DETAILED ACTION
In Applicant’s Response dated 12/18/2025, Applicant amended claims 1-5, 7-9, 11-15, 17-20, cancelled claims 6 and 10 and 16 and added claims 21-23; and argued against all rejections previously set forth in the Office action dated 9/25/2025.
Allowable Subject Matter
Claims 21 and 22 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
With regard to claim 21, the prior arts do not disclose the aspect of detecting that the one or more posture positions of the user deviates from the baseline posture reference includes detecting that the user maintains a first posture position of the one or more posture positions for a second predetermined period of time; and controlling the output of the posture position notification is in response to detecting that the user maintains the first posture position for the second predetermined period of
time.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 2, 5, 11, 12, 15, 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li, Pub. No.: CN 116453384 A, in view of Meng, Paten No.: CN114973423A1.
With regard to claim 1:
Li discloses a computer-implemented method comprising: detecting, by a device, a baseline posture reference for a user (the system determines a standard posture for the user, “obtaining the user standard sitting posture information collected by the identification module to establish the user standard sitting posture three-dimensional model, recording the user standard sitting posture three-dimensional model into the sitting posture identification database;”); receiving, by the device, posture position data for the user (the system collecting the current sitting posture information of the user: “collecting the current sitting posture information of the user, and determining the current sitting posture model according to the current sitting posture information, matching the current sitting posture model with the standard sitting posture three-dimensional model, and performing voice prompt when the deviation degree of the current sitting posture model and the standard sitting posture three-dimensional model reaches the deviation threshold value and the duration reaches the time threshold value.”), detecting, by the device, based at least in part on the posture position data, that one or more posture positions of the user deviates from the baseline posture reference for a first predetermined period of time (performing voice prompt when the deviation degree of the current sitting posture model and the standard sitting posture three-dimensional model reaches the deviation threshold value and the duration reaches the time threshold value: “obtaining the user standard sitting posture information collected by the identification module to establish a user standard sitting posture three-dimensional model, recording the user standard sitting posture three-dimensional model into a sitting posture identification database; collecting the current sitting posture information of the user, and determining the current sitting posture model according to the current sitting posture information, matching the current sitting posture with the standard sitting posture three-dimensional model, and performing voice prompt when the deviation degree of the current sitting posture model and the standard sitting posture three-dimensional model reaches the deviation threshold value and the duration reaches the time threshold value.”); and in response to the one or more posture positions of the user deviating from the baseline posture reference for the first predetermined period of time, controlling, by the device, output of a posture position notification to the user in response to the change in posture position (the system uses voice prompt to notify the user about the deviation: “obtaining the user standard sitting posture information collected by the identification module to establish a user standard sitting posture three-dimensional model, recording the user standard sitting posture three-dimensional model into a sitting posture identification database; collecting the current sitting posture information of the user, and determining the current sitting posture model according to the current sitting posture information, matching the current sitting posture with the standard sitting posture three-dimensional model, and performing voice prompt when the deviation degree of the current sitting posture model and the standard sitting posture three-dimensional model reaches the deviation threshold value and the duration reaches the time threshold value.”);.
Li does not disclose wherein the posture position data is detected by at least one imaging device.
However Meng discloses a method for posture position detection and user feedback (“The invention relates to the technical field of image processing, specifically relates to a warning method and system for sitting posture monitoring of children learning desk, the method comprises: obtaining the multi-frame front image and the corresponding posture image, and obtaining the standard posture image, obtaining abnormal posture image of posture change in the posture image, determining the abnormal region in the abnormal posture image and the human body part and the abnormal region corresponding to the standard region in the standard posture image, calculating the offset angle of the pixel point in the abnormal region, and obtaining the abnormal posture of the abnormal posture image, obtaining two adjacent frame abnormal regions with the same human body part, calculating the comprehensive similarity of the abnormal region corresponding to two adjacent frame abnormal posture images, accumulating the abnormal posture of the abnormal region according to the comprehensive similarity to obtain the final abnormal degree, determining abnormal sitting posture and warning according to the final abnormal degree, the method of the invention improves the accuracy of abnormal sitting posture monitoring.”), the method comprising: detecting, by a device, a baseline posture reference for a user (The system captures a standard posture image of the child: “Preferably, the step of obtaining the standard posture image of the front of the child comprises: storing all frame posture images of the child in a database; selecting a posture image of a child sitting posture end from all the frame posture images as the standard posture image by the user.”); capturing, by the device, posture position data for the user, wherein the posture position data is detected by at least one imaging device (the system captures real time images of the child: “S1. real-time obtaining the multi-frame front image and the corresponding child posture image, and obtaining the standard posture image of the child front, specifically, collecting the child to learn the multi-frame front image before the learning table, all the frame posture image of the child stored in the database, and then selecting one child sitting posture end of the posture image from all frame posture image as the standard posture image by the user terminal, because the child sitting posture is mainly abnormal, so the standard posture image of the embodiment and each frame of posture image collected only analyzing the learning table exposed part, wherein, considering the child good, and from the abnormal sitting time to the human body caused by the harm angle, We choose every 10 seconds to carry out a gesture image monitoring, that is, every 10 seconds is a period to detect, and each 10 seconds will collect 120 frame posture image, then 10 seconds is a period of all the gesture image is divided into several periods.”); detecting, by the device, a change in posture position relative to the baseline posture reference using the posture position data (the system determines the abnormal posture image of the child posture change: “S2, determining the abnormal posture image of the child posture change according to the grey difference value of the corresponding pixel point of each frame posture image and the standard posture image, obtaining the abnormal region and the human body part in the abnormal posture image, and obtaining the standard region corresponding to the abnormal region in the standard posture image. Specifically, as shown in FIG. 2, according to the grey difference of the corresponding pixel point of each frame of posture image and the standard posture image determining the abnormal posture image of the child posture change of the step: S21, obtaining the square value of the grey difference value of the corresponding pixel point in the standard gesture image and each frame gesture image; S22, calculating the sum value of the square value of the grey difference value of all corresponding pixel points in the standard posture image and the corresponding frame posture image and taking it as the difference value of the standard posture image and the posture image; S23, the difference value is greater than the preset difference threshold value of the gesture image as the abnormal gesture image.”) and controlling, by the device, output of a posture position notification to the user in response to the change in posture position (the system use voice notification to notify the child about his or her bad posture: “Specifically, the set similarity threshold value is a second similarity threshold value, and 0.2, the comprehensive similarity of two abnormal regions is greater than the preset similarity threshold value, indicating that the posture of the child is not large change, belonging to abnormal sitting posture, therefore, the posture abnormality degree of the two abnormal regions corresponding to accumulation, and warning by voice, when the comprehensive similarity of two abnormal regions is less than the preset similarity threshold value, indicating the large change of the posture of the child, here we believe that the children are in disorder, not belonging to abnormal sitting posture, it does not need to alarm.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Meng to Li so the user’s image is used to determine a user’s posture and whether it deviates from a baseline posture for easy comparison and for clear and accurate determination of the user’s posture.
With regard to claims 2 and 12:
Li and Meng disclose the computer-implemented method of claim 1, wherein the baseline posture reference includes reference image data of the user (Meng “Preferably, the step of obtaining the standard posture image of the front of the child comprises: storing all frame posture images of the child in a database; selecting a posture image of a child sitting posture end from all the frame posture images as the standard posture image by the user.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Meng to Li so the user’s image is used to determine a user’s posture and whether it deviates from a baseline posture for easy comparison and for clear and accurate determination of the user’s posture.
With regard to claims 5 and 15:
Li and Meng disclose the computer-implemented method of claim 1, wherein the baseline posture reference includes identification of at least one first point of the user, identification of at least one second point on the user and a distance from the at least one first point to the at least one second point (Meng “S3, calculating the offset angle and offset distance of each pixel point in the abnormal region according to the position of each pixel point in the abnormal region and the standard region. specifically, establishing the same coordinate system on the standard posture image and posture image, then according to the pixel point coordinate of the standard posture image and posture image, placing the standard posture image and posture image in the same coordinate system, obtaining the coordinate of each pixel point in the coordinate system of the corresponding posture image in the abnormal region, obtaining the coordinate of the coordinate system of each pixel point in the standard region on the corresponding standard posture image; calculating the offset distance of the corresponding pixel point in the abnormal area according to the coordinate of each two corresponding pixel points, namely representing the offset distance of the pixel point in the abnormal area relative to the corresponding pixel point in the standard area; calculating the offset angle of the corresponding pixel point in the abnormal region according to the ratio of the abscissa difference value and the ordinate difference value of each two corresponding pixel points, wherein the formula for calculating the offset distance of the corresponding pixel point in the abnormal region.
”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Meng to Li so a standard threshold for the deviation can be determined using the distance between points to help the user to accurately determine the posture issues of the user.
Claim 11 is rejected for the same reason as claim 1.
Claim 23 is rejected for the same reason as claim 1.
Claim(s) 3, 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li, in view of Meng, and further in view of Pendse, CN 116075767 A.
With regard to claims 3 and 13:
Li and Meng do not disclose the computer-implemented method of claim 1, wherein the baseline posture reference includes a position reference for at least one of a gaming headset and gaming controller.
However Pendse discloses the aspect wherein the baseline posture reference includes a position reference for at least one of a gaming (Generally, the application program engine 320 comprises providing and presenting the function of the artificial reality application program, the artificial reality application program such as telephone conference application program, game application program, navigation application program, education application program, training or simulation application program and so on. The application engine 320 may include, for example, one or more software packages for implementing the artificial reality application on the console 106, one or more software libraries, one or more hardware drivers, and/or one or more application program interfaces (Application Program Interface, API). The rendering engine 322 responds to the control of the application engine 320 to generate the 3 D artificial reality content for the application engine 340 of the HMD 112 to display to the user.) headset and gaming controller (Pendse: “the artificial reality application program during the operation, by tracking and calculating the reference frame (frame of reference) posture information (typically the observation view of the HMD 112), to construct the user 110 display of the artificial reality content 122. the artificial reality application program using HMD 112 as a reference frame and based on the current estimated posture of the HMD 112 determined by the current view angle, rendering three-dimensional (3D) artificial reality content, in some examples, the 3 D artificial reality content can be at least partially covered on the user 110 of the real world 3 D physical environment. during the process, the artificial reality application program using the received sensing data from the HMD 112 and/or controller 114 (e.g., mobile information and user command). and in some examples from any external sensor 90 (e.g., external camera) data, to collect the real world physical environment in the 3 D information, such as user 110 of motion and/or characteristic tracking information related to the user 110. the artificial reality application program based on the sensing data to determine the current posture of the reference system of the HMD 112, and according to the current gesture to render the artificial reality content 122.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Pendse to Li and Meng so the system can make sure that the user has the correct posture when playing video games such as virtual reality video games to prevent injury to the user.
Claims 4 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li, in view of Meng, in view of Lee, KR 20200034045 A.
With regard to claims 4 and 14:
Li and Meng do not disclose the computer-implemented method of claim 1, wherein detecting the baseline posture reference includes outputting an instruction for the user to stand and capturing image data of the user in a standing position.
However, Lee discloses the aspect wherein detecting the baseline posture reference includes outputting an instruction for the user to stand and capturing image data of the user in a standing position. (“3 and 7, in the sixth step (S6), the user is positioned in front of the screen 42 for taking a commemorative photograph, and poses particularly in a position where the blank area BA is formed. Since the user may not know where to be located when taking a commemorative photo, a message or the like instructing the user to stand in the blank area BA may be sent. As described above, when the user is located in the blank area BA, the blank area BA is made of only a simple color in a blank state without specific content, and thus the content of the screen is projected on the user's body as in the prior art. The problem that the appearance becomes unclear does not occur. For example, when the blank area BA is made of only white color, the user's body located in the blank area BA simply reflects the white color, and thus the screen to be displayed on the screen and the user's appearance as in the prior art. The contents are mixed together so that the user's appearance is not clear or not.
Referring to FIG. 3, in the seventh step (S7), photographing commemorating achievement achievement is performed. In general, screen golf is often played by acquaintances, so another party can capture the user who has achieved the achievement. Alternatively, if the user is playing screen golf by himself, he or she can take a picture of himself using a so-called selfie (self camera) method. In any case, if the blank area BA is formed and the user located there is photographed, a conventional problem does not occur and a picture in which the user's appearance is clearly obtained can be obtained. In the eighth step S8, the commemorative photographing ends and the achievement achievement screen is no longer displayed on the screen 42, and the subsequent play proceeds. For example, if users A and B are playing together and A makes a hole-in-one in his hitting sequence, after A's hole-in-one commemorative shooting is finished, it becomes B's hitting sequence, so the golf course so that B can hit the screen 42 A B ball, etc. is displayed. If the user who achieved the achievement in the third step S3 does not want to take a commemorative photograph, the fourth to seventh steps S4-S7 are omitted and the eighth step S8 proceeds immediately.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Lee to Li and Meng so the user is notified on how to take a base line posture image in order for the system to compare the posture images with the base line image wherein the baseline image represent the posture of the specific user with the correct posture.
Claims 7 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li, in view of Meng, in view of Hassager, US 20210099826 A1.
With regard to claims 7 and 17:
Li and Meng do not disclose the computer-implemented method of claim 1, wherein capturing posture position data for the user includes capturing image data of a reflection of the user for at least one of head position of the user, shoulder position of the user and hand position of the user.
However, Hassager discloses the aspect wherein capturing posture position data for the user includes capturing image data of a reflection of the user for at least one of head position of the user, shoulder position of the user and hand position of the user. (paragraph 79: “The HRTF customization module 380 receives feature data (e.g., one or more captured images of a user, one or more videos of the user, etc.). In one embodiment, the feature data is provided to the HRTF customization module 380 by a device separate from the audio system 300. In some embodiments, the audio system 300 is integrated into the same device that provides the feature data to the HRTF customization module 380. In one example, the feature data may include one or more captured images of the reflection of the user. The reflection of the user captured in the one or more images comprises the user's head and torso. In some embodiments, the HRTF customization module 380 may receive feature data that includes one or more measurements from a position sensor (e.g., the position sensor 190). The position sensor (e.g., an inertial measurement unit (IMU)) calculates the estimated position of a device that includes the position sensor. For instance, the position sensor integrated into a headset device may determine the head orientation of a user wearing the headset device. In some embodiments, the position sensor may be integrated on the same device that includes the audio system 300.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Hassager to Li and Meng so the system can use reflection image of the user to determine user posture in situations where direct image is unavailable.
Claims 8 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over LI, in view of Meng, and further in view of Hernicot, US 20230119594 A1
With regard to claims 8 and 18:
Li and Meng do not disclose the computer-implemented method of claim 1, wherein detecting a change in posture position relative to the baseline posture reference includes detecting at least one of forward shoulder lean, shoulder hunch and shoulder lean relative to the baseline position reference.
However Hernicot discloses the aspect wherein detecting a change in posture position relative to the baseline posture reference includes detecting at least one of forward shoulder lean, shoulder hunch and shoulder lean relative to the baseline position reference (paragraph 25: “Aspects of the invention can analyze a user's posture to determine if the posture is good or bad, and make recommendations for the user to improve their posture. Recommendations can be made in real-time, periodically, in summary format (e.g., daily or weekly report of posture performance over intervals), or the like. The system may determine that the user's posture is bad if they have asymmetry (e.g., crossed feet, leaning on elbow, shoulders forward), they are leaning forward (e.g., screen too far, feet too far back, desk too low, etc.), leaning backwards (e.g., feet forwards, shoulders supported), elbows are to the side (e.g., desk too high, mouse too far away), rounded shoulders (e.g., boxer chest, desk too low, keyboard forward, etc.), or the like. The system can analyze the user's posture via any suitable sensor suite that may comprise of images sensor(s) (e.g., webcam), pressure sensors (e.g., chair), inertial measurement unit (IMU) (e.g., on clothing, furniture, wearables, etc.), motion sensors, or other suitable sensor type and/or combination thereof. In some aspects, recommendations may include video-based feedback that shows an image of the user and posture, and an underlying reference images showing how the user should be sitting in order to have good posture. The user can adjust their posture in real-time until the user's image and the reference image are sufficiently aligned. In some cases, feedback can be given in the form of an avatar representation of the user's posture in comparison to a good posture reference. In some aspects, a good posture reference can be static or in some cases dynamic based on a history of previous measurements of the user (e.g., incremental improvement may be promoted, which may not be at an ideal position, for the sake of improving posture over time). Any suitable method of recommendation can be used as would be appreciated by one of ordinary skill in the art with the benefit of this disclosure. As noted above, the user's activity may affect the recommendation as different activities may warrant different postures or parameters of what constitutes “good” (e.g., healthy) posture. For instance, an example of a good dynamic posture is a posture that distributes weight over a variety of tissues (e.g., muscles, joints, bones, etc.) to minimize overloading in any of them over time.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Hernicot to Li and Meng so the system can accurately determine whether the user has bad posture based on user’s shoulder lean and shoulder hunch which are signs of bad shoulder posture.
Claims 9 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li, in view of Meng, and further in view of Kim, Pub. No.: 2023/0226431A1.
With regard to claims 9 and 19:
LI and Meng do not discloses wherein output of the posture notification includes controlling display of a message including a notice to correct user posture slowing game play of an electronic game; or restricting game play operation of the electronic game.
However Kim discloses the aspect wherein output of the posture notification includes controlling display of a message including a notice to correct user posture slowing game play of an electronic game; or restricting game play operation of the electronic game.. (paragraph 170: “Alternatively, the display apparatus 100 may output information about a part to be corrected in the posture of the user who follows the exercise motion. For example, as illustrated in FIG. 15, the display apparatus 100 may display a message 1520, such as ‘Please spread your arms more’, on the display or output the message 1520 through the speaker. However, the disclosure is not limited thereto.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Kim to Li and Meng so the user would be visually notified of the his or her posture issues and make adjustments quickly in order to improve his or her posture overtime.
Claim 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li, in view of Meng, and further in view of Fu, CN 116744043 A.
With regard to claims 20:
Li and Meng do not disclose the aspect wherein output of the posture notification includes controlling operation of an electronic game for at least one of slowing game play and restricting game play operation.
However Fu discloses the aspect wherein output of the notification includes controlling operation of an electronic game for at least one of slowing game play and restricting game play operation (“Specifically, if there is user information exceeding the pre-warning value, the alarm information is sent to the user, and the alarm information is used for indicating the user to postpone the use of the somatosensory game function. Specifically, if the pre-warning value heart rate is set to 100 times per minute, if the user heart rate is 125 times per minute at a certain time point, the television will display on the large screen that "the user heart rate has exceeded the upper limit, and the current heart rate is 125 times per minute, please slow down the motion rhythm or have a proper rest." At the same time, the television will broadcast the information by voice, so the user can see and hear the information, and the television is highly valued. if the user continues to play the game with high intensity, the heart rate continuously rises, the television displays the pre-warning information again and broadcasts the pre-warning information to the user through the voice to remind the user to properly slow down the rhythm or rest. If the user still does not listen to the advice, in order to avoid the harm to his body caused by excessive exercise, the television will be forced out of the exercise game.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Fu to Li and Meng so a user during gaming can be notified of his or her bad posture so he or she can correct it quickly which the notification is integrated in the game itself to provide a more effective notification.
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 DI XIAO whose telephone number is (571)270-1758. The examiner can normally be reached 9Am-5Pm est M-F.
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, Stephen Hong can be reached at (571) 272-4124. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DI XIAO/Primary Examiner, Art Unit 2178