Sb) reference value form amplitude to determine state (walking/running), the second threshold value TH_L is the lower bound for the time width, analogous to the use of a third threshold value TH_A to ensure the amplitude is high enough to count, Fig. 5 illustrates the amplitude and the concept of a minimum threshold)
Matsumoto, is silent in regard to:
of running down stairs
However, Unuma, further teaches:
of running down stairs ([Col. 18, ll. 45-52], [Col. 31, ll. 28-67], [Col. 32, ll. 1-65], [Col. 33, ll. 6-18], [Col. 35, ll. 66-67] & [Col. 36, ll. 1-31]: defines a “running” state using a performance function Wrun (S:0.5,0.8), where parameter a is a lower threshold (0.5G) and b is an upper threshold (0.8G), state of running is recognized when the amplitude S is greater than b (0.8G), with a likelihood of increasing linearly from a to b (running), also teaches concept of using a first reference value (b=0.8G) and a second, smaller reference value (a=0.5G) to define a range for a specific motion state (running))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining a state of user to be a running downstairs state, of Unuma to Matsumoto, to attain by combination of teachings, using a step-counting device that adjusts its parameters based on a user state, using the maximum acceleration amplitude over the last second to distinguish between low-intensity motion (walking) and high-intensity motion (running), and setting the valid time-width range for a step, of Matsumoto. To improve by modifying with the teachings of Unuma, that combines characteristics such as amplitude, frequency, and step-derived timing, to recognize “more complicated motions”, allowing the system to determine a user’s state (e.g., running walking) based on the amplitude of an acceleration waveform, and using specific amplitude threshold values for the determination (e.g., 0.5 G and 0.8 G), and also based on step count or gait cycle frequency, from which a step count threshold can be derived, and yield predictable results (KSR).
Matsumoto, in combination with Unuma, are silent in regard to:
determining the state of the user to be the running downstairs state and the count value is equal to or more than the piece count threshold value.
However, Taniguchi, further teaches:
determining the state of the user to be the running downstairs state ([0008], [0045] & [Claim 8]: discloses determining a downstairs state and lists general categories) and the count value (Fig. 4a; [0083]-[0085] & [0093]: calculates a “count value” (ZC value) based on the acceleration waveform, Fig. 4a illustrates the method of counting zero-crossings) is equal to or more than the piece count threshold value ([0108]-[0112]: compares the calculated count value (ZC value) against a threshold (i.e., walking threshold Th) to determine if a valid step has occurred, validating the count).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Matsumoto with those of Taniguchi and Unuma, taking Taniguchi’s methodology to apply a downstairs determination and a count value to the threshold-based framework of Matsumoto, and take Unuma as the motivation to break down/separate a general motion (i.e., downstairs) into specific speed states like “running down stairs”. A POSITA trying to create a device that can distinguish between different intensities of stair descent (e.g., walking downstairs vs. running downstairs), would be motivated by experimentation and optimization, to combine the prior art references, and yield predictable results (KSR).
Regarding dependent claim 19, Matsumoto, teaches:
The non-transitory computer readable recording medium according to claim 15 ([0010]-[0020]), wherein determining the reference range ([0024]-[0028] & [0038]: describes determining a “predetermined range” for a time width T (i.e., a reference range), range is defined by a lower limit (first threshold TH_S) and an upper limit (second threshold TH_L)) includes determining a lower-limit value of the reference range ([0024]-[0028]: discloses the first threshold value TH_S functions as a lower-limit value for the valid time width T, acting as a lower boundary of acceptable range) as a first lower-limit value ([0024]-[0025] & [0038]: teaches varying the lower limit of the time width range (TH_S) based on the user’s state, setting a lower value for TH_S (63 ms, the “first fixed value Fix 1”) when the user’s state is estimated to be “running” (RACC_F_max >= Sb)
Matsumoto, is silent in regard to:
when the state of the user is determined to be the running downstairs state,
However, Unuma, further teaches:
when the state of the user is determined to be the downstairs state (Figs. 13-14; [Col. 18, ll. 45-52], [Col. 33, ll. 21-67], [Col. 34, ll. 1-49 & 62-67], [Col. 35, ll.1-67] & [Col. 36, ll. 1-31]: teaches motivation and method for creating sub-states like running downstairs),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Matsumoto (varying thresholds based on a user state) with those of Unuma (subdividing motions into speed-based sub-states), when the state of the user is determined to be the running downstairs state. To attain by modifying the measuring device of Matsumoto, that varies a time-based threshold’s lower limit based on a general walking or running state, with the teachings, of Unuma, that provides a method for determining more specific user states including “walking” and “running downstairs”, extending Matsumoto’s teaching of setting a specific parameter value (a first lower-limit value) for the newly defined state. Optimally selecting tuned lower-limit values (“first lower-limit value” for downstairs and the larger “second lower-limit value” for walking) for the time-width reference range in Matsumoto, improving the analogous parameter, with a predictable variation, that yields expected improvement in accuracy and results (KSR).
Regarding dependent claim 20, Matsumoto, teaches:
The non-transitory computer readable recording medium according to claim 15 ([0010]-[0020]), the program further causing the one or more processors to perform ([0010]-[0020]: measurement device 1 with a CPU 11 and a sensor unit 14 including an acceleration sensor, device executes a program stored in memory, storage unit 16, to perform the methodology below):
determining whether amplitude of the partial waveform is equal to or more than an amplitude threshold value (Figs. 2 & 5-6; [0011], [0025]-[0029], & [0040]: CPU 11 performs this function, in step S7, determines whether the amplitude of the waveform between the first and second timings (partial waveform) is equal to or more than a predetermined threshold (third threshold TH_A)); and
counting one step for the partial waveform ([0025]-[0029]: step S8 of the flowchart) when the time width is determined as falling within the reference range ([0025]-[0029]: step S6 is a required condition that checks if the first width is within a predetermined range) and amplitude of the partial waveform is determined as being equal to or more than the amplitude threshold value (Figs. 2 & 6b; [0025]-[0029] & [0040]: CPU 11 performs this function, if both the time width check (S6) where time width (T) is determined to fall within the predetermined range, and the amplitude check (S7), where the amplitude of the waveform is determined to be equal to or more than the amplitude threshold TH_A, procced to the counting step (S8)).
Regarding dependent claim 21, Matsumoto, teaches:
The measurement device according to claim 3 (Fig. 2; [0011]-[0012], [0015] & [0020]), wherein determining the state of the user (Figs. 3b & 4; ([0006]-[0008], [0011]-[0012], [0015], [0020]-[0028], [0031]-[0033] & [0035]-[0038]) includes determining the state of the user to be the walking state (Figs. 2 & 6a; [Overview], [0006]-[0008], [0015], [0020]-[0028], [0031]-[0033], [0035]-[0038], [Claim 1], [Claim 3] & [Claim 5]: discloses a device that determines a user’s state (walking/running) to count steps, Fig. 2 illustrates a flow chart for the step count measurement process)
Matsumoto, is silent in regard to:
when the amplitude of the acceleration waveform is less than the first reference value or when the amplitude of the acceleration waveform is less than a second reference value.
However, Unuma, further teaches:
when the amplitude of the acceleration waveform is less than the first reference value (Figs. 5, 7, 33 & 47; [Abstract], [Col. 3, ll. 48-67], [Col. 4, ll. 1-17, 24, & 35-39 ], [Col. 8, ll. 59-67], [Col. 9, ll. 1-2], [Col. 10, ll. 17-32], [Col. 30, ll. 48-67], [Col. 31, ll. 1-67,] [Col. 32, ll. 1-65], [Col. 34, ll. 12-26, 37-59 & 62-67], [Col. 35, ll. 1-67], [Col. 36, ll. 1-31], [Col. 40, ll. 58-67], [Col. 41, ll. 1-66] & [Col. 42, ll. 5-46]: teaches motion recognition is achieved by evaluating multiple characteristics of the acceleration signal, including time-domain properties (amplitude), and teaches that an amplitude less than a first reference value (0.8 G for running) but above a very low threshold (0.006 G) indicates walking, further defines “leisurely walking” with a peak likelihood at S = 0.1 G, and “brisk walking” with a peak at S = 0.5 G, both subsets of the broader “walking” state, and teaches that lower acceleration amplitudes (e.g., less that the second reference value of 0.5G used for running) are associated with walking states, and teachings determining a step frequency, where a step count (count value) that is less than the threshold for running would correspond to a walking state) or when the amplitude of the acceleration waveform is less than a second reference value (Fig. 49; [Col. 34, ll. 7-67], [Col. 35, ll. 1-67] & [Col. 36, ll. 1-31]: the leisurely-walking performance function shows a range of amplitudes (0.006G to 0.3G) that are considered part of a walking motion spectrum, where the lower end of this range (S < a) is considered the second reference value for a very slow, low-amplitude walk).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining a state of the user to be a walking state when amplitude of the acceleration waveform is less than the first reference value, or when the amplitude of the acceleration waveform is less than a second reference value, of Unuma to Matsumoto, to attain by combination of teachings, using a step-counting device that adjusts its parameters based on a user state, using the maximum acceleration amplitude over the last second to distinguish between low-intensity motion (walking) and high-intensity motion (running), and setting the valid time-width range for a step, of Matsumoto. The concept of identifying a walking state based on an amplitude being less than a second (lower) reference value is a well-known design choice. Unuma defines the entire spectrum of walking amplitudes, including a very low-amplitude range, and Taniguchi further confirms that identifying a “slow walk” is a routine objective in the field. A POSITA would find it obvious that a walking state can be determined by an amplitude being below a second lower threshold, as a direct extension of the logic in Matsumoto and documented in Unuma and Taniguchi. To improve, by modifying with the teachings of Unuma, that combines characteristics such as amplitude, frequency, and step-derived timing, to recognize “more complicated motions”, recognizing that “running downstairs” would have a high step rate (count) similar to running on a flat ground, but a different impact profile (acceleration amplitude) due to the descent, and a decision rule that can distinguish between a high-step-rate motion with low amplitude (downstairs running) and a high-step rate motion with high amplitude (flat-ground running),u sing selection and combination of pre-existing threshold values, to yield predictable results (KSR).
Matsumoto, in combination with Unuma, are silent in regard to:
and the count value is less than the piece count threshold value
However, Taniguchi, further teaches:
and the count value is less than the piece count threshold value (Figs. 7 & 9; [0045]-[0050], [0054]-[0055], [0061]-[0062], [0074]-[0076], [0083], [0085], [0091]-[0093], [0095]-[0096] & [0108]-[0118]: teaches using a count value to distinguish between walking and other states like resting body movement, the calculation unit calculates a step count based on the number of vibrations, determines whether to output a step count for a walking sate or a resting body movement count by comparing a Y-axis PIM value (analogous to amplitude) against a walking threshold value (Th), establishing using a count value and a threshold to identify a walking state).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Matsumoto’s measurement device and step counting logic with Taniguchi’s use of zero-crossing counts (ZC) and teachings of classifying walking sub-states (i.e., such as slow walking) using vibration intensity (amplitude) thresholds, and Unuma’s amplitude boundaries (technical methodology) to ensure that a walking state is determined when the frequency/count of events is below a certain “piece count threshold” (e.g., such as a threshold for running/walking frequency), verifying that an acceleration amplitude is less than a reference value (i.e., threshold for running/walking), motivating experimentation and optimization to accurately distinguish slow/normal walking from fast running and/or erroneous noise. A POSITA would find it obvious that a walking state can be determined by an amplitude being below a second lower threshold, as a direct extension of the logic in Matsumoto and documented in Unuma and Taniguchi. Therefore, by combining prior art elements according to known methods, would yield predictable results (KSR).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Chen et al. (US2021/0042121A1) discloses a method and apparatus for counting foot step based on stride frequency and device. Hashimoto (US2021/0404842A1) discloses a method, program and measuring device for number of steps. Asada et al. (US2011/0004440A1) discloses a pedometer where a user’s steps are counted based on a waveform form an acceleration sensor. Lee (KR101522466B1) discloses an apparatus and method for detecting the pedestrian foot zero velocity, detecting deceleration state of a pedestrian foot for improving a position tracking performance. Taniguchi (JP4877909B2) discloses a motion state discriminator capable of discrimination a motion state by using a vibration sensor, based on the magnitude of a change in acceleration.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL See MPEP § 706.07(a). 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.
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/HUGO NAVARRO/Examiner, Art Unit 2858 02/25/2026
/EMAN A ALKAFAWI/Supervisory Patent Examiner, Art Unit 2858 3/3/2026