DETAILED ACTION
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 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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application aft final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/25/2026 has been entered.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 2, 4, 5, 7, 8, 10, 11, 13 – 16, and 18 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Barker et al. (Publication: US 2015/0149104 A1) in view of Tsusaka et al. (Publication: US 2010/0256812 A1), Rigiroli et al. (Patent: US 10535174 B1)
Regarding claim 1, see rejection on claim 13.
Regarding claim 2, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1.
Baker discloses the accelerometers each reference gravitational force ([0119] - Referring again to FIG. 9, the zero crossings of the acceleration are shown with circles. At each of these points in the motion, the accelerometer measures the direction of gravity. It is at these points that the zero crossing error correction algorithm is implemented.).
Regarding claim 3, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1.
Baker discloses the magnetometers each reference magnetic north ([0126] - magnetometer measure the direction of magnetic north.).
Regarding claim 4, see claim 18.
Regarding claim 5, see claim 19.
Regarding claim 7, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1.
Baker does not however Tsusaka discloses wherein a position of each of the trackers is inferred using reverse forward kinematics (RFK) ([0227] - the target track generation unit 55, the positional error compensating unit 56, an approximation reverse kinematics calculation unit 57 and the forward kinematics calculation unit 58. The positional error compensating unit 56, the approximation reverse kinematics calculation unit 57 and the forward kinematics calculation unit 58 are allowed to form a position control system 59.
[0239] To the forward kinematics calculation unit 58 is inputted the joint angle vector q corresponding to the current value q of the joint angle measured by the encoder 44 of a joint axis of each of the joint portions and sent from the robot arm 5 through the input/output IF 24 so that the forward kinematics calculation unit 58 carries out geometrical calculations so as to convert the joint angle vector q of the robot arm 5 to the hand position and orientation vector r.).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker in view of Tsusaka, Rigiroli with wherein a position of each of the trackers is inferred using reverse forward kinematics (RFK) as taught by Tsusaka. The motivation for doing is so an area can be coirmed accurately as taught by Tsusaka.
Regarding claim 8, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1.
Baker discloses wherein hard limits based on the anatomical constraints are used to correct errors or drift in the signals from the microcontrollers ([0098] - FIG. 10 shows the mitigation of errors from the finite data rate and the DC offset. The error due to momentary saturation is also mitigated using this zero crossing error correction strategy. FIG. 6 shows that the error due to momentary sensor saturation persists for all times after the saturation occurs. In our three sensor motion tracking system however, the inaccuracies are corrected the next time the runner's arm goes through a point where the acceleration is zero, by employing our error correction technique.) .
Regarding claim 10, Baker discloses a method of providing body motion capture comprising (Fig. 12 – communication between the sensor nodes, MCU and external device. Abs, A system of sensors including 1) an accelerometer, 2) a magnetometer, and 3) a gyroscope, combined with a zero crossing error correction algorithm, as well as a method of using those sensors with the zero crossing error correction algorithm, for orientation motion tracking applications):
tracking orientation of five or more trackers to be placed on disparate points of a user's body, each of the trackers including an accelerometer, a gyroscope, and a microcontroller (Abs - A system of sensors including 1) an accelerometer, 2) a magnetometer, and 3) a gyroscope, combined with a zero crossing error correction algorithm, as well as a method of using those sensors with the zero crossing error correction algorithm, for orientation motion tracking applications. [0063], Fig. 14 - a full body biomechanical suit showing the locations of sensor nodes and a central Microcontroller module.);
generating signals from each of the microcontrollers outputting a signal defining its tracker orientation based on a sensor fusion of outputs from its accelerometer, and gyroscope (Fig. 11, [0099] The sensor node for our motion tracking system requires three sensors: an accelerometer, a magnetometer and a gyroscope. Each of these sensors measures and outputs data at a fixed data rate. The data from each sensor is read using a central Microcontroller Unit (MCU). The simplest architecture for the sensor node is that which only contains the three sensors and the associated discrete components needed for most commercially available MEMS sensors. In a complete system, however, in addition to the MCU, we would use suitable data storage (e.g. flash memory), and data transmission devices such as RF transmitter etc.
[0105] - performing the orientation analysis and zero crossing error correction algorithm.);
receiving the signals from the microcontrollers and consolidating the signals into a singular tracker orientation signal ([0113] – sensor nodes consolidate into the MCU to the external device.
[0099] - Between the sensor nodes (the three sensor combination of Accelerometer, Gyroscope and Magnetometer) and the MCU module which contains all other devices to make a complete motion tracking system.
[0105] - performing the orientation analysis and zero crossing error correction algorithm.); and
receiving the tracker orientation signal at a computing device and the tracker orientation signal using anatomical constraints to create a digital representation of the user's body movement ([0140] - send out data from the MCU to an external device and perform the orientation analysis outlined above in Background, and the zero crossing error correction scheme . [0070] - Graphical Representation: An image displayed on a screen or other display mechanism which shows the movement of the subject.).
Baker does not however Tsusaka discloses interpolate the tracker orientation ([0231] By using the polynomial interpolation, the target track generation unit 55 interpolates the tracks between the respective points, the force and the suction force so that the hand position and orientation target vector r.sub.d, the force vector f.sub.d and the suction force p.sub.d are generated.) .
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker with interpolate the tracker orientation as taught by Tsusaka. The motivation for doing is so an area can be coirmed accurately as taught by Tsusaka.
Baker in view of Tsusaka do not however Rigiroli discloses
determines anatomical constrains track anatomical constraints including known body mechanics and limits of body movement to create a digital representation (column 1 lines 54, column 10 lines 54 to 60 - the machine learning process can iteratively analyze and process motion capture data in order to determine constraints defining the range of motion for a joint that is more closely mapped to the observed limits of movements of human joints and limbs, update the character model for a user display).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker in view of Tsusaka with determines anatomical constrains track anatomical constraints including known body mechanics and limits of body movement to create a digital representation as taught by Rigiroli. The motivation for doing is so the animations can be more realistic as taught by Tsusaka.
Regarding claim 11, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 10.
Baker discloses performing a calibration sequence prior to the generating operation ([0126] – calibration step is performed. [0135] - The key to this innovative calibration method is that the true orientation of {right arrow over (B)}.sub.geo is obtained from the gyroscope rotation information (step 3). This allows the component {right arrow over (B)}.sub.ferrous to be computed ({right arrow over (B)}.sub.ferrous={right arrow over (B)}.sub.total-{right arrow over (B)}.sub.geo) and subtracted from any future magnetic field measurements. )
Regarding claim 13, Baker discloses a kinematic chain motion capture system comprising (Fig. 12 – communication between the sensor nodes, MCU and external device. Abs, A system of sensors including 1) an accelerometer, 2) a magnetometer, and 3) a gyroscope, combined with a zero crossing error correction algorithm, as well as a method of using those sensors with the zero crossing error correction algorithm, for orientation motion tracking applications):
two or more trackers to be placed on disparate points of an object approximated by a kinematic chain, each of the trackers including (Abs - A system of sensors including 1) an accelerometer, 2) a magnetometer, and 3) a gyroscope, combined with a zero crossing error correction algorithm, as well as a method of using those sensors with the zero crossing error correction algorithm, for orientation motion tracking applications. [0063], Fig. 14 - a full body biomechanical suit showing the locations of sensor nodes and a central Microcontroller module.):
an accelerometer; a gyroscope (Abs - A system of sensors including 1) an accelerometer, 2) a magnetometer, and 3) a gyroscope, combined with a zero crossing error correction algorithm, as well as a method of using those sensors with the zero crossing error correction algorithm, for orientation motion tracking applications); and
a microcontroller, each of the microcontrollers outputting a signal defining its tracker orientation based on a sensor fusion of outputs from its accelerometer, and gyroscope (Fig. 11, [0099] The sensor node for our motion tracking system requires three sensors: an accelerometer, a magnetometer and a gyroscope. Each of these sensors measures and outputs data at a fixed data rate. The data from each sensor is read using a central Microcontroller Unit (MCU). The simplest architecture for the sensor node is that which only contains the three sensors and the associated discrete components needed for most commercially available MEMS sensors. In a complete system, however, in addition to the MCU, we would use suitable data storage (e.g. flash memory), and data transmission devices such as RF transmitter etc.
[0105] - performing the orientation analysis and zero crossing error correction algorithm.); and
a link to receive the signals from the microcontrollers and consolidate the signals into a singular tracker orientation signal (
[0113] – sensor nodes consolidate into the MCU to the external device.
[0099] - Between the sensor nodes (the three sensor combination of Accelerometer, Gyroscope and Magnetometer) and the MCU module which contains all other devices to make a complete motion tracking system.
[0105] - performing the orientation analysis and zero crossing error correction algorithm.) ; and
a computing device to receive the tracker orientation signal and the tracker orientation signal using anatomical constraints to create a digital representation of the object's movement ([0140] - send out data from the MCU to an external device and perform the orientation analysis outlined above in Background, and the zero crossing error correction scheme . [0070] - Graphical Representation: An image displayed on a screen or other display mechanism which shows the movement of the subject. ).
Baker does not however Tsusaka discloses interpolate the tracker orientation ([0231] By using the polynomial interpolation, the target track generation unit 55 interpolates the tracks between the respective points, the force and the suction force so that the hand position and orientation target vector r.sub.d, the force vector f.sub.d and the suction force p.sub.d are generated.) .
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker with interpolate the tracker orientation as taught by Tsusaka. The motivation for doing is so an area can be coirmed accurately as taught by Tsusaka.
Baker in view of Tsusaka do not however Rigiroli discloses
determines anatomical constrains track anatomical constraints including known body mechanics and limits of body movement to create a digital representation (column 1 lines 54, column 10 lines 54 to 60 - the machine learning process can iteratively analyze and process motion capture data in order to determine constraints defining the range of motion for a joint that is more closely mapped to the observed limits of movements of human joints and limbs, update the character model for a user display).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker in view of Tsusaka with determines anatomical constrains track anatomical constraints including known body mechanics and limits of body movement to create a digital representation as taught by Rigiroli. The motivation for doing is so the animations can be more realistic as taught by Tsusaka.
Regarding claim 14, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 13.
Baker discloses wherein the object is a human body holding an inanimate object ([0063] FIG. 14: Schematic of a full body biomechanical suit showing the locations of sensor nodes and a central Microcontroller module.).
Regarding claim 15, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 13.
Baker discloses wherein the object is a non-human body ([0079] Subject: An object, person, animal, or a point on the Earth, whose movement is intended to be measured with a sensor node.).
Regarding claim 16, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 13.
Baker discloses the accelerometers each to determine orientation about two axes for their respective trackers ([0021], FIG. 3 - two accelerometers labeled A1 and A2 are separated by a distance r. Each accelerometer measures linear accelerations (A.sub.x, A.sub.y, A.sub.z) relative to its local coordinate system. The angular acceleration about the z axis (out of the page) is now given by
.alpha. Z = 1 r ( A 2 x - A 1 x ) . ##EQU00002##
[0022] There are therefore three kinematical parameters of interest in determining the movements involved in the motion of a single biomechanical segment: [0023] 1) The orientation angles about the x, y, and z axes (i.e. roll, pitch and yaw denoted by .theta..sub.x, .theta..sub.y, .theta..sub.z);).
Regarding claim 18, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 13.
Baker discloses the gyroscopes each to selectively estimate orientation in place of the accelerometers ([0087] - We use the gyroscope to measure the rotational velocities of each segment and deduce the angular orientations through integration. Using the combination of accelerometer and magnetometer, we are then able to apply a simple algorithm to systematically correct for any error in the calculated orientations due to data rate and DC offset, as well as provide a means to accurately recover from sensor saturation.).
Regarding claim 19, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 13.
Baker discloses each accelerometer in each tracker to correct for gyroscope drift ([0087] - The key to this innovation is the ability to minimize orientation errors and provide recovery from sensor saturation by innovative use of data from all three sensors. We use the gyroscope to measure the rotational velocities of each segment and deduce the angular orientations through integration. Using the combination of accelerometer and magnetometer, we are then able to apply a simple algorithm to systematically correct for any error in the calculated orientations due to data rate and DC offset, as well as provide a means to accurately recover from sensor saturation. With these advantages, this three sensor motion tracking and error correction technique is more accurate and robust than competing technologies.).
Claims 9, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Barker et al. (Publication: US 2015/0149104 A1) in view of Tsusaka et al. (Publication: US 2010/0256812 A1), Rigiroli et al. (Patent: US 10535174 B1) and Olsson et al. (Publication: US 2019/0011592 A1)
Regarding claim 9, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1.
Baker in view of Tsusaka, Rigiroli do not, However Olsson discloses
wherein one of the trackers serves as a known position for inferring a position of each of the other trackers therefrom ([0108] Returning to FIG. 3B, in step 368, the location of the utility locator device (or other signal detection/tracking device) relative to the Earth's surface may be determined from positioning elements. For example, inertial navigation sensors, GPS or other global navigation systems receivers, or other position determination devices and methods (e.g., terrestrial navigation systems, etc.) may be used to determine the locator's (or other signal detection/tracking device, or mapping device) position in absolute coordinates, such as latitude longitude or other reference coordinates. In step 370, the location of the POI relative to the Earth's surface may be determined in absolute coordinates (e.g., latitude/longitude or other reference coordinates) by combining the relative position or distance data between the locator (or other signal detection/tracking device, or mapping device) with the absolute position data determined from the positioning element/elements (e.g., GPS or other satellite receiver, inertial sensor and initial reference, etc.). In step 372, the POI may be included in a map or map system as a data point or record, and may be associated with other data as described herein, either locally or in a remote database system.).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker in view of Tsusaka, Rigiroli with wherein one of the trackers serves as a known position for inferring a position of each of the other trackers therefrom as taught by Ollson. The motivation for doing so is to improve location accuracy as taught by Ollson.
Regarding claim 12, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1
Baker in view of Tsusaka, Rigiroli do not, However Olsson discloses
pulling absolute position data from one device; and referencing relative positions of each of the trackers against the pulled absolute position ([0108] Returning to FIG. 3B, in step 368, the location of the utility locator device (or other signal detection/tracking device) relative to the Earth's surface may be determined from positioning elements. For example, inertial navigation sensors, GPS or other global navigation systems receivers, or other position determination devices and methods (e.g., terrestrial navigation systems, etc.) may be used to determine the locator's (or other signal detection/tracking device, or mapping device) position in absolute coordinates, such as latitude longitude or other reference coordinates. In step 370, the location of the POI relative to the Earth's surface may be determined in absolute coordinates (e.g., latitude/longitude or other reference coordinates) by combining the relative position or distance data between the locator (or other signal detection/tracking device, or mapping device) with the absolute position data determined from the positioning element/elements (e.g., GPS or other satellite receiver, inertial sensor and initial reference, etc.). In step 372, the POI may be included in a map or map system as a data point or record, and may be associated with other data as described herein, either locally or in a remote database system.)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker in view of Tsusaka, Rigiroli with pulling absolute position data from one device; and referencing relative positions of each of the trackers against the pulled absolute position as taught by Ollson. The motivation for doing so is to improve location accuracy as taught by Ollson.
Claims 21, 22, 23 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Barker et al. (Publication: US 2015/0149104 A1) in view of Tsusaka et al. (Publication: US 2010/0256812 A1), Rigiroli et al. (Patent: US 10535174 B1), and Fleishman et al. (Publication: US 2016/0335790 A1).
Regarding claim 21, see rejection on claim 23.
Regarding claim 22, see rejection on claim 24.
Regarding claim 23, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1.
Baker in view of Tsusaka, Rigiroli do not however Fleishman discloses
wherein the anatomical constraints treat a portion of the user's body as a kinematic chain including a set of links and joints ([0036] Furthermore, kinematic model 100 includes three joints 101 (e.g., associated with anatomical joints of a finger), one end-effector 103 (e.g., associated with a tip of a finger), and three links 102 connecting the joints and the end-effector. However, kinematic model 100 may include any number of joints, links, and end-effectors combined in any suitable manner to represent an articulated body. Furthermore, in some examples, some of joints 101 may also be end-effectors.
[0072] Furthermore, in some examples, joints in a kinematic model may be required to obey restriction constraints. For example, finger abduction/adduction and flexion/extension angles may be restricted by physical limitations. Such restrictions may be provided via a feasibility set applied to a kinematic model parameter.).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker in view of Tsusaka, Rigiroli with wherein the anatomical constraints treat a portion of the user's body as a kinematic chain including a set of links and joints as taught by Fleishman. The motivation for doing is so to improve accuracy as taught by Fleishman.
Regarding claim 24, Baker in view of Tsusaka, Rigiroli disclose all the limitation of claim 1.
Baker in view of Tsusaka, Rigiroli do not however Fleishman discloses
wherein the anatomical constraints limit the degrees of freedom of a joint of the user's body ([0092] Returning to FIG. 3, as discussed, resultant kinematic model parameters for a kinematic model of a hand skeleton or similar articulated body may be generated or provided. For example, a kinematic model of a hand skeleton may include twenty-six degrees of freedom (e.g., six for the root node and four for each finger) as discussed with respect to FIG. 1B and elsewhere herein. Although discussed herein with respect to a hand skeleton, the techniques discussed herein may be applied to any articulated body such as a human body skeleton, an animal body skeleton, a machine, or any object having moving parts. Furthermore, a calibration module of system 300 (not shown) may (at runtime or the like) be provided to adjust the lengths of each bone (e.g., links) according to the proportions of a user's hand. Such a calibration may be performed using any suitable technique or techniques. In some examples, the techniques discussed herein may assume that such bone lengths are constant. Furthermore, kinematic constraints for plausible finger abduction/adduction and flexion/extension angles may be set according to any suitable technique or techniques.).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Baker in view of Tsusaka, Rigiroli with wherein the anatomical constraints limit the degrees of freedom of a joint of the user's body as taught by Fleishman. The motivation for doing is so to improve accuracy as taught by Fleishman.
Response to Arguments
Claim Rejection Under 35 U.S.C. 103
Applicant asserts “The Office cites the "zero crossing" of Baker at paragraph [0140] to anticipate the "anatomical constraints" of claim 1. See Non-Final Office Action at page 10. Baker defines the zero crossing as "points in time corresponding to ... non-accelerating states" when "the magnitude of the gravity subtracted accelerometer values are below a predefined threshold." See Baker at paragraph [0081]. This description of zero crossing discloses a sensor that is not accelerating, which does not appear related to the recited "anatomical constraints." Further, Baker does not disclose anatomical constraints "including known body mechanics and limits of body movement," as now recited by amended claims 1, 10, and 13. This is because the zero crossing of Baker does not disclose interpolating a tracker orientation signal using "known body mechanics and limits of body movement." Therefore, the cited portion of Baker does not teach "interpolate the tracker orientation signal using anatomical constraints including known body mechanics and limits of body movement," as required by claims 1, 10, and 13.”
The argument has been fully considered and is persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Rigiroli reference.
Regarding claims 1 – 9, 11, 12, and 14 – 22, the Applicant asserts that they are not obvious over based on their dependency from independent claims 1, 10, and 13 respectively. The examiner cannot concur with the Applicant respectfully from same reason noted in the examiner’s response to argument asserted from claims 1, 10, and 13 respectively.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ming Wu whose telephone number is (571)270-0724. The examiner can normally be reached on Monday - Friday: 9:30am - 6:00pm EST .
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/MING WU/
Primary Examiner, Art Unit 2618
Prosecution Insights