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 .
Amendment
This office action is responsive to the amendment filed on 5/26/26. As directed by the amendment: claims 31, 33, 36, 39 and 46 have been amended, claims 1-30 and 32 have been canceled, and no new claims have been added. Thus, claims 31 and 33-50 are presently pending in the application.
Allowable Subject Matter
Claims 38-42 and 49 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
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 31, 33-35, 43-48 and 50 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Goldfarb et al. (2014/0142475).
Regarding claim 31, in fig. 1 Goldfarb discloses a walking assistance apparatus comprising: a main frame 110 configured to be mounted on a user; a sensor configured to generate sensed data (joint angles and angular velocities, fig. 9 and 12A [0064][0075][0086]), the sensed data including joint angle data associated with movement of a lower body of the user ([0064][0075][0086]); a drive controller configured to assist movement of the user [0042][0046]; and at least one processor 604 configured to control the drive controller based at least on the sensed data [0064], wherein the at least one processor 604 is further configured to: generate a current gait pattern (current state of the user as defined by the combination of a set of trajectories, and a set of joint feedback gains [0072] see also table 1 for each state) based on the sensed data [0064][0072-0073], identify at least one gait feature (positioning of a part of the body, for example during a stride [0064][0072][0075-0077] Fig. 9 and 12A) corresponding to the current gait pattern (the position of the body corresponds to the state of the user) based on databases corresponding to a plurality of gait tasks (angle databases are compared against the sensed angles in order to determine the state of the user, see claim 1 of Goldfarb), determine a target gait task among the plurality of gait tasks based on the identified at least one gait feature (the next state of the exoskeleton is the target gait task, see claim 11, which is identified based at least on the current positioning of the body), and control the drive controller based on the determined target gait task and the sensed data (Claims 1 and 12).
Regarding claim 33, Goldfarb discloses that the at least one processor is further configured to search the databases corresponding to the plurality of gait tasks [0097], respectively, for similar gait patterns for the current gait pattern ([0097] what the current state is versus an adjacent state, such as sitting versus pre-standing, fig. 11, is constantly compared to using the threshold databases), the identified at least one gait feature (positioning of a part of the body [0064][0075-0077] Fig. 9 and 12A) is to be generated by generating the identified at least one gait feature corresponding the current gait pattern based at least on similarities between the current gait pattern and the similar gait patterns (by comparing sensed angles to database angle thresholds, which do have similarities to the current gait pattern and the similar gait patterns [0097]).
Regarding claim 34, Goldfarb discloses that the identified gait feature is a vector having dimensions of a number of the plurality of gait tasks (the positioning of the body includes joint angles, which are vectors corresponding to various gait tasks [0097]), and each of the dimensions of the vector represents a similarity between the current gait pattern and a portion of the similar gait patterns of each of the plurality of gait tasks (the sensed angles are compared to the threshold angles of the stored gait tasks [0097]).
Regarding claim 35, Goldfarb discloses that the at least one processor is further configured to sense a heel strike indicating a state in which a sole of the user touches a ground from the sensed data [0079], and detect the current gait pattern based on a basic unit of one of a step including a single heel strike [0079] or a stride including two steps.
Regarding claim 43, Goldfarb discloses that a communication interface 602 configured to communicate with an external device (display [0061][0082]).
Regarding claim 44, Goldfarb discloses that the at least one processor is further configured to: transmit information about the target gait task to the external device [0082].
Regarding claim 45, Goldfarb discloses that the external device is a wearable device [0061][0082] and/or a mobile terminal.
Regarding claim 46, in fig. 1 Goldfarb discloses a method, performed by an apparatus including one or more processors 604, for recognizing a gait task [0064][0070] and driving a walking assistance apparatus (Claims 1 and 11-12), the method comprising: obtaining, by the one or more processors, sensed data representing movement of a lower body of a user (fig. 9 and 12A [0064][0075][0086]); the sensed data including joint angle data ([0064][0075][0086]); generating a current gait pattern based on the sensed data (current state of the user as defined by the combination of a set of trajectories, and a set of joint feedback gains [0072] see also table 1 for each state); identifying at least one gait feature (positioning of a part of the body based in part on joint angles, for example during a stride [0064][0072][0075-0077] Fig. 9 and 12A) corresponding to the current gait patten (the position of the body corresponds to the state of the user) based on databases corresponding to a plurality of gait tasks (angle databases are compared against the sensed angles in order to determine the state of the user, see claim 1 of Goldfarb); determining, by the one or more processors 604, a target gait task among the plurality of gait tasks based at least on the identified at least one gait feature (the next state of the exoskeleton is the target gait task, see claim 11, which is identified based at least on the current positioning of the body); and controlling, by the one or more processors 604, a drive controller of the walking assistance apparatus based at least on the target gait task and the sensed data (Claims 1 and 12).
Regarding claim 47, Goldfarb discloses that transmitting, by the one or more processors 604, information about the target gait task to an external device (display [0061][0082]) using a communication interface 602.
Regarding claim 48, Goldfarb discloses that the external device is a wearable device [0061][0082] or a mobile terminal.
Regarding claim 50, Goldfarb discloses that the gait task comprises a walking environment based on at least one of slope [0070], incline, or lack thereof (sitting to pre-standing, claim 11).
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.
Claims 36-37 are rejected under 35 U.S.C. 103 as being unpatentable over Goldfarb, as applied to claims 31 and 34, respectively, in further view of Agrawal et al. (2017/0027803).
Regarding claim 36, Goldfarb is silent regarding that the at least one processor is further configured to normalize the current gait pattern with respect to at least one of a time axis or a data axis. However, Agrawal teaches at least one processor that is configured to normalize a current gait pattern with respect to at least one of a time axis [0173] or a data axis. It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Goldfarb’s at least one processor with at least one processor that is configured to normalize a current gait pattern with respect to at least one of a time axis, as taught by Agrawal, for the purpose of organizing the data to ensure proper control is provided by the motor.
Regarding claim 37, Goldfarb is silent regarding that the at least one processor is further configured to normalize the vector of the identified gait feature. However, Agrawal teaches at least one processor that is configured to normalize a vector of a gait feature [0173]. It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Goldfarb’s at least one processor with at least one processor that is configured to normalize a vector of a gait feature, as taught by Agrawal, for the purpose of organizing the data to ensure proper control is provided by the motor.
Response to Arguments
Applicant's arguments filed 5/26/26 have been fully considered but they are not persuasive.
Applicant argues on page 9 that claimed "gait feature" is not merely a raw sensed parameter or a labeled state, but rather is a derived representation generated from sensed data using databases corresponding to different gait tasks.
This argument is not taken well since this language that the gait feature is a derived representation generated from sensed data using databases corresponding to different gait tasks is not found in the claim language. The claim language only requires that the gait feature corresponds to the current gait pattern based on databases corresponding to a plurality of gait tasks. Therefore, a gait feature being a position of a part of the body ([0064][0075] Fig. 9 and 12A) corresponding to the current gait pattern (the position of the body corresponds to the state of the user) based on databases corresponding to a plurality of gait tasks (angle databases are compared against the sensed angles in order to determine the state of the user, see claim 1 of Goldfarb) appears to be met my Goldfarb.
Applicant argues on page 10 that Goldfarb’s “state” is equated to the claimed “gait feature.”
This argument is not taken well since Goldfarb’s state is equated with the gait pattern.
Applicant argues on page 10 that Goldfarb’s “next state” cannot be equated to the claimed “target gait task” since the claimed target gait task is determined based on the at least one identified gate feature.
This argument is not taken well since Goldfarb’s next state is determined based on at least one identified gate feature, where the positioning of the user’s body parts is used to determine the next state of the user.
Applicant argues on page 10 that Goldfarb's alleged "angle threshold databases" do not correspond to the claimed "databases corresponding to a plurality of gait tasks" and that threshold values used for state transitions are not databases of gait patterns or gait data, nor do they perform the claimed feature identification process.
Examiner disagrees since threshold values are databases since they are stored and compared against and correspond to the gait tasks, as claimed. Further, the identified position of the user’s body part is based on databases corresponding to a plurality of gait tasks, since sensed joint angles are compared to the angle threshold databases, which correspond to the plurality of gait tasks.
Applicant argues on page 10 that Goldfarb fails to disclose searching stored gait patterns for similarity to a current gait pattern, computing similarities between gait patterns, or generating a gait feature based on such similarities.
This argument is not taken well since Goldfarb discloses searching stored gait patterns for similarity to a current gait patterns since Goldfarb compares threshold angles over time, which equate to various states, to current states and determine if the adjacent state has been reached [0097]. With respect to “computing similarities between gait patterns,” this language is not found in the claims. Finally, Goldfarb discloses generating a gait feature (positioning of a portion of the user) based on such similarities since Goldfarb compares sensed angles to database angle thresholds, which do have similarities to the current gait pattern and the similar gait patterns [0097].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RACHEL T SIPPEL whose telephone number is (571)270-1481. The examiner can normally be reached M-F 9:00-5:00 PM.
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/RACHEL T SIPPEL/Primary Examiner, Art Unit 3785
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