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 .
Specification
The abstract of the disclosure is objected to because
The first sentence includes implied language “The present disclosure provides.”
A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
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 1 – 20 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 1 (line 5 – 6), Claim 6 (line 3), Claim 9 (line 4), and Claim 10 (line 2) each recite the term “executes the set of instructions”. It is unclear if this is intended to be the same or different than the previously-recited “at least one instruction set”. For the purposes of examination, the term “executes the set of instructions” is deemed to claim “executes a set of instructions of the at least one instruction set”. Claims 2 – 10 are similarly rejected due to their dependence on Claim 1.
Claim 1 (line 15), Claim 2 (line 1 – 2), Claim 4 (lines 1 – 2), Claim 6 (line 2 and line 6), Claim 10 (line 4), Claim 11 (line 10), Claim 12 (line 1), Claim 14 (line 1), Claim 16 (line 1 – 2 and 5), and Claim 20 (line 3) each recite the term “each posture signal”. It is unclear if this each posture signal is intended to be the same or different than the previously-recite each posture signal of the at least one posture signal. For the purposes of examination, the term “each posture signal” is deemed to claim “the each posture signal of the at least one posture signal”. Claims 2 – 10 are similarly rejected due to their dependence on Claim 1.
Claim 5 (line 1 - 3) and Claim 15 (lines 1 – 3) each recite the term “the three-dimensional posture data includes angle data and angular velocity data on the X-axis, the Y-axis, and the Z-axis”. As previously-recited, it appears that the “three-dimensional posture data” is of a corresponded measurement position in an original coordinate system. However, as also previously-recited, the X-axis, Y-axis, and Z-axis are part of the target coordinate system. As a result, it is unclear if this is intended to be newly-named x-, y-, and z-axes to be attributed to the original coordinate system, or if this is referring to posture data once it has been converted to the target coordinate system on that x-, y-, and z-axis. For the purposes of examination, the term “the three-dimensional posture data includes angle data and angular velocity data on the X-axis, the Y-axis, and the Z-axis” is deemed to claim “the three-dimensional posture data includes angle data and angular velocity data on the original coordinate system, on each an original X-axis, an original Y-axis, and an original Z-axis”.
Claim 6 (line 6 - 7) and 16 (line 5 - 6) each recite the term “convert each posture signal to the three-dimensional motion data in the target coordinate system”. There is insufficient antecedent basis for this limitation in the claim. There is no previously-recited three-dimensional motion data. For the purposes of examination, the term “convert each posture signal to the three-dimensional motion data” is deemed to claim “convert each posture signal to three-dimensional motion data in the target coordinate system”. Claims 7 – 9 and 17 – 19 are similarly rejected due to their dependence on Claims 6 and 16, respectively.
Claim 6 (line 7) and Claim 16 (line _) each recite the term “the conversion relationship”. It is unclear if this is intended to be the same or different than the previously-recited “pre-stored conversion relationship”. For the purposes of examination, the term “the conversion relationship” is deemed to claim “the pre-stored conversion relationship”.
Claim 10 (line 1) recites the term “The motion data calibration system according to claim” without an associated claim. As recited, it is unclear to which this claim is intended to be dependent. For the purposes of examination, the term “The motion data calibration system according to claim” is deemed to claim “The motion data calibration system according to claim 1” to align with the dependency of a similar claim 20 with claim 11.
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 - 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding Claim 1, the claim recites an apparatus, which is one of the statutory categories of invention (Step 1). The claim is then analyzed to determine whether it is directed to any judicial exception (Step 2A, Prong 1).
Regarding Claim 11, the claim recites "an act or step, or series of acts or steps" and is therefore a process, which is a statutory category of invention (Step 1). The claim is then analyzed to determine whether it is directed to any judicial exception (Step 2A, Prong 1).
Each of claims 1 – 20 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1 – 20 recites at least one step or instruction for observations, evaluations, judgments, and opinions, which are grouped as a mental process under the 2019 PEG. The claimed invention involves making observations, evaluations, judgments, and opinions, which are concepts performed in the human mind under the 2019 PEG.
Accordingly, each of Claims 1 – 20 recites an abstract idea.
Specifically, Claims 1 – 20 recite (underlined are observations, judgments, evaluations, or opinions, which are grouped as a mental process under the 2019 PEG) (additional elements bolded, see Step 2A, prong 2);
Claim 1
A motion data calibration system, comprising:
at least one storage medium storing at least one instruction set for calibrating motion data; and
at least one processor in communication with the at least one storage medium, wherein during operation, the at least one processor executes the set of instructions to:
obtain action data during a movement of a user, wherein the action data includes at least one posture signal corresponding to at least one measurement position on a body of the user, and each posture signal of the at least one posture signal includes three-dimensional posture data of a corresponded measurement position in an original coordinate system,
establish a target coordinate system, wherein the target coordinate system includes an X-axis, a Y-axis, and a Z-axis mutually perpendicular to each other, and
convert each posture signal to two-dimensional posture data in the target coordinate system.
Claim 11.
A method for calibrating motion data, comprising:
obtaining action data during a movement of a user, wherein the action data includes at least one posture signal corresponding to at least one measurement position on a body of the user, and each posture signal of the at least one posture signal includes three-dimensional posture data of a corresponded measurement position in an original coordinate system;
establishing a target coordinate system, wherein the target coordinate system includes an X-axis, a Y-axis, and a Z-axis mutually perpendicular to each other; and
converting each posture signal to two-dimensional posture data in the target coordinate system.
(observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG);
These underlined limitations describe a mathematical calculation and/or a mental process, as a skilled practitioner is capable of performing the recited limitations and making a mental assessment thereafter. Examiner notes that nothing from the claims suggests that the limitations cannot be practically performed by a human with the aid of a pen and paper, or by using a generic computer as a tool to perform mathematical calculations and/or mental process steps in real time. Examiner additionally notes that nothing from the claims suggests and undue level of complexity that the mathematical calculations and/or the mental process steps cannot be practically performed by a human with the aid of a pen and paper, or using a generic computer as a tool to perform mathematical calculations and/or mental process steps. For example, in Independent Claims 1 and 11, these limitations include:
Observation and judgment to establish a target coordinate system, wherein the target coordinate system includes an X-axis, a Y-axis, and a Z-axis mutually perpendicular to each other, and
Observation and judgment to convert each posture signal to two-dimensional posture data in the target coordinate system.
all of which are grouped as mental processes under the 2019 PEG.
Similarly, Dependent Claims 2 – 10, and 12 - 20 include the following abstract limitations, in addition the aforementioned limitations in Independent Claims 1 and 11 (underlined observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG):
obtain a pre-stored conversion relationship between the target coordinate system and the original coordinate system;
Observation and judgement of a pre-stored conversion relationship between the target coordinate system and the original coordinate system;
convert each posture signal to the three-dimensional motion data in the target coordinate system based on the conversion relationship
Observation and judgement of to convert each posture signal to the three-dimensional motion data in the target coordinate system based on the conversion relationship
convert the angular velocity data on the X-axis and the angular velocity data on the Y-axis to vertical angular velocity data based on a vector law;
Observation and judgement of convert the angular velocity data on the X-axis and the angular velocity data on the Y-axis to vertical angular velocity data based on a vector law;
perform time integration with the vertical angular velocity data based on a time corresponding to a start position and a time corresponding to an end position of the movement of the user to obtain the vertical angle data;
Observation and judgement to evaluate by time integration with the vertical angular velocity data based on a time corresponding to a start position and a time corresponding to an end position of the movement of the user to obtain the vertical angle data;
use the angular velocity data on the Z-axis as the horizontal angular velocity data;
Observation and judgement to use the angular velocity data on the Z-axis as the horizontal angular velocity data;
perform time integration with the horizontal angular velocity data based on the time corresponding to the start position and the time corresponding to the end position of the movement of the user to obtain the horizontal angle data.
Observation and judgement to evaluate by time integration with the horizontal angular velocity data based on the time corresponding to the start position and the time corresponding to the end position of the movement of the user to obtain the horizontal angle data.
determine relative motion between the at least one measurement position based on the two-dimensional posture data corresponding to each posture signal.
Observation and judgement to evaluate by relative motion between the at least one measurement position based on the two-dimensional posture data corresponding to each posture signal.
all of which are grouped as mental processes under the 2019 PEG.
Accordingly, as indicated above, each of the above-identified claims recite an abstract idea.
Step 2A, Prong 2
The above-identified abstract ideas in each of Independent Claims 1 and 11 (and their respective Dependent Claims) are not integrated into a practical application under 2019 PEG because the additional elements (identified above in Independent Claims 1 and 11), either alone or in combination, generally link the use of the above-identified abstract ideas to a particular technological environment or field of use. More specifically, the additional elements of:
“at least one storage medium”
“at least one processor”
“posture sensor”
“acceleration sensor”
“angular velocity sensor”
“magnetic sensor”
“image sensor”
Additional elements recited include an “at least one storage medium”, “at least one processor”, “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor”, “image sensor” in the Independent Claims 1 and 11, their dependent claims. These component are recited at a high level of generality, , i.e., as a generic computer processor performing a generic function of processing data (the obtaining, converting, and calculating) and a memory performing a generic function of storing data (the storing). These generic hardware component limitations for “at least one storage medium”, “at least one processor”, “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor”, “image sensor” are no more than mere instructions to apply the exception using generic computer and hardware components. As such, these additional elements do not impose any meaningful limits on practicing the abstract idea.
Further additional elements from Independent Claims 1 and 11 include pre-solution activity limitations, such as:
at least one storage medium storing at least one instruction set for calibrating motion data; and
at least one processor in communication with the at least one storage medium, wherein during operation, the at least one processor executes the set of instructions to:
obtain action data during a movement of a user, wherein the action data includes at least one posture signal corresponding to at least one measurement position on a body of the user, and each posture signal of the at least one posture signal includes three-dimensional posture data of a corresponded measurement position in an original coordinate system,
In addition the aforementioned extra-solution activity limitations in Independent Claims 1 and 11, additional extra-solution activity limitations recited in Dependent Claims 2 – 10 and 12 – 20 include:
each posture signal includes data obtained by a posture sensor, and the original coordinate system includes a coordinate system in which the posture sensor is located.
wherein the posture sensor includes at least one of an acceleration sensor, an angular velocity sensor, or a magnetic sensor.
wherein each posture signal includes data obtained by an image sensor, and the original coordinate system includes a coordinate system in which the image sensor is located.
wherein the three-dimensional posture data includes angle data and angular velocity data on the X-axis, the Y-axis and the Z-axis.
, wherein the three-dimensional motion data includes at least angular velocity data on the X-axis, angular velocity data on the Y-axis, and angular velocity data on the Z-axis; and
wherein the Z-axis of the target coordinate system is in a direction opposite to a vertical direction of a gravity acceleration.
wherein the two-dimensional posture data in the target coordinate system includes:
horizontal posture data, including horizontal angle data and horizontal angular velocity data of the movement of the user in a horizontal plane perpendicular to the Z-axis; and
vertical posture data, including vertical angle data and vertical angular velocity data of the movement of the user in any vertical plane perpendicular to the horizontal plane.
wherein the at least one processor further executes the set of instructions
These pre-solution measurement elements are insignificant extra-solution activity, setting up the parameters of the system, and serve as data-gathering for the subsequent steps.
The “at least one storage medium”, “at least one processor”, “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor”, “image sensor” as recited in Independent Claims 1 and 11 and their dependent claims are generically recited computer and hardware elements which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract ideas identified above in Independent Claims 1 and 11 (and their respective dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer processor as claimed. In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in Independent Claims 1 and 11 (and their respective dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, Independent Claims 1 and 11 (and their respective dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B –
None of Claims 1 – 20 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of: “at least one storage medium”, “at least one processor”, “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor”, “image sensor” as recited in Independent Claims 1 and 11 and their dependent claims.
The additional elements of the “at least one storage medium”, “at least one processor”, “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor”, “image sensor” Claims 1 - 20, as discussed with respect to Step 2A Prong Two, amounts to no more than mere instructions to apply the exception using generic computer and hardware components. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Per Applicant’s specification, the “at least one storage medium” is described generically at [0045] with “The at least one storage medium of the computing device 300 may include a data storage apparatus. The data storage apparatus may be a non-transitory storage medium, or may be a transitory storage medium”. The “at least one storage medium” is shown in Figure 3 as ROM 330 and/or RAM 340.
Per Applicant’s specification, the “at least one processor” is defined generically at [0037] with “a processing module 220 (also referred to as a processor)” and [0048] “the processor 320 may include a microcontroller, a microprocessor…CPU…GPU…may include a plurality of processors”. The “at least one processor” is shown in Fig. 2 as “processing module 220” and Fig. 3 as “at least one processor 320”.
Per Applicant’s specification, the “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor” is defined generically at [0052] “the posture sensor may include, but is not limited to, an acceleration three-axis sensor, an angular velocity three-axis sensor, a magnetic sensor, or the like, or any combination thereof”; “when the posture sensor is configured to obtain a posture signal during movement of the user, the posture sensor may be placed at positions corresponding to a torso, two arms, and joints of the human body”; and “the at least one upper garment obtaining module 4140 may include, but is not limited to, one or more of a posture sensor.” The “acceleration sensor”, “angular velocity sensor”, and “magnetic sensor” are described generically at [0063] as “a nine-axis inertial measurement unit (IMU) having a three-axis acceleration sensor, three-axis angular velocity sensor, and a three-axis geomagnetic sensor.” The “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor” are shown in Fig. 4 as “at least one upper garment obtaining module 4140.”
Per Applicant’s specification, the “image sensor” is defined generically at [0067] with “The image sensor may be an image sensor capable of obtaining depth information, such as a 3D structured light camera or a binocular camera. The image sensor may be installed at any position capable of shooting an image during movement of the user.”
Accordingly, in light of Applicant’s specification, the claimed terms “at least one storage medium”, “at least one processor”, “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor”, “image sensor” are reasonably construed as a generic computing and hardware devices. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the “at least one storage medium”, “at least one processor”, “posture sensor”, “acceleration sensor”, “angular velocity sensor”, “magnetic sensor”, “image sensor”. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Claims 1 – 20 amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the apparatus and method of Claims 1 - 20 are directed to applying an abstract idea as identified above on a general-purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1 - 20 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements for Step 2A Prong 2 in Independent Claims 1 and 11 (and their dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1 - 20 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1 - 20 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1 - 20 are not patent eligible and are rejected under 35 U.S.C. 101.
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.
Claims 1 - 3, 10 – 13, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ladetto et. al., (US 2007/0260418 A1)
Regarding Claims 1 and 11, Ladetto discloses
For Claim 1: A motion data calibration system ([Abstract]), comprising:
at least one storage medium storing at least one instruction set for calibrating motion data ([0097] “…carrier containing program code…”; [0246]) and
at least one processor in communication with the at least one storage medium wherein during operation ([0097] “computer program, or a carrier containing program code, the program or the program code being executable by processor means…”; [0246] “…processor housing…storage memory”), the at least one processor executes the set of instructions ([0097] “computer program, or a carrier containing program code, the program or the program code being executable by processor means…”) to:
For Claim 11: A method for calibrating motion data ([Abstract]), comprising:
For both Claim 1 and Claim 11, Ladetto discloses:
obtain action data during a movement of a user ([0233] “the IMU sensors 2 provide data in respect of relative motions of body portions…”;[0238]; [0025] “detect and provide displacement information for various types of motions made by the pedestrian, such as: normal walking…walking in a crouching position…”), wherein the action data includes at least one posture signal corresponding to at least one measurement position on a body of the user (Fig. 10, “local sensor axes” positioned on the body with +x, +y, and +z axes; [0238] and [0241] “…each IMU sensor 2…two accelerometers which measure the sensor's acceleration in the above-mentioned three perpendicular directions”; [0366] – [0371] “IMU sensors 2a-2e” IMU positions on legs and back) and each posture signal of the at least one posture signal includes three-dimensional posture data of a corresponded measurement position in an original coordinate system (Fig. 10, “local sensor axes” positioned on the body with +x, +y, and +z axes; [0238] and [0241] “…each IMU sensor 2… measure the sensor's acceleration…three perpendicular directions”; [0366] – [0371] “IMU sensors 2a-2e” IMU positions on legs and back)
establish a target coordinate system (Fig. 10 “global (align) axes”; [0377] “…earth frame”), wherein the target coordinate system includes an X-axis, a Y-axis, and a Z-axis mutually perpendicular to each other (Fig 10, “Global (align) axes” with +z, +y, and +x axes.; [0377]) and
convert each posture signal to two-dimensional posture data in the target coordinate system (Fig. 3A, “vertical 2D projection plane” and “horizontal 2D projection plane”; [0017] “a plane containing at least one axis corresponding to an axis of a reference coordinate system on which the motion is to be expressed…”; [0019] “…plane can be a vertical plane…”; Fig 23A and 23B; [0165] “the movement of the pedestrian is to be determined along a coordinate system mapped against a 2D reference plane…2D projection…”)
Regarding Claims 2 and 12, Ladetto discloses The motion data calibration system according to claim 1 and The method according to claim 11, respectively. For the remainder of Claims 2 and 12, Ladetto discloses wherein each posture signal includes data obtained by a posture sensor ([0323] “five IMU sensors 2 a-2 e”; Fig 10; [0238] and [0241] “…each IMU sensor 2…two accelerometers which measure the sensor's acceleration in the above-mentioned three perpendicular directions”), and the original coordinate system includes a coordinate system in which the posture sensor is located (Fig. 10, “local sensor axes” positioned on the body with +x, +y, and +z axes; [0293])
Regarding Claims 3 and 13, Ladetto discloses The motion data calibration system according to claim 2 and The method according to claim 12, respectively. For the remainder of Claims 3 and 13, Ladetto discloses wherein the posture sensor includes at least one of an acceleration sensor ([0238] “…each IMU sensor 2 comprises…two accelerometers…measure the sensor's acceleration…”), an angular velocity sensor ([0238] and [0239] “…each IMU sensor 2 comprises…three gyroscopes…measure absolute angular velocity…”), or a magnetic sensor ([0238] and [0240] “…each IMU sensor 2 comprises…three magnetometers…measure the Earth’s magnetism…”).
Regarding Claims 10 and 20, Ladetto discloses The motion data calibration system according to claim (See 112b interpretation above as claim 1) and The method according to claim 11, respectively. For the remainder of Claims 10 and 20, Ladetto discloses wherein the at least one processor further executes the set of instructions ([0097] “computer program, or a carrier containing program code, the program or the program code being executable by processor means…”) to:
determine relative motion between the at least one measurement position based on the two-dimensional posture data corresponding to each posture signal ([0233] “ IMU sensors 2 provide data in respect of relative motions of body portions, typically motion relative to the PNM”; Fig. 5 “Step direction”, “Left foot step” and “Right foot step” in the 2-D xy plane; Fig. 11, “Step Distance and Orientation”)
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Ladetto in view of Akgul et. al., (US 2021/0397250 A1).
Regarding Claims 4 and 14, Ladetto discloses The motion data calibration system according to claim 1 and The method according to claim 11, respectively. For the remainder of Claims 4 and 14, Ladetto discloses each posture signal (Fig. 10, “local sensor axes” positioned on the body with +x, +y, and +z axes; [0238] and [0241] “…each IMU sensor 2… measure the sensor's acceleration…three perpendicular directions”)
Ladetto does not disclose wherein each posture signal includes data obtained by an image sensor, and the original coordinate system includes a coordinate system in which the image sensor is located
Akgul teaches head and body pose tracking using IMUs for the purpose of aligning sensors for spatial audio applications, including measuring data from a camera in an original coordinate system to be converted to a reference inertial frame with the other sensors [0002], [0003], Fig 13. Specifically for Claims 4 and 14, Akgul teaches wherein each posture signal includes data obtained by an image sensor ([0062] “Camera/3D depth sensor 1002”; Fig 12, “camera frame”), and the original coordinate system includes a coordinate system in which the image sensor is located (Fig 12, “camera frame”).
Akgul provides a motivation to combine at [0003] with “Existing spatial audio platforms include a head pose tracker that uses a video camera to track the head pose of a user…” and [0045] “The ground truth yaw angle is determined by, for example, a face detector in source device 103 that detects the position and orientation of a user's face in a camera reference frame…” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that having a camera with its own coordinate system to be aligned with other sensors in a reference coordinate system would be useful for gathering additional data, particularly for detecting a face for indexing the location of the user’s face relative to supplied 3D spatial audio for watching a movie, playing a video game, or interacting with augmented reality content (applications in [Akgul: 0003]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the human motion capture system with IMU sensors with sensor-alignment coordinate system calculations disclosed by Ladetto with Akgul’s taught camera and audio sensors as part of the human motion capture system sensors input to the sensor alignment calculations, creating a single human motion capture system with IMU sensors and camera sensors aligned to gather additional data that could be applied to augmented reality 3d spatial sound applications for knowing where the subject’s face is at a given time.
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Ladetto in view of Wang et. al., (US 2013/0310711 A1).
Regarding Claims 5 and 15, Ladetto discloses The motion data calibration system according to claim 1 and The method according to claim 11, respectively. For the remainder of Claims 5 and 15, Ladetto discloses wherein the three-dimensional posture data includes angular velocity data on the X-axis, the Y-axis and the Z-axis ([0238] and [0239]“…each IMU sensor 2 comprises…three gyroscopes…measure absolute angular velocity in three mutually perpendicular directions”; Fig. 10, “local sensor axes” positioned on the body with +x, +y, and +z axes).
Ladetto does not specifically specify that the raw data from the gyroscope before rotating to a target coordinate system is angle data for wherein the three-dimensional posture data includes angle data. However, Ladetto does later broadly obtain orientation [0456] “direction of the same steps in terms of an angle indicated along the ordinate” angle data, suggesting that the gyroscope data were integrated at some point to obtain angle data from angular velocity. Using an integral with angular velocity (such as from a gyroscope) to obtain an angle is a fundamental engineering/mathematical relationship that is routinely performed by persons with ordinary skill in the art using.
For a specific teaching of the idea, Wang teaches a human joint motion measuring apparatus attitude sensing unit that integrates gyroscope angular velocity data to obtain angle data to determine the rotation angle orientation of a body part. Specifically for Claims 4 and 14, Wang teaches wherein the three-dimensional posture data includes angle data ([0016] “ …integrates the angular velocity sensed by a triaxial gyroscope to obtain an orientation angle.”)
Wang provides a motivation to combine at [0006] with “During the rehabilitation process, clinicians or physical therapists can evaluate patient's condition changes through measuring the range of motion of the patient's joint. Therefore, it can be seen that the measuring of the joint motion is an important indication of assessing the degree of impairment of the joint for clinicians or physical therapists.” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that performing an integral on angular velocity data from a gyroscope is a common mathematical relationship that yields angle data, which in this application, would be useful for analyzing joint mobility using a human motion capture system’s IMU data.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the gyroscope angular velocity data that becomes angle (orientation data) disclosed in Ladetto with the specific teaching that integration is used the gyroscope data to obtain the angle orientation for a limb taught by Wang, creating a single human motion capture system that uses integration on gyroscope angular velocity data to evaluate angle data for limb orientation.
Claims 6 - 7 and 16 – 17 are rejected under 35 U.S.C. 103 as being unpatentable over Ladetto in view of Aoki et. al., (US 2020/0383609 A1).
Regarding Claims 6 and 16, Ladetto discloses The motion data calibration system according to claim 1 and The method according to claim 11, respectively. For the remainder of Claims 6 and 16, Ladetto discloses wherein to convert each posture signal to the two-dimensional posture data in the target coordinate system (Fig. 3A, “vertical 2D projection plane” and “horizontal 2D projection plane”; [0017] “a plane containing at least one axis corresponding to an axis of a reference coordinate system on which the motion is to be expressed…”; [0019] “…plane can be a vertical plane…”; Fig 23A and 23B; [0165] “the movement of the pedestrian is to be determined along a coordinate system mapped against a 2D reference plane…2D projection…”), the at least one processor further executes the set of instructions ([0097] “computer program, or a carrier containing program code, the program or the program code being executable by processor means…”) to:
obtain a pre-stored conversion relationship between the target coordinate system and the original coordinate system ([0325] “converting quaternions to a rotation matrix; calculating the sensor alignment matrix…”; Fig 11; [0433] “Cearth — to — IMU=rotation matrix from earth frame to IMU frame”);
convert each posture signal to the three-dimensional motion data in the target coordinate system based on the conversion relationship ([0326] “converting the quaternions to a rotation matrix; applying sensor alignment/attitude calibration.”; Fig 11; Fig 10);
convert the three-dimensional motion data in the target coordinate system to the two-dimensional posture data in the target coordinate system (Fig. 3A, “vertical 2D projection plane” and “horizontal 2D projection plane”; [0017] “a plane containing at least one axis corresponding to an axis of a reference coordinate system on which the motion is to be expressed…”; [0019] “…plane can be a vertical plane…”; Fig 23A and 23B; [0165] “the movement of the pedestrian is to be determined along a coordinate system mapped against a 2D reference plane…2D projection…”)
Ladetto does not specifically disclose the angular velocity data part of the output of the rotation matrix application for the limitation wherein the three-dimensional motion data includes at least angular velocity data on the X-axis, angular velocity data on the Y-axis, and angular velocity data on the Z-axis. Generally, a rotation matrix applied to an input of angular velocity data, such as the [0326] “converting the quaternions to a rotation matrix; applying sensor alignment/attitude calibration.”; Fig 11; Fig 10] gyroscope data disclosed by Ladetto would yield a matrix of angular velocity data.
For a particular teaching of rotating gyroscope data and still having angular velocity data, Aoki teaches a human motion capture system that corrects data from multiple IMUs using quaternions or rotation matrix and integration to compensate for error between sensors on different segments [Abstract]. Specifically for Claims 6 and 16, Aoki teaches wherein the three-dimensional motion data includes at least angular velocity data on the X-axis, angular velocity data on the Y-axis, and angular velocity data on the Z-axis ([0038] – [0040] including “quaternion…rotating matrix…an angular velocity corresponding to the segment converted into the information of the standard coordinate system”; Fig 1).
Aoki provides a motivation to combine at [0004] with “When an error in the yaw direction is high, body areas (segments) are twisted in different directions, which is unnatural for a person's whole body posture.” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that applying a rotation matrix to angular velocity data from a gyroscope is a common mathematical relationship that would yields angular velocity data in another orientation, which could be useful for directly analyzing the rotational data from each IMU to determine if unnatural movements of the person’s whole body posture are being measured (which could indicate an error).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the gyroscope angular velocity data from multiple sensors that is corrected using a rotation matrix disclosed in Ladetto with Aoki’s specific teaching that the output of orientation correction with a rotation matrix on gyroscope data is angular velocity data, creating a single human motion capture system that can correct gyroscope angular velocity data from multiple sensors to obtain angular velocity data in a collective reference coordinate system that could be applied to investigating further errors in the system (such as unnatural angular velocity movement directions between sensors).
Regarding Claims 7 and 17, Ladetto in view of Aoki discloses The motion data calibration system according to claim 6 and The method according to claim 16, respectively. For the remainder of Claims 7 and 17, Ladetto discloses wherein the Z-axis of the target coordinate system is in a direction opposite to a vertical direction of a gravity acceleration ([0431] “gravity vector…”; Fig 10, +Z on the “Global (align) axes”).
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Ladetto in view of Aoki et. al., (US 2020/0383609 A1), further in view of Akgul et. al., (US 2021/0397250 A1).
Regarding Claims 8 and 18, Ladetto in view of Aoki discloses The motion data calibration system according to claim 7 and The method according to claim 17, respectively. For the remainder of Claims 8 and 18, Ladetto discloses wherein the two-dimensional posture data in the target coordinate system [0308] “derive the positions of the pedestrian's feet at any time, by means of a geometric vector calculation”; Figure 3A) includes:
horizontal posture data (Table II, Fig 3A; [0216]-[0217]), including horizontal angle data ([0216]-[0217], Table II “Parameter range (min - max) angle (degs)”) and of the movement of the user in a horizontal plane perpendicular to the Z-axis (Fig. 3A, “horizontal 2D projection plane”; [0165] “…the movement of the pedestrian is to be determined along a coordinate system mapped against a 2D reference plane…ground plane…”); and
vertical posture data, including vertical angle data of the movement of the user in any vertical plane perpendicular to the horizontal plane (Fig. 3A, “vertical 2D projection plane”; [0145] “the plots of a pedestrian projected on the YZ plane of the earth at step moments when a pedestrian is walking with the torso inclined at 45° with respect to the displacement path; [0148] “…angle from the direction of the torso during calibration for the different steps…”; Fig 30B)
Ladetto does not particularly disclose and horizontal angular velocity data of the movement of the user in a horizontal plane perpendicular to the Z-axis and vertical angular velocity data of the movement of the user in any vertical plane perpendicular to the horizontal plane. Generally, a rotation matrix applied to an input of angular velocity data, such as the [0326] “converting the quaternions to a rotation matrix; applying sensor alignment/attitude calibration.”; Fig 11; Fig 10] gyroscope data disclosed by Ladetto would yield a matrix of angular velocity data, which could be projected onto Ladetto’s horizontal and vertical planes.
Akgul teaches horizontal posture data, including horizontal angular velocity data of the movement of the user in a horizontal plane ([0052] “The angular rate data is split into vertical and horizontal planes using an estimated gravity vector…“; [0036] “IMU…3-axis MEMs gyro…3-axis MEMS accelerometer…. outputs of IMU 1007 are processed into rotation and acceleration data in an inertial reference frame.”; Fig 13) and vertical posture data, including vertical angular velocity data of the movement of the user in any vertical plane perpendicular to the horizontal plane ([0052] “The angular rate data is split into vertical and horizontal planes using an estimated gravity vector…“; [0036] “IMU…3-axis MEMs gyro…3-axis MEMS accelerometer…. outputs of IMU 1007 are processed into rotation and acceleration data in an inertial reference frame.”; Fig 13)
Akgul provides a motivation to combine at [0005] with “splitting….motion data into vertical and horizontal planes, the vertical plane in the direction of the estimated gravity vector and the horizontal plane perpendicular to the estimated gravity vector; calculating…similarity measures based on the source device motion data and headset motion data in the vertical and horizontal planes over a time window; detecting…a user posture change event based on the calculated similarity measures…” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that splitting the angular velocity into vertical and horizontal components in the target coordinate system would be useful for doing comparative analysis to determine posture changes, such as sitting-to-standing.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the gyroscope angular velocity data from multiple sensors that is corrected using a rotation matrix into vertical and horizontal 2d angle data disclosed in Ladetto with Akgul’s specific teaching that gyroscope data is angular velocity data that can be rotated and split into vertical and horizontal components for analysis, creating a single human motion capture system that can correct gyroscope angular velocity data from multiple sensors to obtain angular velocity data and angle data in a collective reference coordinate system that could be applied to investigating human postural changes, such as sitting-to-standing.
Claim 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ladetto in view of Aoki et. al., (US 2020/0383609 A1), further in view of Akgul et. al., (US 2021/0397250 A1), as evidenced by Hong Kong Polytechnic University (”CH9 Rotation of Rigid Bodies”, Ref U on PTO-892)
Regarding Claims 9 and 19, Ladetto in view of Aoki, further in view of Akgul discloses The motion data calibration system according to claim 8 and The method according to claim 18, respectively, as well as angular velocity data on the X-axis, angular velocity data on the Y-axis, and angular velocity data on the Z-axis (See citation in Claim 6/16 above). For the remainder of Claims 9 and 19, Ladetto discloses wherein to convert the three-dimensional motion data in the target coordinate system to the two-dimensional posture data in the target coordinate system (Fig. 3A, [0017]; Fig 23A and 23B; [0165]), the at least one processor further executes the set of instructions ([0097] “…program code being executable by processor means…”) to:
convert the angular velocity data based on a vector law ([0308] “derive the positions of the pedestrian's feet at any time, by means of a geometric vector calculation”; [0238] and [0239]“…each IMU sensor 2…three gyroscopes which measure absolute angular velocity in three mutually perpendicular directions…”; Fig 10 +x, +y, +z; Fig 11)
obtain the vertical angle data ([0147] – [0148] “in X and Y directions for the pedestrian motion of FIG. 30A/30B…angle from the direction of the torso”; Fig 30B; Fig. 3A, “vertical 2D projection plane”; [0145] “the plots of a pedestrian projected on the YZ plane…”);
use the angular velocity data ([0238] and [0239] “…each IMU sensor 2…three gyroscopes which measure absolute angular velocity in three mutually perpendicular directions…”; Fig 10 +x, +y, +z; Fig 11); and
obtain the horizontal angle data (Fig. 31B, “angle”; [0216]-[0217] Table II “Parameter range (min - max) angle (degs)”;
Ladetto does not specifically disclose convert the angular velocity data on the X-axis and the angular velocity data on the Y-axis to vertical angular velocity data; perform time integration with the vertical angular velocity data based on a time corresponding to a start position and a time corresponding to an end position of the movement of the user, use the angular velocity data on the Z-axis as the horizontal angular velocity data; and perform time integration with the horizontal angular velocity data based on the time corresponding to the start position and the time corresponding to the end position of the movement of the user. Ladetto broadly obtains horizontal and vertical plane angle data, suggesting that the gyroscope data were integrated to obtain angle data, however the integration step is not specifically disclosed. Further, as described above, generally, a rotation matrix applied to an input of angular velocity data, such as the [0326] “converting the quaternions to a rotation matrix; applying sensor alignment/attitude calibration.”; Fig 11; Fig 10] gyroscope data disclosed by Ladetto would yield a matrix of angular velocity data. So the raw angular velocity data on the z-axis would be transformed into angular velocity data in Ladetto.
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Figure A: Excerpt from Hong Kong Polytechnic University reference, pages 1 and 2, showing the Right Hand Rule
While Ladetto does not explicitly disclose use the angular velocity data on the Z-axis as the horizontal angular velocity data. However, based on the right-hand rule of used in physics and engineering, as evidenced by Hong Kong Polytechnical University, “Angular velocity is a vector”: given a z-axis which points upward for the target coordinate system (as in the z-axis of the “reference coordinate system” of Ladetto Fig. 9C, and also given an angular velocity about that z-axis (as taught by the combination of Ladetto and Aoki for angular velocity on the Z-axis described in Claim 6 above, from which this claim depends), then the manner of describing that angular velocity curling about the z-axis would be considered the “horizontal angular velocity data” because it rotates in the horizontal axis, which is the xy axis in Ladetto. The right-hand rule is a well-known physics concept to persons with ordinary skill in the art. Therefore, Ladetto in view of Aoki, as evidenced by Hong Kong Polytechnical University, teaches use the angular velocity data on the Z-axis as the horizontal angular velocity data.
Akgul teaches convert the angular velocity data on the X-axis ([0048] “…rotation rate…integrated…rotation…vectors…xy…horizontal”;([0036] “IMU…3-axis MEMs gyro…3-axis MEMS accelerometer…. outputs of IMU 1007 are processed into rotation and acceleration data in an inertial reference frame.”; Fig 13) and the angular velocity data on the Y-axis ([0048] “…rotation rate…integrated…rotation…vectors…z…vertical”; [0036] “IMU…3-axis MEMs gyro…3-axis MEMS accelerometer…. outputs of IMU 1007 are processed into rotation and acceleration data in an inertial reference frame.”; Fig 13) to vertical angular velocity data based on a vector law (Fig 6A; [0052] “angular rate data is split into vertical and horizontal planes using an estimated gravity vector”);
perform time integration with the vertical angular velocity data based on a time corresponding to a start position and a time corresponding to an end position of the movement of the user to obtain the vertical angle data ([0052] “then integrated over a 0.5 second window, to produce the windowed vertical angle change shown in FIG. 6B…”; Fig 6B);
perform time integration with the horizontal angular velocity data based on the time corresponding to the start position and the time corresponding to the end position of the movement of the user to obtain the horizontal angle data ([0048] “rotation rate and acceleration is then integrated over a moving window to obtain rotation and velocity data…2) horizontal rotation similarity…”).
The combination of Ladetto and Aoki explained in more detail above that applying a rotation matrix to angular velocity data from a gyroscope is a common mathematical relationship that would yields angular velocity data in another orientation, and was cited above to teach the Claim 6 limitations of angular velocity data on the X-axis, angular velocity data on the Y-axis, and angular velocity data on the Z-axis, from which this claim depends. Similarly, Akgul also teaches processing raw angular velocity sensor data in a sensor frame mathematically to obtain angular velocity that is rotated into the target coordinate plane (“inertial reference plane” in Akgul). A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that rotational velocity in a sensor reference frame can be processed into rotational velocity in a target reference frame, which would be useful for directly analyzing the rotational data from each IMU to determine if unnatural movements of the person’s whole body posture are being measured (which could indicate an error) (as in Aoki), or to determine posture change events (as in Akgul).
Further, Akgul provides a motivation to combine at [0005] with “splitting….motion data into
vertical and horizontal planes, the vertical plane in the direction of the estimated gravity vector and the horizontal plane perpendicular to the estimated gravity vector; calculating, using the one or more processors, similarity measures based on the source device motion data and headset motion data in the vertical and horizontal planes over a time window; detecting…a user posture change event based on the calculated similarity measures…” Similarly to the combination with Wang above described for Claims 5 and 15, a person having ordinary skill in the art before the effective filing date of the claimed invention would also recognize that performing an integral on angular velocity data from a gyroscope is a common mathematical relationship that yields angle data, which would be useful for analyzing vertical and horizontal angle changes to determine sit-to-stand posture changes (as in Akgul).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the gyroscope angular velocity data from multiple sensors that is corrected using a rotation matrix into vertical and horizontal 2d angle data disclosed in Ladetto with Akgul’s specific teaching that the output of orientation correction with a rotation matrix on gyroscope data is angular velocity data and that angular velocity data can then be integrated to get angle data, creating a single human motion capture system that can correct gyroscope angular velocity data from multiple sensors to obtain angular velocity data and angle data in a collective reference coordinate system that could be applied to investigating human postural changes, such as sitting-to-standing.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Ladetto et. al., (“Three Dimensional Gait Analysis Using Wearable Acceleration and Gyro Sensors Based on Quaternion Calculations”, Ref V on PTO-892) teaches a body-worn sensor system for which the orientations of the sensor units are converted to the orientations of the body segments by a rotation matrix and then used to construct 2d joint trajectory analyses in a global reference plane.
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/MELISSA JO MONTGOMERY/Examiner, Art Unit 3791
/PATRICK FERNANDES/Primary Examiner, Art Unit 3791
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