DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/21/2026 is being considered by the examiner.
Response to Arguments / Amendments
The response, entered 09/11/2026, has been entered. Claim 11 is cancelled. Claims 1-10 and 12-21 are pending. The previous 101 rejection is withdrawn due to amendment. Applicant’s arguments regarding claims 1-10 and 12-21 have been fully considered but are moot due to a new grounds of rejection, necessitated by amendment.
Claim Rejections - 35 USC § 102
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 1-6, 8-10, 12, and 19-20 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Perlin et al. (US 20210081031 A1).Regarding claim 1:Perlin teaches an information processing device comprising:
a controller configured to acquire posture angles of multiple body parts across an entire body of a user ([0033], [0046]), the multiple body parts including a body part on which a sensor device is not worn ([0132], [0049]-[0051], [0037], [0102]), based on sensor data representing movement of a subset of the multiple body parts of the user and a trained model, wherein the sensor data is acquired from the sensor device worn on only the subset of the multiple body parts, the subset including a head of the user, and the trained model is configured to output the posture angles of the multiple body parts across the entire body of the user when input with the sensor data([0119]-[0133], [0036], [0040], [0048]-[0051], [0037], [0102]; it is noted that Perlin teaches multiple possibilities regarding the number and positioning of the sensors)
Regarding claim 2:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the controller is configured to acquire the sensor data from a sensor device worn on at least some body parts of the user([0034], [0101], [0127]-[0128], [0132], etc. The citations in the rejection of claim 1 also teach the instant claim limitation.)
Regarding claim 3:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles, the posture angles occurring when the user performs periodic exercise ([0118], [0102]. The examiner notes that “exercise” is broad.)
Regarding claim 4:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles when input with the sensor data (e.g., [0044]-[0045], [0061], [0119]-[0133]. The citations in the rejection of claim 1 also teach the instant claim limitation.)
Regarding claim 5:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles when input with the sensor data, the sensor data including sensor data representing movement of a head of the user and sensor data representing movement of either one of two ankles of the user (e.g., [0036], [0101]-[0104])
Regarding claim 6:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles when input with the sensor data, the sensor data including sensor data representing movement of a head of the user and sensor data representing movement of either one of two feet of the user ([0033]-[0036], [0101]-[0104])
Regarding claim 8:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles when input with the sensor data, the sensor data including sensor data representing movement of a head of the user and sensor data representing movement of either one of two forearms of the user([0036], [0015], [0044]. E.g., data of the gloves/hands is biomechanically sensor data representing movement of the forearm(s))
Regarding claim 9:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles when input with the sensor data, the sensor data including sensor data representing movement of a head of the user (e.g., the HMD; [0036]), sensor data representing movement of either one of two forearms of the user ([0036], [0015], [0044]. E.g., data of the gloves/hands is biomechanically sensor data representing movement of the forearm(s)), and sensor data representing movement of either one of two ankles of the user (e.g., [0036], [0101]-[0104])
Regarding claim 10:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles when input with the sensor data, the sensor data including sensor data representing movement of a head of the user (e.g., the HMD; [0036]), sensor data representing movement of either one of two forearms of the user ([0036], [0015], [0044]. E.g., data of the gloves/hands is biomechanically sensor data representing movement of the forearm(s)), and sensor data representing movement of either one of two feet of the user ([0033]-[0036], [0101]-[0104])
Regarding claim 12:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles, the posture angles being posture angles of the user while walking(e.g., [0102], [0118])
Regarding claim 19:Perlin teaches an information processing system comprising:
an information processing device configured to acquire posture angles of multiple body parts across an entire body of a user ([0033], [0046]), the multiple body parts including a body part on which a sensor device is not worn ([0132], [0049]-[0051], [0037], [0102]), based on sensor data representing movement of a subset of the multiple body parts of the user and a trained model, wherein the sensor data is acquired from the sensor device worn on only the subset of the multiple body parts, the subset including a head of the user, and the trained model is configured to output the posture angles of the multiple body parts across the entire body of the user when input with the sensor data([0119]-[0133], [0036], [0040], [0048]-[0051], [0037], [0102]; it is noted that Perlin teaches multiple possibilities regarding the number and positioning of the sensors)
Regarding claim 20:Perlin teaches an information processing method comprising:
acquiring posture angles of multiple body parts across an entire body of a user, the multiple body parts including a body part on which a sensor device is not worn, based on sensor data representing movement of a subset of the multiple body parts of the user and a trained model, wherein the sensor data is acquired from the sensor device worn on only the subset of the multiple body parts, the subset including a head of the user, and the trained model is configured to output the posture angles of the multiple body parts across the entire body of the user when input with the sensor data([0033], [0036]-[0037], [0040]-[0051], [0102], [0119]-[0133])
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 of this title, 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 7 is rejected under 35 U.S.C. 103 as being unpatentable over Perlin et al. (US 20210081031 A1) in view of Zheng et al. ("Training data selection and optimal sensor placement for deep-learning-based sparse inertial sensor human posture reconstruction").Regarding claim 7:Perlin teaches all the limitations of claim 1, as mentioned above.Perlin also teaches:
wherein the trained model is further configured to output the posture angles when input with the sensor data, the sensor data including sensor data representing movement of a head of the user (e.g., the HMD; [0033], [0036]-[0037], [0046])Perlin fails to teach
sensor data representing movement of either one of two thighs of the userZheng teaches:
sensor data representing movement of either one of two thighs of the user(e.g., last full paragraph of page 2; section 7.3)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use sensor data representing movement of either one of two thighs of the user, as taught by Zheng, to increase accuracy based on the type of movement being tracked. Additionally/alternatively, it would be obvious to incorporate the teachings of Zheng to yield increased accuracy as more sensors yields increased accuracy due to an increased number of sensor locations.
Claims 13-18 are rejected under 35 U.S.C. 103 as being unpatentable over Perlin et al. (US 20210081031 A1) in view of Jagannathanet al. (US 20220330854 A1, prior art of record).Regarding claim 13:Perlin teaches all the limitations of claim 12, as mentioned above.Perlin also teaches:
animated full-body avatars of walking users (e.g., [0098], [0118])Perlin fails to teach:
wherein the controller is further configured to generate a gait model representing a way in which the user walks based on the posture angles of the multiple body parts across an entire body of the user and data of a movement velocity of a waist of the userJagannathanet teaches:
wherein the controller is further configured to generate a gait model representing a way in which the user walks based on the posture angles of the multiple body parts across an entire body of the user and data of a movement velocity of a waist of the user([0038], [0040]-[0041], [0051]-[0052], [0070]-[0075], [0079], [0082], [0099], [0105])
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to generate a gate model, as taught by Jagannathanet, in the device of Perlin to allow for its use in medical diagnosis and evaluation (e.g., joint movements, stability, balance, etc.).
Regarding claim 14:Perlin and Jagannathanet teach all the limitations of claim 13, as mentioned above.As combined in the claim 13 rejection above, Perlin and Jagannathanet teach:
wherein the trained model is further configured to output the movement velocity of the waist of the user when input with the sensor data, and the controller is configured to acquire the estimated value of the movement velocity of the waist of the user based on the trained model(e.g., see citations in the rejections of claims 1 and 13 above)
Regarding claim 15:Perlin teaches all the limitations of claim 12, as mentioned above.Perlin fails to teach:
wherein the controller is further configured to evaluate a gait of the user based on the posture anglesJagannathanet teaches:
wherein the controller is further configured to evaluate a gait of the user based on the posture angles([0038], [0040]-[0041], [0051]-[0052], [0070]-[0075], [0079], [0082], [0099], [0105])
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to evaluate the gait of the user, as taught by Jagannathanet, in the device of Perlin to allow for its use in medical diagnosis and evaluation (e.g., joint movements, stability, balance, etc.).
Regarding claim 16:Perlin and Jagannathanet teach all the limitations of claim 13, as mentioned above.As combined in the claim 13 rejection above, Perlin and Jagannathanet teach:
an output unit, wherein the controller is further configured to cause the output unit to output data of the gait model
As cited in the rejections of claims 1 and 13 above, each of Perlin and Jagannathanet teach an output unit and Jagannathanet teaches the gait model. Also see Jagannathanet - abstract, [0088], [0095], [0105].
Regarding claim 17:Perlin and Jagannathanet teach all the limitations of claim 13, as mentioned above.As combined in the claim 13 rejection above, Perlin and Jagannathanet teach:
a communication unit, wherein the controller is further configured to transmit data of the gait model to an external device by using the communication unit
As cited in the rejections of claims 1 and 13 above, each of Perlin and Jagannathanet teach a communication unit for data transmission and Jagannathanet teaches the gait model. Also see Jagannathanet - [0049], [0088], [0091], [0105].
Regarding claim 18:Perlin and Jagannathanet teach all the limitations of claim 13, as mentioned above.As combined in the claim 13 rejection above, Perlin and Jagannathanet teach:
an electronic device comprising: an output unit configured to output data of the gait model generated by the information processing device according to claim 13 (see claim 13 rejection above)
As cited in the rejections of claims 1 and 13 above, each of Perlin and Jagannathanet teach an output unit and Jagannathanet teaches the gait model. Also see Jagannathanet - abstract, [0088], [0095], [0105].
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Perlin et al. (US 20210081031 A1).Regarding claim 21:Perlin teaches an information processing method comprising:
acquiring posture angles of multiple body parts across an entire body of a user, the multiple body parts including a body part on which a sensor device is not worn, based on sensor data representing movement of a subset of the multiple body parts of the user and a trained model, wherein the sensor data is acquired from the sensor device worn on only the subset of the multiple body parts, the subset including a head of the user, and the trained model is configured to output the posture angles of the multiple body parts across the entire body of the user when input with the sensor data([0033], [0036]-[0037], [0040]-[0051], [0102], [0119]-[0133])
The “non-transitory computer-readable recording medium having embodied thereon a program configured to cause a computer to execute” limitation is very strongly implied by Perlin to one of ordinary skill in the art. The examiner takes Official notice that it is well-known to use a non-transitory computer-readable recording medium having embodied thereon a program configured to cause a computer to execute method steps.
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 Herbert Keith Roberts whose telephone number is (571)270-0428. The examiner can normally be reached 10a - 6p MT.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter Macchiarolo can be reached at (571) 272-2375. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HERBERT K ROBERTS/Primary Examiner, Art Unit 2855
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