DETAILED ACTION
This action is pursuant to claims filed on 12/26/2023. Claims 1-10 are pending. A first action on the merits of claims 1-10 is as follows.
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 .
Claim Objections
Claims 7 and 8 are objected to because of the following informalities:
In claim 7, line 9, “the objective variable” should read “an objective variable”, as there is no antecedent basis for this limitation
In claim 8, line 5, “spatial angular velocity” should read “the spatial angular velocity”
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “a data acquisition device” in claim 8.
Regarding “a data acquisition device” limitation in claim 8:
(A) “a data acquisition device” is a generic placeholder for “means for”.
(B) The functional language that modifies “a data acquisition device” is the steps of measuring spatial acceleration and spatial angular velocity, generates the sensor data based on the spatial acceleration and spatial angular velocity, and transmits the sensor data to the walking index calculation device.
(C) “a data acquisition device” is not modified by sufficient structure for performing the claimed functions, therefore 35 U.S.C. 112(f) is invoked.
The corresponding structure for “a data acquisition device” in claim 8 configured to “measure spatial acceleration and spatial angular velocity, generates the sensor data based on the spatial acceleration and spatial angular velocity, and transmits the sensor data to the walking index calculation device” will be interpreted as including an acceleration sensor and an angular velocity sensor, as described in paragraph [0022] of the instant specification ([0022]: “The data acquisition device 11 includes an acceleration sensor and an angular velocity sensor”).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-7 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 2, the claim recites the limitations “a walking waveform” in line 4 and “a walking waveform” in line 6. It is unclear if these recitations are meant to refer to each other, the walking waveform from claim 1, or a different walking waveform. If they are meant to refer to the walking waveform from claim 1, they need to refer back to it. If they are referring to a different walking waveform, they need to be distinguished from the walking waveform from claim 1. For purposes of examination, they are interpreted as referring to the walking waveform from claim 1. Claims 3-7 are also rejected due to their dependence from claim 2.
Regarding claim 3, the claim recites the limitation “a walking waveform” in lines 4-5. It is unclear if this is meant to refer to the walking waveform from claim 1, “a walking waveform” in claim 2, line 4, “a walking waveform” in claim 2, line 6, or a different walking waveform. If it is meant to refer to any of the walking waveforms from claims 1-2, it needs to refer back to it. If it is referring to a different walking waveform, it needs to be distinguished from all of the walking waveforms from claims 1-2. For purposes of examination, it is being interpreted as referring to the walking waveform from claim 1. Claims 5-6 are also rejected due to their dependence from claim 3.
Regarding claim 4, the claim recites the limitation “a walking waveform” in lines 4-5. It is unclear if this is meant to refer to the walking waveform from claim 1, “a walking waveform” in claim 2, line 4, “a walking waveform” in claim 2, line 6, or a different walking waveform. If it is meant to refer to any of the walking waveforms from claims 1-2, it needs to refer back to it. If it is referring to a different walking waveform, it needs to be distinguished from all of the walking waveforms from claims 1-2. For purposes of examination, it is being interpreted as referring to the walking waveform from claim 1.
Regarding claim 6, the claim recites the limitation “a walking parameter” in line 4. It is unclear if this is meant to refer to the walking parameter from claim 1, or a different walking parameter. If it is meant to refer to the walking parameter from claim 1, it needs to refer back to it. If it is referring to a different walking parameter, it needs to be distinguished from the walking parameter from claim 1. For purposes of examination, it is being interpreted as referring to the walking parameter from claim 1, or any other walking parameter.
Further regarding claim 6, the claim recites the limitation “a walking waveform” in lines 4-5. It is unclear if this is meant to refer to the walking waveform from claim 1, “a walking waveform” in claim 2, line 4, “a walking waveform” in claim 2, line 6, “a walking waveform” in claim 3, lines 4-5, or a different walking waveform. If it is meant to refer to any of the walking waveforms from claims 1-3, it needs to refer back to it. If it is referring to a different walking waveform, it needs to be distinguished from all of the walking waveforms from claims 1-3. For purposes of examination, it is being interpreted as referring to the walking waveform from claim 1.
Regarding claim 7, the claim recites the limitation “with content optimized for healthcare application” in lines 12-13. It is unclear what is meant by content optimized for healthcare application. The broad and indefinite scope of the limitation fails to inform a person of ordinary skill in the art with reasonable certainty of the metes and bounds of the claimed invention, therefore the claim is rendered indefinite. For purposes of examination, any content that can be considered content optimized for healthcare application will teach on this limitation.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Greene (US 20130060512) in further view of Huang (US 20180279915).
Regarding independent claim 1, Greene teaches a walking index calculation device (Abstract: “Methods, systems, and apparatus for deriving a relationship between minimum ground clearance (MGC) and inertial sensor data”) comprising:
a memory storing instructions ([0054]: “The operations described above may be implemented in executable software as a set of logic instructions stored in a machine- or computer-readable medium of a memory such as random access memory (RAM), read only memory (ROM), programmable ROM (PROM), firmware, flash memory, etc., in fixed-functionality hardware using circuit technology such as application specific integrated circuit (ASIC), complementary metal oxide semiconductor (CMOS) or transistor-transistor logic (TTL) technology, or any combination thereof. For example, computer program code to carry out operations may be written in any combination of one or more programming languages”), and
a processor connected to the memory ([0055]: “the processor 48 may include one or more processor cores 58 capable of running a falls assessment program, frailty assessment program, gait assessment program, or other software with instructions stored in the system memory 50”) and configured to execute the instructions to:
generate a walking waveform by using sensor data regarding motion of a foot ([0029]: “The walking trial in which the inertial sensor data are generated may be part of a gait analysis in which a person's motion is measured while the person is walking a distance (e.g. 15 m or 30 m) in a straight path”) acquired by a sensor installed in footwear worn by a user ([0009]: “The regression model may be generated based on sensor data from a particular person, and may further be generated based on sensor data from a particular body segment, such as a left shank or a left foot.”; [0035]: “each marker may be placed on the lateral aspect of the fifth metatarsal head of each foot, on the exterior of the individual's shoes”);
detect a timing at which a clearance of a toe is minimized from the walking waveform ([0028]: “MGC, also called minimum toe clearance (MTC), may be defined as the minimum distance between the foot and the ground during a swing-phase of a gait cycle. At that instant, the foot may be at or near its maximum velocity, the center of mass of the body is outside its base of support, and a small positional error could result in collision with the ground. Thus, low MGC may be a trip hazard and an indication of a risk of falling, such as in the elderly population. Because measuring MGC with an optical motion capture system may require expensive, specialized equipment and personnel, the MGC and MGC parameters, or their estimates, may instead be calculated from parameters measured by or derived from one or more inertial sensors mounted on a person's body, such as his or her feet or legs. The calculation may be based on a regression model that estimates the MGC as a function of the inertial sensor parameters.”; [0039]: “FIG. 3B shows events that may be identified and labeled from the inertial sensors' angular velocity data. For example, FIG. 3B shows that initial contact (i.e. toe-off) points during a walk may be identified as the points where angular velocity is the lowest, and mid-swing points may be identified as the points where angular velocity is the highest.”; Claim 6: “calculating the estimate of the minimum ground clearance parameter is based on a mean angular velocity at a mid-swing point”. Fig. 3B shows the step of determining the timing of the mid-swing point, which is the timing at which the minimum ground clearance is determined.);
calculate a minimum value of the clearance of the toe by using a walking parameter at the timing at which the clearance of the toe is minimized ([0005]: “One aspect of this invention relates to calculating a minimum ground clearance (MGC) of a person by using data acquired from inertial sensors mounted on the person”; [0028]: “MGC, also called minimum toe clearance (MTC)”; [0028]: “The calculation may be based on a regression model that estimates the MGC as a function of the inertial sensor parameters”; [0036]: “A relationship may be derived between data from the inertial sensors and data from the optical capture system so that subsequent measurements collected by the inertial sensors (e.g., angular velocity and acceleration data) may be used to estimate parameters (e.g., MGC) that would otherwise have required the optical motion capture system to measure”. The walking parameter is the inertial sensor parameters, such as angular velocity and acceleration data.);
determine a risk of falling of the user based on the minimum value of the toe clearance ([0028]: “The calculated MGC may be used as part of a falls risk assessment”).
However, Greene does not teach the step of displaying the determination result regarding the risk of falling of the user on a screen of a mobile terminal used by the user.
Huang discloses a wearable gait analysis system. Specifically, Huang teaches the step of displaying the determination result regarding the risk of falling of the user on a screen of a mobile terminal used by the user ([0037]: “the clinical parameter can be sent to an external device as a record of the condition of the subject. However, when the alert generator 47 is employed, the alert can be, for example, a tactile signal (e.g., vibration of the mobile device), an audio signal or a visual signal … the alert generator 47 can generate a visual signal or an audio signal”; [0048]: “The Wearable Gait Lab application 92 was implemented on a mobile computing device 90 (e.g., an Android smartphone) for the purposes of displaying and recording the sensor data from the left, right or both of the lower limbs by bridging the data to xPC host-target system through BLE 94”). Greene and Huang are analogous arts as they are both related to systems used to monitor a user’s walking.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the display from Huang into the device from Greene as it allows the device to show the user their risk of falling, which can keep them more alert and allow them to cause a change to ensure they do not fall if it is needed.
Regarding claim 8, the Greene/Huang combination teaches a walking index calculation system comprising: the walking index calculation device according to claim 1 (see the rejection of claim 1); and a data acquisition device that measures spatial acceleration and spatial angular velocity, generates the sensor data based on the spatial acceleration and spatial angular velocity, and transmits the sensor data to the walking index calculation device (Greene, [0033]: “The inertial sensor parameters, such as acceleration or angular velocity, may be collected from each axis of the inertial sensors”; [0056]: “the network controller 54 obtains angular velocity data 62 wirelessly (e.g., from a data aggregator over a Bluetooth connection), and provides the angular velocity data 62 to the processor 48 for further analysis. The illustrated processor 48 calculates MGC 64 and other parameters and may generate a falls risk assessment”).
Regarding independent claim 9, Greene teaches an estimation method executed by a computer (Abstract: “Methods, systems, and apparatus for deriving a relationship between minimum ground clearance (MGC) and inertial sensor data”), the method comprising:
generating a walking waveform by using sensor data regarding motion of a foot ([0029]: “The walking trial in which the inertial sensor data are generated may be part of a gait analysis in which a person's motion is measured while the person is walking a distance (e.g. 15 m or 30 m) in a straight path”) acquired by a sensor installed in footwear worn by a user ([0009]: “The regression model may be generated based on sensor data from a particular person, and may further be generated based on sensor data from a particular body segment, such as a left shank or a left foot.”; [0035]: “each marker may be placed on the lateral aspect of the fifth metatarsal head of each foot, on the exterior of the individual's shoes”);
detecting a timing at which a clearance of a toe is minimized from the walking waveform ([0028]: “MGC, also called minimum toe clearance (MTC), may be defined as the minimum distance between the foot and the ground during a swing-phase of a gait cycle. At that instant, the foot may be at or near its maximum velocity, the center of mass of the body is outside its base of support, and a small positional error could result in collision with the ground. Thus, low MGC may be a trip hazard and an indication of a risk of falling, such as in the elderly population. Because measuring MGC with an optical motion capture system may require expensive, specialized equipment and personnel, the MGC and MGC parameters, or their estimates, may instead be calculated from parameters measured by or derived from one or more inertial sensors mounted on a person's body, such as his or her feet or legs. The calculation may be based on a regression model that estimates the MGC as a function of the inertial sensor parameters.”; [0039]: “FIG. 3B shows events that may be identified and labeled from the inertial sensors' angular velocity data. For example, FIG. 3B shows that initial contact (i.e. toe-off) points during a walk may be identified as the points where angular velocity is the lowest, and mid-swing points may be identified as the points where angular velocity is the highest.”; Claim 6: “calculating the estimate of the minimum ground clearance parameter is based on a mean angular velocity at a mid-swing point”. Fig. 3B shows the step of determining the timing of the mid-swing point, which is the timing at which the minimum ground clearance is determined.);
calculating a minimum value of the clearance of the toe by using a walking parameter at the timing at which the clearance of the toe is minimized ([0005]: “One aspect of this invention relates to calculating a minimum ground clearance (MGC) of a person by using data acquired from inertial sensors mounted on the person”; [0028]: “MGC, also called minimum toe clearance (MTC)”; [0028]: “The calculation may be based on a regression model that estimates the MGC as a function of the inertial sensor parameters”; [0036]: “A relationship may be derived between data from the inertial sensors and data from the optical capture system so that subsequent measurements collected by the inertial sensors (e.g., angular velocity and acceleration data) may be used to estimate parameters (e.g., MGC) that would otherwise have required the optical motion capture system to measure”. The walking parameter is the inertial sensor parameters, such as angular velocity and acceleration data.);
determining a risk of falling of the user based on the minimum value of the toe clearance ([0028]: “The calculated MGC may be used as part of a falls risk assessment”).
However, Greene does not teach the step of displaying the determination result regarding the risk of falling of the user on a screen of a mobile terminal used by the user.
Huang teaches the step of displaying the determination result regarding the risk of falling of the user on a screen of a mobile terminal used by the user ([0037]: “the clinical parameter can be sent to an external device as a record of the condition of the subject. However, when the alert generator 47 is employed, the alert can be, for example, a tactile signal (e.g., vibration of the mobile device), an audio signal or a visual signal … the alert generator 47 can generate a visual signal or an audio signal”; [0048]: “The Wearable Gait Lab application 92 was implemented on a mobile computing device 90 (e.g., an Android smartphone) for the purposes of displaying and recording the sensor data from the left, right or both of the lower limbs by bridging the data to xPC host-target system through BLE 94”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the display from Huang into the method from Greene as it allows the method to show the user their risk of falling, which can keep them more alert and allow them to cause a change to ensure they do not fall if it is needed.
Regarding independent claim 10, Greene teaches a non-transitory program recording medium recorded with a program causing a computer to perform the following processes (Claim 11: “A non-transitory computer-readable medium, the computer-readable medium comprising one or more instructions that, when executed by one or more processors, cause the one or more processors to: calculate, with a regression model, an estimate of a minimum ground clearance parameter of a person associated with motion data, wherein an input to the regression model comprises the motion data, and wherein the motion data comprises data obtained by one or more inertial sensors mounted on the person's body.”):
generating a walking waveform by using sensor data regarding motion of a foot ([0029]: “The walking trial in which the inertial sensor data are generated may be part of a gait analysis in which a person's motion is measured while the person is walking a distance (e.g. 15 m or 30 m) in a straight path”) acquired by a sensor installed in footwear worn by a user ([0009]: “The regression model may be generated based on sensor data from a particular person, and may further be generated based on sensor data from a particular body segment, such as a left shank or a left foot.”; [0035]: “each marker may be placed on the lateral aspect of the fifth metatarsal head of each foot, on the exterior of the individual's shoes”);
detecting a timing at which a clearance of a toe is minimized from the walking waveform ([0028]: “MGC, also called minimum toe clearance (MTC), may be defined as the minimum distance between the foot and the ground during a swing-phase of a gait cycle. At that instant, the foot may be at or near its maximum velocity, the center of mass of the body is outside its base of support, and a small positional error could result in collision with the ground. Thus, low MGC may be a trip hazard and an indication of a risk of falling, such as in the elderly population. Because measuring MGC with an optical motion capture system may require expensive, specialized equipment and personnel, the MGC and MGC parameters, or their estimates, may instead be calculated from parameters measured by or derived from one or more inertial sensors mounted on a person's body, such as his or her feet or legs. The calculation may be based on a regression model that estimates the MGC as a function of the inertial sensor parameters.”; [0039]: “FIG. 3B shows events that may be identified and labeled from the inertial sensors' angular velocity data. For example, FIG. 3B shows that initial contact (i.e. toe-off) points during a walk may be identified as the points where angular velocity is the lowest, and mid-swing points may be identified as the points where angular velocity is the highest.”; Claim 6: “calculating the estimate of the minimum ground clearance parameter is based on a mean angular velocity at a mid-swing point”. Fig. 3B shows the step of determining the timing of the mid-swing point, which is the timing at which the minimum ground clearance is determined.);
calculating a minimum value of the clearance of the toe by using a walking parameter at the timing at which the clearance of the toe is minimized ([0005]: “One aspect of this invention relates to calculating a minimum ground clearance (MGC) of a person by using data acquired from inertial sensors mounted on the person”; [0028]: “MGC, also called minimum toe clearance (MTC)”; [0028]: “The calculation may be based on a regression model that estimates the MGC as a function of the inertial sensor parameters”; [0036]: “A relationship may be derived between data from the inertial sensors and data from the optical capture system so that subsequent measurements collected by the inertial sensors (e.g., angular velocity and acceleration data) may be used to estimate parameters (e.g., MGC) that would otherwise have required the optical motion capture system to measure”. The walking parameter is the inertial sensor parameters, such as angular velocity and acceleration data.);
determining a risk of falling of the user based on the minimum value of the toe clearance ([0028]: “The calculated MGC may be used as part of a falls risk assessment”).
However, Greene does not teach the step of displaying the determination result regarding the risk of falling of the user on a screen of a mobile terminal used by the user.
Huang teaches the step of displaying the determination result regarding the risk of falling of the user on a screen of a mobile terminal used by the user ([0037]: “the clinical parameter can be sent to an external device as a record of the condition of the subject. However, when the alert generator 47 is employed, the alert can be, for example, a tactile signal (e.g., vibration of the mobile device), an audio signal or a visual signal … the alert generator 47 can generate a visual signal or an audio signal”; [0048]: “The Wearable Gait Lab application 92 was implemented on a mobile computing device 90 (e.g., an Android smartphone) for the purposes of displaying and recording the sensor data from the left, right or both of the lower limbs by bridging the data to xPC host-target system through BLE 94”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the display from Huang into the device from Greene as it allows the device to show the user their risk of falling, which can keep them more alert and allow them to cause a change to ensure they do not fall if it is needed.
Claims 2-4 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over the Greene/Huang combination as applied to claim 1 above, and further in view of Yamamoto (JP 2020092955). Citations to JP 2020092955 will refer to the English Machine Translation that accompanies this Office Action.
Regarding claim 2, the Greene/Huang combination teaches the walking index calculation device according to claim 1.
However, the Greene/Huang combination does not teach wherein the processor is configured to execute the instructions to calculate the minimum value of the clearance of the toe by using a value of a height of the sensor detected from a walking waveform of a vertical trajectory and a value of a rotation angle in a sagittal plane detected from a walking waveform of the rotation angle in the sagittal plane at the timing at which the clearance of the toe is minimized.
Yamamoto teaches a device for measuring the walking parameters of a user. Specifically, Yamamoto teaches wherein the processor is configured to execute the instructions to calculate the minimum value of the clearance of the toe by using a value of a height of the sensor detected from a walking waveform of a vertical trajectory and a value of a rotation angle in a sagittal plane detected from a walking waveform of the rotation angle in the sagittal plane at the timing at which the clearance of the toe is minimized (Fig. 7; [0036]-[0038], b is the height of the sensor, the rotation angle is α, and the minimum value of the clearance of the toe is d.). Greene, Huang, and Yamamoto are analogous arts as they are all related to systems used to monitor a user’s walking.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the steps used to determine minimum value of the toe clearance from Yamamoto into the Greene/Huang combination as it is another known calculation method used to determine the minimum toe clearance, therefore it is a simple substitution of the method from Yamamoto into the Greene/Huang combination.
Regarding claim 3, the Greene/Huang/Yamamoto combination teaches the walking index calculation device according to claim 2, wherein the processor is configured to execute the instructions to detect a timing of a gentle peak appearing between 40 and 60% of a gait cycle starting from a start timing of a support end stage in a walking waveform of an advancing direction acceleration as the timing at which the clearance of the toe is minimized (Greene, [0039]: “FIG. 3B shows events that may be identified and labeled from the inertial sensors' angular velocity data. For example, FIG. 3B shows that initial contact (i.e. toe-off) points during a walk may be identified as the points where angular velocity is the lowest, and mid-swing points may be identified as the points where angular velocity is the highest.”; Claim 6: “calculating the estimate of the minimum ground clearance parameter is based on a mean angular velocity at a mid-swing point”. The MGC is calculated at the mid-swing point, which is located between 40% and 60% of the gait cycle, as shown in Fig. 3B).
Regarding claim 4, the Greene/Huang/Yamamoto combination teaches the walking index calculation device according to claim 2, wherein the processor is configured to execute the instructions to detect a timing of zero crossing appearing between 40 and 60% of a gait cycle starting from a start timing of a support end stage in a walking waveform of a vertical acceleration as the timing at which the clearance of the toe is minimized (Greene, [0039]: “FIG. 3B shows events that may be identified and labeled from the inertial sensors' angular velocity data. For example, FIG. 3B shows that initial contact (i.e. toe-off) points during a walk may be identified as the points where angular velocity is the lowest, and mid-swing points may be identified as the points where angular velocity is the highest.”; Claim 6: “calculating the estimate of the minimum ground clearance parameter is based on a mean angular velocity at a mid-swing point”. The MGC is calculated at the mid-swing point, which is located between 40% and 60% of the gait cycle, as shown in Fig. 3B).
Regarding claim 7, the Greene/Huang/Yamamoto combination teaches the walking index calculation device according to claim 2.
However, the Greene/Huang/Yamamoto combination does not teach wherein the processor is configured to execute the instructions to estimate the minimum value of the clearance of the toe by inputting the value of the height of the sensor and the value of the rotation angle in the sagittal plane at the timing at which the clearance of the toe is minimum into a machine learning model generated by machine learning with values of the vertical height and values of the rotation angle in the sagittal plane as explanatory variables and the minimum value of the toe clearance as the objective variable, and display the determination result of the fall risk of the user according to the estimated minimum value of the toe clearance on the screen of the mobile terminal used by the user with content optimized for healthcare application.
Huang teaches wherein the processor is configured to execute the instructions to estimate the minimum value of the clearance of the toe by inputting the value of the height of the sensor and the value of the rotation angle in the sagittal plane at the timing at which the clearance of the toe is minimum into a machine learning model generated by machine learning with values of the vertical height and values of the rotation angle in the sagittal plane as explanatory variables and the minimum value of the toe clearance as the objective variable ([0031]: “the statistical or machine learning-based classification applied by the classifier 46 can employ one or more pattern recognition classifiers, each of which utilize the extracted features or a subset of the extracted features to determine an appropriate clinical parameter”. The vertical height and the values of the rotation angle are the known values, therefore they are the explanatory variables in the machine learning model, and the minimum value of the toe clearance is what the model determines, therefore it is the objective variable.), and display the determination result of the fall risk of the user according to the estimated minimum value of the toe clearance on the screen of the mobile terminal used by the user with content optimized for healthcare application ([0049]: “The JavaFX program is a user interface 102 on a PC 100 for ease of display and analysis of the data collected from the Wearable Gait Lab system”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to use the machine learning from Huang in the Greene/Huang/Yamamoto combination as it allows for faster and easier processing of the data to determine the minimum toe clearance.
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over the Greene/Huang/Yamamoto combination as applied to claim 3 above, and further in view of Barth (EP 3257437) and Math is Fun (“Finding a Side in a Right Triangle”).
Regarding claim 5, the Greene/Huang/Yamamoto combination teaches the walking index calculation device according to claim 3.
However, the Greene/Huang/Yamamoto combination is silent on the calculation process.
Barth discloses a system for analyzing human gait. Specifically, Berth teaches wherein the processor is configured to execute the instructions to calculate a first value by using trigonometric functions to calculate a first value , calculate a second value by subtracting the first value from a height of the sensor at the timing at which the clearance of the toe is minimized, and add a value of a height of the sensor at a timing of sole strike and the second value to calculate the minimum value of the clearance of the toe ([0045]: “With the help of trigonometric functions and the angle at toe off event, the distance between sensor and toes can be estimated. The sensor-toe distance again can be subtracted or added from the sensor clearance dependent on the foot angle with the help of trigonometric functions to calculate the toe clearance”). Greene, Huang, Yamamoto, and Barth are analogous arts as they are all related to systems used to monitor a user’s walking.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the calculations from Barth into the Greene/Huang/Yamamoto combination as the combination is silent on the calculations used, and Barth discloses suitable calculations in an analogous device.
However, the Greene/Huang/Yamamoto/Barth combination is silent on what trigonometric functions are used.
Math is Fun discloses equations used to find the side in a right triangle. Specifically, Math is Fun teaches calculating the first value by multiplying a sine of the rotation angle in the sagittal plane by a position of the sensor in an advancing direction at the timing at which the clearance of the toe is minimized (Pages 1-4. The rotation angle is θ, the position of the sensor in the advancing direction is the hypotenuse, and the first value is the opposite side of the right triangle, therefore the equation to determine the first value is multiplying the sine of the rotation angle by the position of the sensor to determine the first value based on the equations used to find a side in a right angled triangle as disclosed in Math is Fun.). Barth and Math is Fun are analogous arts as they both use trigonometric equations to calculate parameters.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to use the equation from Math is Fun in the Greene/Huang/Yamamoto/Barth combination as the combination is silent on the specific equations used, and Math is Fun discloses the specific equations in an analogous art.
Regarding claim 6, the Greene/Huang/Yamamoto/Barth/Math is Fun combination teaches the walking index calculation device according to claim 5, wherein the processor is configured to execute the instructions to calculate the position of the sensor in the advancing direction by using a walking parameter at a timing of toe off detected from a walking waveform, and calculate the minimum value of the clearance of the toe by using the position of the sensor in the advancing direction (Barth, [0045]: “With the help of trigonometric functions and the angle at toe off event, the distance between sensor and toes can be estimated. The sensor-toe distance again can be subtracted or added from the sensor clearance dependent on the foot angle with the help of trigonometric functions to calculate the toe clearance”. The walking parameter used for calculating the position of the sensor is the angle at toe off event.).
Conclusion
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/E.K.M./Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791