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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/18/2024 was received and placed in the record on file. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claims 1-23; using the two part test for subject matter eligibility, independent claims 1 and 12 are exemplary independent claims and are directed to a process (claim 1) and a machine (claim 9) (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:
detecting a rotation of one or more body parts of the person around an upright center axis of the person; 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.
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; and
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.
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 of detecting a rotation of one or more body parts and calculating an asymmetric score of the one or more body parts, the asymmetric score relating to a level of the posture condition of the person are drawn to mental processes. Here, the mental process equates to a user viewing one or more body parts (using their eyes and brain to detect rotation) and mentally calculating an asymmetric score of the one or more body parts (i.e. using their brain to determine if they body part 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 (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 element, 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); 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).
Finally, the claims as a whole do not include additional elements that are sufficient to 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, and a server which are al 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 server), 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 and 12 are rejected as non-statutory as being directed toa judicial exception (abstract idea – mental process) without significantly more.
Dependent claims 2-11 and 13-23 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 as they merely recite further abstract idea steps to 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); or recite additional elements that are conventional, well known and recited at a high level of generality to perform their intended function (Claim 23 wherein the additional element of one or more image capturing apparatus configured to capture one or more images of the person which is conventional, routine, well understood and utilized for its intended purpose of capturing data).
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 12-23 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.
Claim 12 recites the limitation "the server" in line 6. There is insufficient antecedent basis for this limitation in the claim. Claims 13-23 are rejected as being dependent on claim 12 without correcting the issue of claim 12.
Claims 12-23 recite an apparatus, the apparatus comprising at least one processor and at least one memory including computer program code and that the processor and memory cause the server at least to. However, no server has been previously recited, so it is unclear if it is part of the apparatus, or if the claim should be a system and further recite a server in communication with the apparatus.
For the purpose of prosecution of the claims over prior art and promoting compact prosecution, the examiner will interpret claims 12-23 as if the claims recite a system that includes a server.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-8, 10-19 and 21-23 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Debaun et al (US 2024/0023809 A1).
Regarding claims 1-8, 10-19 and 21-23; Debaun discloses a method for identifying a posture condition of a person (paragraphs [0047] and [0059]; figure 1) comprising:
detecting a rotation of one or more body parts of the person around an upright center axis of the person (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 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).
Further regarding claims 12-23; Debaun further 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 2-4 and 13-15; Debaun discloses detecting an angle of a first line connecting two body part positions of the person from an image of the person against a reference line, wherein 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 (paragraphs [0043]-[0072], specifically [0053]-[0054]; figures 1a-2, specifically 1B, and 1D).
Further regarding claims 3 and 14; Debaun discloses the first line connects 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 and 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 (wherein first and second lines and planes are identified in the 3d model wherein the planes extends from the left side of the body to the right side of the body; paragraphs [0043]-[0072], specifically [0050]-[0054]; figures 1a-2, specifically 1B and 1D).
Further regarding claims 4 and 15; Debaun discloses the reference line is a third line connecting another two body part positions of the person (wherein reference line 162 is a line connecting the a left mid sagittal line with a right mid sagittal line; paragraphs [0043]-[0072], specifically [0050]-[0054]; figures 1a-2, specifically 1B and 1D).
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).
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 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, Debaune 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 Debaune 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 2026/0106025 A1 to Ostadabbas et al; discloses a computer vision based assessment of symmetry based on facial scan and created 3D models from images.
US 2021/0052199 A1 to Park et al; discloses a system for measuring body information, posture information and range of motion from a biomechanical model of a person created from a recorded image.
US 2018/0020954 A1 to Lillie et al; discloses a method and system for automated biomechanical analysis of bodily strength and flexibility.
US 2016/0310064 A1 to Cheng; discloses a posture advisory system.
US 2012/0000300 A1 to Sunagawa et al; discloses a body condition estimation and evaluation apparatus based on models of the body and analysis bilateral symmetry.
US 2014/0303522 A1 to Akimoto et al; discloses a scoliosis evaluation system and apparatus.
US 2022/0254018 A1 to Zhang; discloses a system for diagnosing and tracking spinal alignment of a person.
US 2011/0021914 A1 to Zheng et al; discloses a 3D ultrasound imaging system for assessing scoliosis.
US 2018/0116560 A1 to Quinn et al; discloses system for monitoring body parts of an individual.
US 2023/0119594 A1 to Hernicot et al; discloses a system for monitoring and recommending a posture to a user.
US 2021/0233643 A1 to Paravastu et al; discloses a system for determining a condition of subject using image analysis and deep neural network learning.
US 2015/0320343 A1 to Utsunomiya et al; disclose a motion information processing apparatus which models the body and identifies conditions.
US 2022/0004744 A1 to Xiang et al; discloses a human posture detection system.
US 2018/0153445 A1 to Noda et al; discloses a measurement system for monitoring posture from image data.
US 2021/0232810 A1 to Parsa et al; discloses an automated system for biomechanical postural assessment.
US 12,318,663 to Jalali et al; discloses a system for automated diagnosis of musculoskeletal and neurological disorders.
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).
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/ADAM J EISEMAN/ Primary Examiner, Art Unit 3791
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