DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The applicant has amended the claims in an effort to overcome the previously held rejections. Claim 1 is amended to incorporate limitations of previous claims 2 and 3 (now cancelled). Claim 12 is amended to incorporate limitations of previous claims 13 and 14 (now cancelled). Claim 24 is added to provide a new independent claim which incorporates previous claim 1 with the limitations of previous claims 2 and 4 (now cancelled). Additional dependent claims were amended to address 35 USC 112(b) rejections and/or to further limit the claims. The amendments and arguments/remarks are addressed in the rejections and responses to arguments provided herein.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 5-12, and 15-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claims 1, 5-12, and 15-24; using the two part test for subject matter eligibility, independent claims 1, 12 and 24 are exemplary independent claims and are directed to a process (claims 1 and 24) and a machine (claim 12) (Step 1: Yes), and are directed to a judicial exception regarding an abstract idea (Step 2A, Prong 1: Yes). The abstract idea is bolded and italicized in the recreated claims below:
Claim 1:
A method for identifying a posture condition of a person comprising:
determining a set of two-dimensional and/or three-dimension body landmark positions based on a plurality of captured images
detecting a rotation of one or more body parts of the person around an upright center axis of the person based on the body landmark positions;
calculating an asymmetric score of the one or more body parts based on the rotation of the one or more body parts of the person, the asymmetric score relating to a level of the posture condition of the person; and
detecting an angle of a first line connecting a left side body part position and a right side body part position of a first body part of the person across a frontal plane from an image of the person against a reference line, wherein
the reference line comprises a second line connecting a left side body part position and a right side body part position of a second body part of the person across the frontal plane, and
the detection of the rotation of the one or more body parts of the person around the upright center axis of the person is based on the angle.
Claim 12:
An apparatus for identifying a posture condition of a person comprising, the apparatus comprising:
at least one processor; and
at least one memory including computer program code;
the at least one memory and the computer program code configured to, with at least one processor, cause the server at least to:
detect a rotation of one or more body parts of the person around an upright center axis of the person based on a set of two-dimensional and/or three-dimensional body landmark positions determined based on a plurality of captured images;
calculate an asymmetric score of the one or more body parts based on the rotation of the one or more body parts of the person, the asymmetric score relating to a level of the posture condition of the person; and
detect an angle of a first line connecting a left side body part position and a right side body part position of a first body part of the person across a frontal plane from an image of the person against a reference line, wherein
the reference line comprises a second line connecting a left side body part position and a right side body part position of a second body part of the person across the frontal plane, and
the detection of the rotation of the one or more body parts of the person around the upright center axis of the person is based on the angle.
Claim 24:
A method for identifying a posture condition of a person comprising:
determining a set of two-dimensional and/or three-dimension body landmark positions based on a plurality of captured images
detecting a rotation of one or more body parts of the person around an upright center axis of the person based on the body landmark positions;
calculating an asymmetric score of the one or more body parts based on the rotation of the one or more body parts of the person, the asymmetric score relating to a level of the posture condition of the person; and
detecting an angle of a first line connecting a left side body part position and a right side body part position of a first body part of the person across a frontal plane from an image of the person against a reference line, wherein
the reference line is a third line connecting another two body part positions of the person, and
the detection of the rotation of the one or more body parts of the person around the upright center axis of the person is based on the angle.
The independent claims encompass an abstract idea drawn to a mental process that can be performed in the human mind and/or by hand using a pen and paper. In this case, the steps identified in bold and italics above are drawn to mental processes. Here, the mental process equates to a user viewing a plurality of captured images (using their eyes and brain to view and analyze the images) and mentally analyzing, determining and calculating an asymmetric score of the one or more body parts (i.e. using their brain to determine if the body part in the images is asymmetric and how asymmetrical it is). In other words, the mental process includes observation, evaluation, judgement and opinion.
Further, the claims do not recite additional elements that integrate the judicial exception into a practical application (Step 2A, Prong 2: No). The claims fail to recite additional element or combination of additional element to apply, rely on, or use the judicial exception in a manner that imposed meaningful limitations on the judicial exception. In the instant claims, the identified additional elements are: the at least one processor and the at least one memory including computer program code of claims 12-23) do not integrate the judicial exception into a practical application as they amount to merely applying the judicial exception by including the instruction to implement on a computer, or merely using a computer as a tool to perform the abstract idea (i.e. implementing on an processor and memory with computer program are all recited at a high level of generality); and generally linking the use of the judicial exception to a particular technological environment or field of use (i.e. a processor and memory with computer program). Further, the additional elements, considered individually and as a whole, with the abstract idea does not result in an improvement in the functioning of a computer or improvement in technology or technological field (the specification is silent to any improvement to the functioning of the processor and/or memory including computer program code and does not provide an improvement in a technological field); does not apply the judicial exception to effect a particular treatment or prophylaxis (only calculates the asymmetric scores); does not implement the judicial exception in conjunction with a particular machine or manufacture which is integral to the claims (the processor and memory including computer program code are conventional and recited at a high level of generality); does not affect the transformation or reduction of a particular articles to a different state (wherein analyzing data is not transforming to a particular article or state); and does not apply the judicial exception in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (wherein the abstract idea detecting and calculating are merely implemented on a processor and memory including computer program code). Further, in arguendo, if one were to argue the plurality of captured images of claims 1, 12 and 24 were additional elements (which the examiner does not concede based on the current claim drafting); they would also not amount to significantly more than the abstract idea as capturing of the images for analyses, at least as broadly and as generically as claimed, amounts to mere data gathering which is identified as insignificant extra-solution activity (see MPEP 2106.05 (g)).
Finally, the claims do not include additional elements, when considered individually and as an ordered combination, that amount to significantly more than the judicial exception (Step 2B: No). The additional elements of: at least one processor; at least one memory including computer program code, and a server (claim 12); do not amount to or contribute to the inventive concept recited in the abstract idea. The additional elements, considered individually and as a whole, amount to merely implementing the abstract idea on a computer by reciting implementation by at least one processor, at least one memory including computer program code to be executed on the processor, are recited at a high level of generality and do not attempt to meaningfully limit the abstract idea. When considered as a whole, implementing the abstract idea on a general computer (processor and memory including computer program code to cause a processor), does not amount to more than the abstract idea as use of general CPUs is well known, conventional and pervasive through data analysis.
Accordingly, claims 1, 12 and 24 are rejected as non-statutory as being directed toa judicial exception (abstract idea – mental process) without significantly more.
Dependent claims 5-11 and 15-23 do not recite any further additional elements that implement the abstract idea into a practical application or amount to significantly more than the abstract idea. Claims 5-11 and 15-22 merely recite further steps and/or details of the abstract idea, wherein eligibility cannot be furnished by the unpatentable abstract idea itself [MPEP 2106.04, II, A, 2] (claims 2-11 and 13-22). Claim 23 recites the additional elements of: one or more image capturing apparatuses configured to capture one or more images of the person, wherein the one or more images comprises an image of the person across a frontal plane and/or an image across a sagittal plane of the person. However, the additional element of the one or more image capturing apparatus are conventional, well known and recited at a high level of generality to perform their intended function, wherein one or more image capturing apparatus configured to capture one or more images of the person are conventional, routine, well understood and utilized for its intended purpose of capturing/collecting data. The examiner notes that the limitations recited in claim 23 that the images comprise an image of the person across a frontal plane and/or an image across a sagittal plane of the person are mere intended use of a image capturing apparatus, and conventional generic image capturing apparatuses are capable of obtaining images in those planes.
Accordingly, claims 1, 5-12 and 15-24 are rejected under 35 USC 101 as non-statutory subject matter, directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 4-8, 10-12, 15-19 and 21-24 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Debaun et al (US 2024/0023809 A1).
Regarding claims 1, 4-8, 10-12, 15-19 and 21-23; Debaun discloses a method for identifying a posture condition of a person (paragraphs [0047] and [0059]; figure 1) comprising:
determining a set of two-dimensional and/or three-dimensional body landmark positions based on a plurality of captured images (identifies anatomical landmarks from image of body; paragraphs [0043]-[0072], specifically [0049]-[0050],[0053]-[0057] and [0063]; figures 1a-2);
detecting a rotation of one or more body parts of the person around an upright center axis of the person based on the set of body landmark positions (wherein the method models a 3D representation and demarcates lines and representations of the body and identifies ratios, angles, torsions, rotations and other differences between the lines and/or anatomical landmarks and further specifically discloses angles with respect to other joints/planes/axis and trunk rotation; paragraphs [0043]-[0072], specifically [0048]-[0049],[0053]-[0057] and [0063]; figures 1a-2); and
calculating an asymmetric score of the one or more body parts based on the rotation of the one or more body parts of the person, the asymmetric score relating to a level of the posture condition of the person (wherein quantifying the magnitude of asymmetry inherently means calculating a asymmetric score; paragraphs [0043]-[0072], specifically [0045], [0049]-[0050], [0054]-[0055]; figures 1a-2); and
detecting an angle of a first line (element 156) connecting a left side body part position and a right side body part position of a first body part of the person across a frontal plane from an image of the person against a reference line (element 152) (wherein DeBaun discloses identifies ratios, angles, torsions, rotations and differences between lines demarcated on the body, and both 156 and 152 are demarcates and thus discloses detecting the angle between them; paragraphs [0043]-[0072], specifically [0053]-[0054]; figures 1a-2, specifically 1B, and 1D), wherein
the reference line comprises a second line (element 152) connecting a left side body part position and a right side body part position of a second body part of the person across the frontal plane (paragraphs [0043]-[0072], specifically [0048], [0053]-[0054]; figures 1a-2, specifically 1B, and 1D), and
the detection of the rotation of the one or more body parts of the person around the upright center axis of the person is based on the angle (wherein the rotation of the body parts around the center as abnormal is based upon the determined angles; paragraphs [0043]-[0072], specifically [0053]-[0054]; figures 1a-2, specifically 1B, and 1D).
Further regarding claims 12, 15-19 and 21-23; Debaun discloses the method of identifying a posture condition of a person as described in claim 1, wherein the method is implemented on an apparatus for identifying a posture condition of a person (figure 2), the apparatus comprising: at least one processor (CPU element 204 and processors in cloud server element 208); at least one memory including a computer program code, the at least one memory and the computer program code configured to, with at least one processor, cause the server (element 208) at least to perform the method of claim 1 (wherein in order to execute the method on the CPU and servers would inherently require memory and a program; paragraphs [0043]-[0072], specifically [0065]-[0067]; figures 1a-2).
Further regarding claims 5 and 16; Debaun discloses detecting a first distance of a body part position from a nearest point along the upright center axis of the person; wherein the detection of the rotation of the one or more body parts of the person and/or the calculation of the asymmetric score of the one or more body parts of the person is based on the first distance (detects the shift of axial lines which is a distance from the midpoint which is used in calculations of rotations, angles, ratios and proportions fed into machine learning algorithm to determine posture and rotation; paragraphs [0043]-[0072], specifically [0051]-[0052]; figures 1a-2, specifically 1C).
Further regarding claims 6 and 17; Debaun discloses detecting a second distance of a body part position from one of (i) two body part positions of the person, (ii) a middle point between the two body part positions or (iii) a fourth line connecting the two body part positions, wherein the detection of the rotation of the one or more body parts of the person and/or the calculation of the asymmetric score of the one or more body parts of the person is based on the second distance (detects distances between middle points of body part lines 154, 156 and 152 to determine shift and rotation and determines asymmetry using detected values; paragraphs [0043]-[0072], specifically [0048], [0051]-[0056]; figures 1a-2, specifically 1b and 1c).
Further regarding claims 7-8 and 18-19; Debaun discloses detecting a plurality of body part positions of the person based on relative positions of a plurality of body parts in one or more images in which the person is detected, wherein each of plurality of body part positions corresponds to a body part of the person (paragraphs [0043]-[0072]; figures 1a-2).
Further regarding claims 8 and 19; Debaun discloses detecting the plurality of body part positions of the person comprises: estimating a body part position of the person based on one of the plurality of body part positions, wherein the plurality of body part positions of the person further comprises the estimated body part position (creates a 3D model and identifies anatomical landmarks to estimate body part positions in order to obtain measurements used for analysis; paragraphs [0043]-[0072], specifically [0046]-[0051]; figures 1a-2).
Further regarding claims 10 and 21; Debaun discloses the asymmetric score is one of a plurality of asymmetric scores relating to a plurality of body parts, the method further comprising: calculating the level of the posture condition of the person based on the plurality of asymmetric scores (wherein the measurements of angles, ratios, distances and curvatures are fed into a machine learning model to determine asymmetry and severity/magnitude of asymmetry; paragraphs [0043]-[0072], specifically [0049], [0056], and [0059]; figures 1a-2).
Further regarding claims 11 and 22; Debaun discloses comparing each of the plurality of asymmetric scores with other asymmetric scores of the plurality of asymmetric scores; identifying one or more asymmetric scores having a higher score among the plurality of asymmetric scores; and identifying a set of posture correction programs based on a result of the identification (wherein the asymmetry of the different identifies body parts from the measured angles, distances, rotations and ratios are fed into the machine learning model which considers the input asymmetries to identify specific posture issues and provides recommended treatment; paragraphs [0043]-[0072], specifically [0049], [0056], [0059]-[0060] and [0063]; figures 1A-2, specifically 1A).
Further regarding claim 23; Debaun further discloses one or more image capturing apparatuses (element 202) configured to capture one or more images of the person, wherein the one or more images comprises an image of the person across a frontal plane (figures 1b left side image, 1c) and/or an image of the person across a sagittal plane (figure 1b, right side image) (paragraphs [0043]-[0072]; figures 1a-2).
Regarding claim 24; Debaun discloses a method for identifying a posture condition of a person (paragraphs [0047] and [0059]; figure 1) comprising:
determining a set of two-dimensional and/or three-dimensional body landmark positions based on a plurality of captured images (identifies anatomical landmarks from image of body; paragraphs [0043]-[0072], specifically [0049]-[0050],[0053]-[0057] and [0063]; figures 1a-2);
detecting a rotation of one or more body parts of the person around an upright center axis of the person based on the set of body landmark positions (wherein the method models a 3D representation and demarcates lines and representations of the body and identifies ratios, angles, torsions, rotations and other differences between the lines and/or anatomical landmarks and further specifically discloses angles with respect to other joints/planes/axis and trunk rotation; paragraphs [0043]-[0072], specifically [0048]-[0049],[0053]-[0057] and [0063]; figures 1a-2); and
calculating an asymmetric score of the one or more body parts based on the rotation of the one or more body parts of the person, the asymmetric score relating to a level of the posture condition of the person (wherein quantifying the magnitude of asymmetry inherently means calculating a asymmetric score; paragraphs [0043]-[0072], specifically [0045], [0049]-[0050], [0054]-[0055]; figures 1a-2); and
detecting an angle of a first line (element 164) connecting a left side body part position and a right side body part position of a first body part (posterior portion of body slide) of the person across a frontal plane from an image of the person against a reference line (element 162) (wherein DeBaun discloses identifies ratios, angles, torsions, rotations and differences between lines demarcated on the body, and both 156 and 152 are demarcates and thus discloses detecting the angle between them; paragraphs [0043]-[0072], specifically [0053]-[0054]; figures 1a-2, specifically 1B, and 1D), wherein
the reference line is a third line (element 162) connecting another two body part positions of the person (wherein horizontal line 162 connects two body part position from the left mid sagittal line to the right mid sagittal line; paragraphs [0043]-[0072], specifically [0048], [0053]-[0054]; figures 1a-2, specifically 1B, and 1D), and
the detection of the rotation of the one or more body parts of the person around the upright center axis of the person is based on the angle (wherein the rotation of the body parts around the center as abnormal is based upon the determined angles; paragraphs [0043]-[0072], specifically [0053]-[0054]; figures 1a-2, specifically 1B, and 1D).
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 8 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Debaun as applied to claims 1 and 12 above, and further in view of Brokaw et al (US 9,974,478 B1).
Debaun is described in the rejection of claims 1 and 12 above; Debaun further discloses the use of an artificial neural network/machine learning device for analyzing the information to determine asymmetry. However, Debaun does not explicitly disclose receiving demographic data relating to the person; wherein the calculation of the asymmetric score is further based on the demographic data.
Brokaw teaches it is known in artificial neural networks/machine learning algorithms to utilize demographic information as an input into the machine learning algorithm in order to analyze complex data trends, interactions and update information in the machine learning algorithm (column 58, lines 11-41; figure 17).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to modify Debaun to further provide demographic information to the neural network/machine learning algorithm to calculate the asymmetrical score as taught by Brokaw in order to identify complex data trends, interactions and provide more accurate results in the machine learning algorithm.
Response to Arguments
The examiner notes that the amendments to claims 12-23 to remove the limitation server and replace it with apparatus were sufficient to overcome the previously held 35 USC 112(b) rejection of those claims.
Applicant's amendments and arguments/remarks filed 7/28/2026 have been fully considered but they are not persuasive to overcome the 35 USC 101 and 102 rejections.
Regarding the applicant’s arguments with regards to the 35 USC 101 rejection as non-statutory subject matter, the examiner finds the applicant’s arguments to be non-persuasive. The applicant argues that by detecting the rotation of the one or more body parts of the person around the upright center axis of the person based on the angle, that the claim provides a significant technical advantage in the field of image-based biomechanical posture analysis system. This argument is non-persuasive as the MPEP notes that “the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” (see MPEP 2106.04(d)(1) and 2106.05(a)). Here, the applicant argues that the abstract idea of the analysis and determining of the angle provides the improvement in technology, however the examiner contends that the improvement is not provided by or to the additional elements. Said another way, there is no improvement to the functioning of a computer processor or memory (claims 12 and 15-23); and further there is no improvement to an imaging system (which is not even positively recited in the claim, except in claim 23). Rather, the claimed improvement relates to the abstract idea itself, in identifying an angle for determining the asymmetric score, which is part of the abstract idea (mental process) and does not provide an improvement to the actual technology or computer which executes the technology. The court cases cited by the applicant do not match the fact pattern of the instant application as those resulted in the improvement to the functioning of a computer and/or to a specific technology; whereas the claimed improvement here is just to an “improvement” to the abstract idea of determining/diagnosing asymmetry itself. The specification and claims are devoid of how the abstract idea provides any improvement to the functioning of a computer or to the technology of image capturing apparatus, rather it simply utilizes the computer or image capturing apparatus as a means to execute the abstract idea without integrating into a practical application or amounting to significantly more than the abstract idea. Accordingly, the applicant’s arguments with regards to the 35 USC 101 rejection are found to be non-persuasive.
The examiner further finds the applicant’s arguments with regards to the 35 USC 102 and 103 rejections to be non-persuasive. Specifically, the applicant argues that Debaun does not disclose “detecting an angle of a first line connecting a left side body part position and a right side body part position of a first body part of the person across a frontal plane from an image of the person against a reference line, wherein the reference line comprises a second line connecting a left side body part position and a right side body part position of a second body part of the person across the frontal plane, and the detection of the rotation of the one or more body parts of the person around the upright center axis of the person is based on the angle.” The examiner finds this argument to be non-persuasive as rejected above. With regards to claim 1, the examiner notes that Debaun explicitly discloses, “In many embodiments, the 3D representation is analyzed by demarcating various lines or representations and identifying ratios, angles, torsions, rotations, or other differences between these lines.” (paragraph [0048]). Debaun also discloses determining demarcating lines on the body including those depicted in figures 1C and 1D which show different demarcated lines associated with landmarks on the body. As Debaun discloses using these lines and angles between them to determine rotation, the examiner contends that Debaun discloses the claimed subject matter as the “ratios, angles, torsions, rotations, or other differences between these lines” are used to determine asymmetry in the user. Further, regarding new claim 24, the examiner notes that line 164 meets the broadest reasonable interpretation (BRI) of the first line and horizontal line 162 meets the BRI of the reference line, at least as broadly as claimed. As such, the examiner disagrees with the applicant’s contention that the measurement of the angle between the lines representing the posterior portion of the body (element 164) and the middle of the body (horizontal line, element 162) does not meet the claim language.
Accordingly, the applicant’s amendments and arguments/remarks have been fully considered but are non-persuasive.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ADAM J EISEMAN whose telephone number is (571)270-3818. The examiner can normally be reached Monday - Friday (7:00 AM - 4:00 PM).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jacqueline Cheng can be reached at 571-272-5596. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ADAM J EISEMAN/ Primary Examiner, Art Unit 3791
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