DETAILED ACTION
Applicant’s arguments, filed on 12/19/2025, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed on 12/19/2025, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1, 3-4, and 6-19 are the current claims hereby under examination.
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 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.
Claim 8 is 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 8, the claim recites the limitation “a spatial acceleration and a spatial angular velocity” in lines 4-5. It is unclear if this is meant to refer to the spatial acceleration data and spatial angular velocity from claim 1, or different spatial acceleration and different spatial angular velocity. If it is referring to the acceleration and velocity from claim 1, it needs to refer back to it. If it is referring to different acceleration and velocity, it needs to be distinguished from the acceleration and velocity from claim 1. For purposes of examination, it is being interpreted as referring to the spatial acceleration and spatial angular velocity from claim 1.
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, 3-4, 6, 8-14, and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Greene (US 20130060512) in further view of Barth (EP 3257437), Math is Fun (“Finding a Side in a Right Triangle”), and 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:
at least one 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
at least one processor connected to the at least one memory and configured to execute the instructions to ([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”):
receive, via wireless communication, sensor data regarding motion of a foot of a user measured by a sensor installed in footwear ([0032]: “inertial sensor data may be acquired using four wireless sensors”; [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”), the sensor including an acceleration sensor that measures three-dimensional spatial acceleration data and an angular velocity sensor that measures three- dimensional spatial angular velocity data ([0033]: “The inertial sensor parameters, such as acceleration or angular velocity, may be collected from each axis of the inertial sensors”; [0030]: “the sensor's gyroscope X-axis may be oriented to capture movement about a plane perpendicular to the long line of the shank, the sensor's gyroscope Y-axis may be oriented to capture movement in the person's anatomical sagittal plane, and the sensor's gyroscope Z-axis may be oriented to measure movement in the plane in which the long line of the shank lies”);
generate a walking waveform by using the sensor data regarding the motion of the foot of the user ([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”);
detect, as a detected timing, a first 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 at the detected timing ([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”).
However, Greene is silent on the calculation process.
Barth discloses a system for analyzing human gait. Specifically, Berth teaches calculating a first value by using trigonometric functions to calculate a first value, calculating a second value by subtracting the first value from a first height, of the sensor at the detected timing, obtained from a vertical trajectory of the foot represented by the walking waveform, and adding a second height, of the sensor at a second timing which is of a sole strike, to the second value ([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 and Barth 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 calculations from Barth into device from Greene as Greene is silent on the calculations used, and Barth discloses suitable calculations in an analogous device.
However, the Greene/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 a first value by multiplying a sine of a rotation angle in a sagittal plane of the foot at the detected timing by a position of the sensor in an advancing direction with respect to the toe (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/Barth combination as the combination is silent on the specific equations used, and Math is Fun discloses the specific equations in an analogous art.
The Greene/Barth/Math is Fun combination teaches determine a risk of falling of the user according to a decrease of the minimum value of the clearance of the toe (Greene, [0028]: “The calculated MGC may be used as part of a falls risk assessment”).
However, the Greene/Barth/Math is Fun combination does not teach the step of cause a mobile terminal used by the user to emit a notification sound in accordance with the timing at which the minimum value of the toe clearance is smaller than a threshold value for a fall risk.
Huang discloses a wearable gait analysis system. Specifically, Huang teaches the step of display a 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 sound notification from Huang into the device from the Greene/Barth/Math is Fun combination as it allows the device to alert the user when they are at risk of falling, which can keep them more alert and allow them to cause a change to ensure they do not fall.
Regarding claim 3, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation device according to claim 1, wherein the at least one processor is further configured to execute the instructions to: determine 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 of an advancing direction acceleration represented by the walking waveform as the detected 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/Barth/Math is Fun/Huang combination teaches the walking index calculation device according to claim 1, wherein the at least one processor is further 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 of a vertical acceleration represented by the walking waveform as the detected 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 6, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation device according to claim 1, wherein the at least one processor is further configured to execute the instructions to: calculate the position of the sensor in the advancing direction by using a walking parameter at a third timing of toe off detected from the 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.).
Regarding claim 8, the Greene/Barth/Math is Fun/Huang combination teaches a walking index calculation system comprising: the walking index calculation device according to claim 1 (see the above rejection of claim 1); and a data acquisition device that is disposed in the footwear worn by a user who is a measurement target of the walking waveform, measures a spatial acceleration and a spatial angular velocity according to walking of the user, generates the sensor data based on the measured spatial acceleration and spatial angular velocity, and transmits the generated 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 a walking index calculation method comprising for causing a computer to execute (Abstract: “Methods, systems, and apparatus for deriving a relationship between minimum ground clearance (MGC) and inertial sensor data”):
receiving, via wireless communication, sensor data regarding motion of a foot of a user measured by a sensor installed in footwear ([0032]: “inertial sensor data may be acquired using four wireless sensors”; [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”), the sensor including an acceleration sensor that measures three-dimensional spatial acceleration data and an angular velocity sensor that measures three-dimensional spatial angular velocity data ([0033]: “The inertial sensor parameters, such as acceleration or angular velocity, may be collected from each axis of the inertial sensors”; [0030]: “the sensor's gyroscope X-axis may be oriented to capture movement about a plane perpendicular to the long line of the shank, the sensor's gyroscope Y-axis may be oriented to capture movement in the person's anatomical sagittal plane, and the sensor's gyroscope Z-axis may be oriented to measure movement in the plane in which the long line of the shank lies”);
generating a walking waveform by using the sensor data regarding the motion of the foot of the user ([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”);
detecting, as a detected timing, 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 at the detected timing ([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”).
However, Greene is silent on the calculation process.
Barth discloses a system for analyzing human gait. Specifically, Berth teaches calculating a first value by using trigonometric functions to calculate a first value, calculating a second value by subtracting the first value from a first height, of the sensor at the detected timing, obtained from a vertical trajectory of the foot represented by the walking waveform, and adding a second height, of the sensor at a second timing which is of a sole strike, to the second value ([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 and Barth 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 calculations from Barth into method from Greene as Greene is silent on the calculations used, and Barth discloses suitable calculations in an analogous device.
However, the Greene/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 a first value by multiplying a sine of a rotation angle in a sagittal plane of the foot at the detected timing by a position of the sensor in an advancing direction with respect to the toe (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/Barth combination as the combination is silent on the specific equations used, and Math is Fun discloses the specific equations in an analogous art.
The Greene/Barth/Math is Fun combination teaches determine a risk of falling of the user according to a decrease of the minimum value of the clearance of the toe (Greene, [0028]: “The calculated MGC may be used as part of a falls risk assessment”).
However, the Greene/Barth/Math is Fun combination does not teach the step of cause a mobile terminal used by the user to emit a notification sound in accordance with the timing at which the minimum value of the toe clearance is smaller than a threshold value for a fall risk.
Huang discloses a wearable gait analysis system. Specifically, Huang teaches the step of display a 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 sound notification from Huang into the method from the Greene/Barth/Math is Fun combination as it allows the method to alert the user when they are at risk of falling, which can keep them more alert and allow them to cause a change to ensure they do not fall.
Regarding independent claim 10, Greene teaches a non-transitory, computer-readable program recording medium recording a program causing a computer to execute (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.”):
a process of receiving, via wireless communication, sensor data regarding motion of a foot of a user measured by a sensor installed in footwear ([0032]: “inertial sensor data may be acquired using four wireless sensors”; [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”), the sensor including an acceleration sensor that measures three-dimensional spatial acceleration data and an angular velocity sensor that measures three- dimensional spatial angular velocity data ([0033]: “The inertial sensor parameters, such as acceleration or angular velocity, may be collected from each axis of the inertial sensors”; [0030]: “the sensor's gyroscope X-axis may be oriented to capture movement about a plane perpendicular to the long line of the shank, the sensor's gyroscope Y-axis may be oriented to capture movement in the person's anatomical sagittal plane, and the sensor's gyroscope Z-axis may be oriented to measure movement in the plane in which the long line of the shank lies”);
a process of generating a walking waveform by using the sensor data regarding the motion of the foot of the user ([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”);
a process of detecting, as a detected timing, 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.);
a process of calculating a minimum value of the clearance of the toe at the detected timing ([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”).
However, Greene is silent on the calculation process.
Barth discloses a system for analyzing human gait. Specifically, Berth teaches calculating a first value by using trigonometric functions to calculate a first value, calculating a second value by subtracting the first value from a first height, of the sensor at the detected timing, obtained from a vertical trajectory of the foot represented by the walking waveform, and adding a second height, of the sensor at a second timing which is of a sole strike, to the second value ([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 and Barth 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 calculations from Barth into device from Greene as Greene is silent on the calculations used, and Barth discloses suitable calculations in an analogous device.
However, the Greene/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 a first value by multiplying a sine of a rotation angle in a sagittal plane of the foot at the detected timing by a position of the sensor in an advancing direction with respect to the toe (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/Barth combination as the combination is silent on the specific equations used, and Math is Fun discloses the specific equations in an analogous art.
The Greene/Barth/Math is Fun combination teaches determine a risk of falling of the user according to a decrease of the minimum value of the clearance of the toe (Greene, [0028]: “The calculated MGC may be used as part of a falls risk assessment”).
However, the Greene/Barth/Math is Fun combination does not teach the step of cause a mobile terminal used by the user to emit a notification sound in accordance with the timing at which the minimum value of the toe clearance is smaller than a threshold value for a fall risk.
Huang discloses a wearable gait analysis system. Specifically, Huang teaches the step of display a 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 sound notification from Huang into the device from the Greene/Barth/Math is Fun combination as it allows the device to alert the user when they are at risk of falling, which can keep them more alert and allow them to cause a change to ensure they do not fall.
Regarding claim 11, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation device according to claim 1, wherein the determination result is output for decision making by the user regarding a walking behavior associated with the risk of falling (Huang, [0042]: “FIG. 6 illustrates an example of a method 60 for preventing a slip, trip and fall (STF) event. The method 60 can be an extension of method 50, in some examples. At 62, a risk of a STF event can be determined based on the clinical parameter satisfying a STF condition. For example, the STF condition can be a threshold that can be established for the subject, for a group of subjects suffering from the same medical condition or for a population of subjects suffering from different medical conditions. At 64, an alert can be provided (e.g., by the wearable device 12 or by the mobile computing device 14) in response to determining the risk of the STF event. The alert can be a tactile signal, an audio signal or a visual signal”. The risk assessment can be used by a user for decision making, therefore the output teaches on this limitation.).
Regarding claim 12, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation method according to claim 9, wherein detecting a third timing, of a gentle peak appearing between 40 and 60% of a gait cycle starting from a start timing of a support end stage of an advancing direction acceleration represented by the walking waveform, as the detected 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 13, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation method according to claim 9, wherein detecting a third timing, of zero crossing appearing between 40 and 60% of a gait cycle starting from a start timing of a support end stage of a vertical acceleration represented by the walking waveform, as the detected 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 14, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation method according to claim 13, wherein calculating the position of the sensor in the advancing direction by using a walking parameter at a timing of toe off detected from the walking waveform; and calculating 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.).
Regarding claim 16, the Greene/Barth/Math is Fun/Huang combination teaches the non-transitory, computer-readable program recording medium according to claim 10, wherein the program is further configured to cause the computer to execute detecting a third timing, at which the clearance of the toe is minimized, and the third timing is detected as a gentle peak appearing between 40 and 60% of a gait cycle starting from a start timing of a support end stage of an advancing direction acceleration represented by the walking waveform, as the detected timing (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 17, the Greene/Barth/Math is Fun/Huang combination teaches the non-transitory, computer-readable program recording medium according to claim 10, wherein the program is further configured to cause the computer to execute detecting a third timing, at which the clearance of the toe is minimized, and the third timing is detected as a zero crossing appearing between 40 and 60% of a gait cycle starting from a start timing of a support end stage of a vertical acceleration represented by the walking waveform, as the detected timing (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 18, the Greene/Barth/Math is Fun/Huang combination teaches the non-transitory, computer-readable program recording medium according to claim 17, wherein the program is further configured to cause the computer to execute: calculating the position of the sensor in the advancing direction by using a walking parameter at a timing of toe off detected from the walking waveform; and calculating 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.).
Claims 7, 15, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over the Greene/Barth/Math is Fun/Huang combination as applied to claims 1, 9, and 10 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 7, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation device according to claim 1.
However, the Greene/Barth/Math is Fun/Huang combination does not teach wherein the at least one processor is further configured to execute the instructions to: verify the minimum value of the clearance of the toe.
Yamamoto teaches a method and system for measuring walking parameters of a user. Specifically, Yamamoto teaches wherein the at least one processor is further configured to execute the instructions to: verify the minimum value of the clearance of the toe ([0053]-[0054]: “In addition, in this embodiment, the vertical toe clearance is calculated using two distance sensors with the shortest measurement distances out of multiple, three or more, distance sensors arranged adjacent to each other, so that the clearance can be measured with higher accuracy.
When calculating the clearance, an accurate clearance can be corrected and calculated using a simple formula that uses the values measured by the two distance sensors and angle information that is known from the relative positions of the two distance sensors, so there is no increase in the processing burden on the control system.”). Greene, Barth, Huang, and Yamamoto are analogous arts as they are all related to devices that monitor the walking of a user.
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 step of verifying the value from Yamamoto into the Greene/Barth/Math is Fun/Huang combination as it ensures that the determined value is correct, which can be used to accurately inform the user of their walking patterns and allows for a more accurate determination of their fall risk.
The Greene/Barth/Math is Fun/Huang/Yamamoto combination teaches the step of output the determination result based on the minimum value of the clearance of the toe (Huang, [0042]: “FIG. 6 illustrates an example of a method 60 for preventing a slip, trip and fall (STF) event. The method 60 can be an extension of method 50, in some examples. At 62, a risk of a STF event can be determined based on the clinical parameter satisfying a STF condition. For example, the STF condition can be a threshold that can be established for the subject, for a group of subjects suffering from the same medical condition or for a population of subjects suffering from different medical conditions. At 64, an alert can be provided (e.g., by the wearable device 12 or by the mobile computing device 14) in response to determining the risk of the STF event. The alert can be a tactile signal, an audio signal or a visual signal”; Greene, [0028]: “The calculated MGC may be used as part of a falls risk assessment”).
Regarding claim 15, the Greene/Barth/Math is Fun/Huang combination teaches the walking index calculation method according to claim 9.
However, the Greene/Barth/Math is Fun/Huang combination does not teach wherein the at least one processor is further configured to execute the instructions to: verify the minimum value of the clearance of the toe.
Yamamoto teaches a method and system for measuring walking parameters of a user. Specifically, Yamamoto teaches wherein verifying the minimum value of the clearance of the toe ([0053]-[0054]: “In addition, in this embodiment, the vertical toe clearance is calculated using two distance sensors with the shortest measurement distances out of multiple, three or more, distance sensors arranged adjacent to each other, so that the clearance can be measured with higher accuracy.
When calculating the clearance, an accurate clearance can be corrected and calculated using a simple formula that uses the values measured by the two distance sensors and angle information that is known from the relative positions of the two distance sensors, so there is no increase in the processing burden on the control system.”). Greene, Barth, Huang, and Yamamoto are analogous arts as they are all related to devices that monitor the walking of a user.
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 step of verifying the value from Yamamoto into the Greene/Barth/Math is Fun/Huang combination as it ensures that the determined value is correct, which can be used to accurately inform the user of their walking patterns and allows for a more accurate determination of their fall risk.
The Greene/Barth/Math is Fun/Huang/Yamamoto combination teaches the step of outputting the determination result based on the minimum value of the clearance of the toe (Huang, [0042]: “FIG. 6 illustrates an example of a method 60 for preventing a slip, trip and fall (STF) event. The method 60 can be an extension of method 50, in some examples. At 62, a risk of a STF event can be determined based on the clinical parameter satisfying a STF condition. For example, the STF condition can be a threshold that can be established for the subject, for a group of subjects suffering from the same medical condition or for a population of subjects suffering from different medical conditions. At 64, an alert can be provided (e.g., by the wearable device 12 or by the mobile computing device 14) in response to determining the risk of the STF event. The alert can be a tactile signal, an audio signal or a visual signal”; Greene, [0028]: “The calculated MGC may be used as part of a falls risk assessment”).
Regarding claim 19, the Greene/Barth/Math is Fun/Huang combination teaches the non-transitory, computer-readable program recording medium according to claim 10.
However, the Greene/Barth/Math is Fun/Huang combination does not teach wherein the at least one processor is further configured to execute the instructions to: verify the minimum value of the clearance of the toe.
Yamamoto teaches a method and system for measuring walking parameters of a user. Specifically, Yamamoto teaches wherein the program is further configured to cause the computer to execute: verifying the minimum value of the clearance of the toe ([0053]-[0054]: “In addition, in this embodiment, the vertical toe clearance is calculated using two distance sensors with the shortest measurement distances out of multiple, three or more, distance sensors arranged adjacent to each other, so that the clearance can be measured with higher accuracy.
When calculating the clearance, an accurate clearance can be corrected and calculated using a simple formula that uses the values measured by the two distance sensors and angle information that is known from the relative positions of the two distance sensors, so there is no increase in the processing burden on the control system.”). Greene, Barth, Huang, and Yamamoto are analogous arts as they are all related to devices that monitor the walking of a user.
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 step of verifying the value from Yamamoto into the Greene/Barth/Math is Fun/Huang combination as it ensures that the determined value is correct, which can be used to accurately inform the user of their walking patterns and allows for a more accurate determination of their fall risk.
The Greene/Barth/Math is Fun/Huang/Yamamoto combination teaches the step of outputting the determination result based on the minimum value of the clearance of the toe (Huang, [0042]: “FIG. 6 illustrates an example of a method 60 for preventing a slip, trip and fall (STF) event. The method 60 can be an extension of method 50, in some examples. At 62, a risk of a STF event can be determined based on the clinical parameter satisfying a STF condition. For example, the STF condition can be a threshold that can be established for the subject, for a group of subjects suffering from the same medical condition or for a population of subjects suffering from different medical conditions. At 64, an alert can be provided (e.g., by the wearable device 12 or by the mobile computing device 14) in response to determining the risk of the STF event. The alert can be a tactile signal, an audio signal or a visual signal”; Greene, [0028]: “The calculated MGC may be used as part of a falls risk assessment”).
Response to Arguments
All of applicant’s argument regarding the rejections and objections previously set forth have been fully considered and are persuasive unless directly addressed subsequently.
Applicant has amended claims to overcome the 112(b) rejections, however the amendments have introduced new issues as raised in the 112(b) rejections above.
Applicant’s arguments with respect to the prior art rejections of claims 1-10 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
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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/E.K.M./Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791