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 .
Response to Amendment
The following Office Action is in response to amendments filed on 10/14/2025. Claims 1-20 are pending in the application. Claims 1-20 have been rejected as set forth below.
Claim Objections
Claim 1 is objected to because of the following informalities: the phrase “and assembly” in line 16, needs to be changed to “and the assembly”. Appropriate correction is required.
Claim 3 is objected to because of the following informalities: the phrase “the first set of cables” in line 3, needs to be changed to “the first set of one or more cables”. Appropriate correction is required.
Claim 11 is objected to because of the following informalities: the phrase “the first set of cables” in line 3, needs to be changed to “the first set of one or more cables”. Appropriate correction is required.
Claim 19 is objected to because of the following informalities: the phrase “the first set of cables” in line 3, needs to be changed to “the first set of one or more cables”. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. Claim 1, recites: “wherein the certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine”. However, nowhere in the original specification, support for such limitation has been provided. According to at least paragraphs [0135] and [0184] of original specification and claims 2, 10 and 18, the certain criteria comprise: one or more muscle groups, one or more user attributes comprising height, weight, demographic characteristics, psychographic characteristics, race, gender, medical history, comorbidities, prescription medications, non-prescription medications or nutritional supplements, familial medical history, and performed medical procedures on the user, one or more desired goals, more or more desired results, or some combination thereof. Nowhere in the original specification, has applicant recited the certain criteria comprise information specifying one or more physical characteristics of the assembly of the electromechanical machine. As such, this limitation of claim 1 is considered New Matter. Further clarification, appropriate corrections and specific citation of the pertinent portion(s) of the original specification where support for such limitation is found, are respectfully requested. The same also applies to Claims 9 and 17 for reciting the same limitation. Claims 2-8, 10-16 and 18-20 are also rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, by virtue of dependency upon claims 1, 9 or 17.
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 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for the following reasons. Claim 1 recites: “an electromechanical machine comprising…an assembly; and a processing device…to…generate…a motion profile for an assembly of the electromechanical machine”. However, it is unclear whether “an assembly” of the electromechanical machine for which a motion profile is generated is the same as or different from “an assembly” recited as a component of an electromechanical machine. For the purposes of examination, the two recitations of “an assembly” in the claim have been considered to refer to the same component. In addition, Claim 1 recites: “a first set of one or more cables”. Applicant has not provided any specific definition regarding “a first set of one or more cables” in the original specification. The term “set”, according to a dictionary definition (i.e., merriam-webster.com) means: a number of things of the same kind that belong or are used together, a collection of elements and especially mathematical ones (such as numbers or points), etc. Similar definition has been provided by other dictionaries as well, whereby the term “set” refers to a group/number of elements. Therefore, the term “set” requires at least two of whichever element it is referring (i.e. set of cables= at least two cables). As such, it is unclear what is meant by a first set of one or more cables. Furthermore, Claim 1 also recites: “control, using one or more machine learning models trained using training data, at least one of…one or more speed of the one or more motors, one or more resistances provided by the one or more motors…and control, using the desired virtual apparatus model, the one or more motors of the electromechanical machine”. However, it is unclear whether or not and if so, how “control, using one or more machine learning models trained using training data, at least one of…one or more speed of the one or more motors, one or more resistances provided by the one or more motors” is different from “control, using the desired virtual apparatus model, the one or more motors of the electromechanical machine”. Further clarification and appropriate corrections are respectfully requested. Claims 2-8 are also rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, by virtue of dependency upon claim 1.
Claim 9 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for the following reason. Claim 9, line 5, recites: “a first set of one or more cables”. Applicant has not provided any specific definition regarding “a first set of one or more cables” in the original specification. The term “set”, according to a dictionary definition (i.e., merriam-webster.com) means: a number of things of the same kind that belong or are used together, a collection of elements and especially mathematical ones (such as numbers or points), etc. Similar definition has been provided by other dictionaries as well, whereby the term “set” refers to a group/number of elements. Therefore, the term “set” requires at least two of whichever element it is referring (i.e. set of cables= at least two cables). As such, it is unclear what is meant by a first set of one or more cables. In addition, Claim 9, in lines 7-8, recites: “one or more ranges of motion of a carriage and an assembly of the electromechanical machine” and in line 10, recites: “a motion profile for an assembly of the electromechanical machine”. However, it is unclear whether or not “an assembly” recited in line 10 is referring to the same “an assembly” recited in lines 7-8. Furthermore, Claim 9 also recites: “controlling, using one or more machine learning models trained using training data, at least one of…one or more speed of the one or more motors, one or more resistances provided by the one or more motors…and controlling, using the desired virtual apparatus model, the one or more motors of the electromechanical machine”. However, it is unclear whether or not and if so, how “control, using one or more machine learning models trained using training data, at least one of…one or more speed of the one or more motors, one or more resistances provided by the one or more motors” is different from “control, using the desired virtual apparatus model, the one or more motors of the electromechanical machine”. Further clarification and appropriate corrections are respectfully requested. Claims 10-16 are also rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, by virtue of dependency upon claim 9.
Claim 17 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for the following reason. Claim 17, line 6, recites: “a first set of one or more cables”. Applicant has not provided any specific definition regarding “a first set of one or more cables” in the original specification. The term “set”, according to a dictionary definition (i.e., merriam-webster.com) means: a number of things of the same kind that belong or are used together, a collection of elements and especially mathematical ones (such as numbers or points), etc. Similar definition has been provided by other dictionaries as well, whereby the term “set” refers to a group/number of elements. Therefore, the term “set” requires at least two of whichever element it is referring (i.e. set of cables= at least two cables). As such, it is unclear what is meant by a first set of one or more cables. In addition, Claim 17, in lines 8-9, recites: “one or more ranges of motion of a carriage and an assembly of the electromechanical machine” and in line 11, recites: “a motion profile for an assembly of the electromechanical machine”. However, it is unclear whether or not “an assembly” recited in line 11 is referring to the same “an assembly” recited in lines 8-9. Furthermore, Claim 17 also recites: “control, using one or more machine learning models trained using training data, at least one of…one or more speed of the one or more motors, one or more resistances provided by the one or more motors…and control, using the desired virtual apparatus model, the one or more motors of the electromechanical machine”. However, it is unclear whether or not and if so, how “control, using one or more machine learning models trained using training data, at least one of…one or more speed of the one or more motors, one or more resistances provided by the one or more motors” is different from “control, using the desired virtual apparatus model, the one or more motors of the electromechanical machine”. Further clarification and appropriate corrections are respectfully requested. Claims 18-20 are also rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, by virtue of dependency upon claim 17.
Claims 2, 10 and 18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for the following reason. Claim 2 recites: “wherein the certain criteria comprise: one or more muscle groups, one or more user attributes comprising height, weight, demographic characteristics, psychographic characteristics, race, gender, medical history, comorbidities, prescription medications, non-prescription medications or nutritional supplements, familial medical history, and performed medical procedures on the user, one or more desired results, or some combination thereof”, while claim 1, upon which claim 2 depends, recites: “wherein the certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine”. However, it is unclear whether the certain criteria recited in claim 2 are in addition to the certain criteria recited in claim 1 or not. The same also applies to Claim 10 with respect to claim 9, upon which claim 10 depends as well as Claim 18 with respect to claim 17, upon which claim 18 depends. Further clarification and appropriate corrections are respectfully requested.
Claims 3, 11 and 19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for the following reason. Claim 3 recites: “wherein the assembly is coupled to a carriage”. However, it is unclear whether or not “a carriage” recited in claim 3, refers to the same “a carriage” recited in claim 1, upon which claim 3 depends, as part of the electromechanical machine. The same also applies to Claim 11 with respect to claim 9, upon which claim 11 depends as well as Claim 19 with respect to claim 17, upon which claim 19 depends. Further clarification and appropriate corrections are respectfully requested.
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 1-6, 9-14 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Miller et al. (US 2017/0361165 A1, hereinafter referred to as “Miller ‘165”) in view of Miller et al. (US 5,755,645, hereinafter referred to as “Miller ‘645”) and De las Casas Zolezzi et al. (US 2021/0077884 A1, hereinafter referred to as “Zolezzi”).
Regarding claims 1, 9 and 17, Miller ‘165 teaches a computer-implemented system (¶ [3])/a method (¶ [10])/a tangible, non-transitory computer-readable medium storing instructions (¶ [11]), comprising:
an electromechanical machine comprising:
one or more motors (i.e., B3, ¶ [64], the brake B3 is a magnetic particle brake, but can be of any other type including motor/step motor) mounted to a body (Fig. 1) and a first set of one or more cables (as part of the transmission device, ¶ [64], [77]);
a carriage (i.e., 18); and
an assembly (i.e., 8); and
a processing device (computer 110, ¶ [3], [64]) communicatively coupled (via 111) to the one or more motors (¶ [64]), wherein the processing device executes instructions implementing a control system/causes the processing device to:
receive/receiving data comprising a treatment plan, wherein the treatment plan includes one or more prescribed exercises for a user to perform using the electromechanical machine (Figs. 29-31, ¶ [71], [165]);
generate/generating, based on the data and certain criteria, via execution of the one or more machine learning models, a motion profile for an assembly (i.e. 8, Fig. 1, ¶ [63]) of the electromechanical machine, wherein the certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine (i.e., resistance amount and type, Figs. 29-31), wherein the motion profile comprises a movement shape of one or more portions of the electromechanical machine, and wherein the movement shape includes one or more spatial movement paths (Figs. 5B, 11A-11B, 13A-14B, 29-31, ¶ [3]-[4], [64]-[68], [70]-[76], [88]-[93], [96]-[98], [103]-[109], [117]-[119], [122], [126]-[130], [135], [137], [163]-[164], [167]-[168]);
execute/executing a transformation function to implement, using the electromechanical machine, a desired virtual apparatus model, wherein, to implement the desired virtual apparatus model, the transformation function maps the motion profile to one or more coordinates in a domain (Figs. 13A-14B, abstract, ¶ [66]-[68], [71]-[75], [77]-[84], [88]-[93], [96]-[98], [103]-[109], [113], [117]-[119], [121]-[123], [126]-[130], [162]); and
control/controlling, using the desired virtual apparatus model, the one or more motors of the electromechanical machine (Figs. 13B and 14B, ¶ [64], [90]-[93], [96], [126]-[130]).
Miller ‘165 teaches that the brake B3 is a magnetic particle brake, but can be of any other type including motor/step motor (see ¶ [64]). Miller ‘165 is silent about each cable of the first set of one or more cables being coupled to a respective one of the one or more brakes/motors.
Regarding claims 1, 9 and 17, Miller ‘645 teaches a computer-implemented system/method/computer-readable instructions/comprising: an electromechanical machine comprising: one or more brakes (i.e. B3, col. 3, lines 1-3) mounted to a body (Figs. 1-2, indirectly mounted); a first set of one or more cables (i.e. 27) , each cable of the first set of one or more cables coupled to a respective one of the one or more brakes (Figs. 5, col. 4 line 61 – col. 5 line 12, please note that upon modification of Miller ‘165 with features of Miller ‘645, each cable would be coupled to the motor/brake); a carriage (i.e., 18); and an assembly (i.e., 8).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Miller ‘165 wherein each cable of the first set of one or more cables being coupled to a respective one of the one or more brakes/motors as taught by Miller ‘465 in order to provide for a smooth transmission of the load/resistance to the user.
It is Office’s position that Miller ‘165 in view of Miller ‘645 teaches the control system to control, using one or more machine learning models trained using training data, at least one of: one or more spools of the first set of one or more cables, one or more speeds of the one or more motors, one or more resistances provided by the one or more motors, and one or more ranges of motion of the carriage and assembly of the electromechanical machine (Miller ‘165: ¶ [3]-[8], [167]-[168], control one or more resistances provided by the one or more motors through providing various recommendations. Machine learning algorithms can be incorporated to review stored performance data of several users, from such data, the system may determine that power increases are most efficiently achieved for most users by training at 90% of the MVC with two sets of four repetitions each, rather than 80% of the MVC with one set of ten repetitions. The personalized training protocols of others can be automatically updated with 90% MVC resistances and revived exercise sessions. Also the processor can be configured to aggregate trajectory and performance data generated by users, providing the ability to learn from individual user and aggregate user behavior, the system can thus automatically assess user performance, and the quality of a user’s training, exercise, and recovery movements and overall programs without the need for direct human intervention or supervision, the system is further able to provide suggestions for correcting a user movement, providing recommendations for correcting or improving the user movement, and/or suggest or automatically generate personalized training and recover programs to address a user’s needs). However, if applicant is not in agreement with the Office’s position, such limitations are taught by Zolezzi.
Regarding claims 1, 9 and 17, Zolezzi teaches a computer-implemented system/method/computer-readable instructions/comprising: an electromechanical machine (100) comprising: one or more motors mounted to a body (i.e., 102, Fig. 1, abstract, ¶ [142], [144], [146]) and a first set of one or more cables (i.e., 116, 117, Fig. 1, ¶ [145]), each cable of the first set of one or more cables coupled to a respective one of the one or more motos (Fig. 1, ¶ [146]), an assembly (i.e., 130, Fig. 1, ¶ [23]-[24]), and a processing device (i.e., controller) communicatively coupled to the one or more motors (¶ [23], [159]), wherein the processing device executes instructions implementing a control system/causing the processing device to: control/controlling, using one or more machine learning models trained using training data, at least one or more resistances provided by the one or more motors (¶ [26]-[27], [101], [103], [107], [110], [112], [119]-[120], [126]), generate/generating, based on certain criteria, via executing of the one or more machine learning models, a motion profile for an assembly of the electromechanical machine, wherein the certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine, wherein the motion profile comprises a movement shape of one or more portions of the electromechanical machine, and wherein the movement shape includes one or more spatial movement paths (i.e., one or more motion trajectories, ¶ [26]-[27], [100]-[101], [103], [107], [110], [112], [119]-[120], [126]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Miller ‘165 in view of Miller ‘645 wherein the processing device executes instructions implementing the control system to control, using one or more machine learning models trained using training data, at least one of: one or more spools of the first set of one or more cables, one or more speeds of the one or more motors, one or more resistances provided by the one or more motors, and one or more ranges of motion of the carriage and assembly of the electromechanical machine as taught by Zolezzi in order to provide for a safer system in which one or more resistances provided by the one or more motors is adjusted to provide the maximum benefit for the specific user and his/her fitness/rehabilitation purposes based on performance information of other users with similar fitness/rehabilitation purposes.
Regarding claims 2, 10 and 18, Miller ‘165 in view of Miller ‘645 and Zolezzi teaches wherein the certain criteria comprise: one or more muscle groups, one or more user attributes comprising height, weight, demographic characteristics, psychographic characteristics, race, gender, medical history, comorbidities, prescription medications, non-prescription medications or nutritional supplements, familial medical history, and performed medical procedures on the user, one or more desired results, or some combination thereof (Miller ‘165: ¶ [137], [163]-[164]; Zolezzi: ¶ [106]-[108], [110]).
Regarding claims 3, 11 and 19, Miller ‘165 in view of Miller ‘645 and Zolezzi teaches wherein the assembly is coupled to the carriage (Miller ‘165: i.e., 18; Miller ‘645: i.e., 18) to enable movement along a length of an arm (Miller ‘165: i.e., 16, ¶ [63]; Miller ‘645: i.e., 16), wherein the carriage is coupled to each cable of the first set of cables (Miller ‘645: Fig. 5, col. 4 line 61 – col. 5 line 12).
Regarding claims 4, 12 and 20, Miller ‘165 in view of Miller ‘645 and Zolezzi teaches wherein the processing device is further configured to control the one or more motors to operate in a plurality of modes comprising an active mode, an active-assist mode, an assisted mode, a passive mode, or some combination thereof (Miller ‘165: ¶ [68], [101]).
Regarding claims 5 and 13, Miller ‘165 in view of Miller ‘645 and Zolezzi teaches wherein, by using the electromechanical machine in order to control the one or more motors based on the motion profile, the plurality of modes, or some combination thereof, the processing device is further configured to enable performing at least one of the one or more prescribed exercises (Miller ‘165: Figs. 29-31, ¶ [64], [68], [90]-[91], [93], [101]; Zolezzi: ¶ [23], [27], [67], [69], [81]-[87] [126]).
Regarding claims 6 and 14, Miller ‘165 in view of Miller ‘645 and Zolezzi teaches wherein the movement shape comprises a line or a geometrical shape (Miller ‘165: Figs. 3-4, 29-30).
Claims 7-8 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Miller ‘165 in view of Miller ‘645 and Zolezzi as applied to claims 1 and 9 above, and further in view of Shavit (US 2017/0368413 A1).
Regarding claims 7-8 and 15-16, Miller ‘165 in view of Miller ‘645 and Zolezzi teaches the computer-implemented system/method further comprising: a headset configured to present virtual reality (Miller ‘165: ¶ [69], virtual reality glasses are configured to present virtual reality; Zolezzi: ¶ [123]), a display configured to present, based on a prescribed exercise of the one or more prescribed exercises, various information (Miller ‘165: 809, Figs. 29-32, ¶ [69], [165], [169], please note that a headset is also considered a display; Zolezzi: ¶ [123]).
Miller ‘165 in view of Miller ‘645 and Zolezzi is silent about the headset configured to present to the user, based on a prescribed exercise of the one or more prescribed exercises, a virtual reality element, wherein the virtual reality element presents to the user a visual modification of an appearance of the electromechanical machine/the display configured to present to the user, based on a prescribed exercise of the one or more prescribed exercises, an augmented reality element, wherein the augmented reality element displays to the user a visual modification of an appearance of the electromechanical machine.
Regarding claims 7-8 and 15-16, Shavit teaches a computer-implemented system/method comprising: headset configured to present to the user, based on a prescribed exercise of the one or more prescribed exercises, a virtual reality element, wherein the virtual reality element presents to the user a visual modification of an appearance of an electromechanical machine/a display configured to present to the user, based on a prescribed exercise of the one or more prescribed exercises, an augmented reality element, wherein the augmented reality element displays to the user a visual modification of an appearance of an electromechanical machine (¶ [60], [337], [1085], [1116]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Miller ‘165 in view of Miller ‘645 and Zolezzi such that the headset is configured to present to the user, based on a prescribed exercise of the one or more prescribed exercises, a virtual reality element, wherein the virtual reality element presents to the user a visual modification of an appearance of the electromechanical machine/the display configured to present to the user, based on a prescribed exercise of the one or more prescribed exercises, an augmented reality element, wherein the augmented reality element displays to the user a visual modification of an appearance of the electromechanical machine as taught by Shavit in order to provide the user with a more immersive and realistic experience, reduce boredom and motivate the user to exercise.
Response to Arguments
Applicant's arguments filed on 10/14/2025 have been fully considered but they are not persuasive.
In response to applicant’s arguments regarding claim 1, stating:
“As discussed and agreed in the interview, the present amendments to claim 1 are not anticipated or obvious in view of the proposed combination of Miller '165 and Miller '645, even assuming that a reason to combine these references exists (which Applicant does not concede).
As amended, claim 1 recites in part:
controlrling], using one or more machine learning models trained using training data, at least one of: one or more spools of the first set of one or more cables, one or more speeds of the one or more motors, one or more resistances provided by the one or more motors, and one or more ranges of motion of a carriage and assembly of the electromechanical machine;
generat[ing], based on the data and certain criteria, via execution of the one or more machine learning models, a motion profile for an assembly of the electromechanical machine, wherein the certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine wherein the motion profile comprises a movement shape of one or more portions of the electromechanical machine, wherein the movement shape includes one or more spatial movement paths;
Relative to the above amendments, Applicant notes that Miller '165 only briefly discusses machine learning at para. 0167, but not with the details and specifics recited above. Meanwhile, Miller '645 does not appear to discuss machine learning aspects at all. Accordingly, as agreed in the interview, these cited references do not teach or suggest all elements of amended claim 1. Independent claims 9 and 17, while not identical in scope to claim 1, have been similarly amended herein, and Applicant submits these claims likewise are patentably distinct from the cited references.
Accordingly, Applicant respectfully requests withdrawal of the present Section 103 rejections.
Applicant additionally notes that the burden of establishing a prima facie case of obviousness falls on the Examiner. Ex parte Wolters and Kuypers, 214 U.S.P.Q. 735 (PTO Bd. App. 1979). Obviousness cannot be established by combining or modifying the teachings of the prior art to produce the claimed invention 36 absent some teaching or suggestion supporting the combination or modification. See ACS Hospital Systems, Inc. v. Montefiore Hospital, 732 F.2d 1572, 1577, 221 U.S.P.Q. 929, 933 (Fed. Cir. 1984). Accordingly, to establish a prima facie case, the Examiner must not only show that the combination includes all of the claimed elements, but also provide a convincing line of reason as to why one of ordinary skill in the art would have found the claimed invention to have been obvious in light of the teachings of the references. Ex parte Clapp, 227 U.S.P.Q. 972 (B.P.A.I. 1985)”,
the Examiner respectfully disagrees and would like to mention the followings. As stated in the Examiner’s Interview Summary dated 10/14/2025, applicant was told that the proposed amendments, appear to overcome the Miller’165 reference, and an updated search was required to be performed. With respect to the argued limitations cited above, Miller ‘165 teaches the processing device to: generate/generating, based on the data and certain criteria, via execution of the one or more machine learning models, a motion profile for an assembly (i.e. 8, Fig. 1, ¶ [63]) of the electromechanical machine, wherein the certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine (i.e., resistance amount and type, Figs. 29-31), wherein the motion profile comprises a movement shape of one or more portions of the electromechanical machine, and wherein the movement shape includes one or more spatial movement paths (Figs. 5B, 11A-11B, 13A-14B, 29-31, ¶ [3]-[4], [64]-[68], [70]-[76], [88]-[93], [96]-[98], [103]-[109], [117]-[119], [122], [126]-[130], [135], [137], [163]-[164], [167]-[168]). Miller ‘165 at least in ¶ [167]-[168] recites:
“Performance data can be aggregated from several users and stored on a network such that analysis can be performed across several users. For example, the health of a population as a whole can be determined. In another example, users can be stratified based on demographics and can view comparisons of their performance to that of their peers. Peer data may be useful in, for example, detecting an injury or weakness of the user, and a training plan can be adjusted accordingly. Also, recommended exercise sessions and regimens for a given user can be further refined based on the progress or outcomes of others with similar training prescriptions. For example, machine learning algorithms can be incorporated on a cloud-based system to review stored performance data of several users. From such data, the system may determine that power increases are most efficiently achieved for most users by training at 90% of the MVC with two sets of four repetitions each, rather than at 80% of the MVC with one set of ten repetitions. The personalized training protocols of others can be automatically updated with 90% MVC resistances and revised exercise sessions.
A processer can be configured to aggregate trajectory and performance data generated by users, providing the ability to learn from individual user and aggregate user behavior. The system can thus automatically assess user performance, and the quality of a user's training, exercise, and recovery movements and overall programs without the need for direct human intervention or supervision. The system is further able to provide suggestions for correcting a user movement, providing recommendations for correcting or improving the user movement, and/or suggest or automatically generate personalized training and recovery programs to address a user's needs, such as overcoming a particular weakness”.
As such, Miller ‘165 does teach the control system to generate, based on the data and certain criteria, via execution of the one or more machine learning models, a motion profile for an assembly of the electromechanical machine, wherein certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine (i.e., resistance amount and type).
Furthermore, as stated above, it is Office’s position that Miller ‘165 in view of Miller ‘645 teaches the control system to control, using one or more machine learning models trained using training data, at least one of: one or more spools of the first set of one or more cables, one or more speeds of the one or more motors, one or more resistances provided by the one or more motors, and one or more ranges of motion of the carriage and assembly of the electromechanical machine (Miller ‘165: ¶ [3]-[8], [167]-[168], control one or more resistances provided by the one or more motors through providing various recommendations. Machine learning algorithms can be incorporated to review stored performance data of several users, from such data, the system may determine that power increases are most efficiently achieved for most users by training at 90% of the MVC with two sets of four repetitions each, rather than 80% of the MVC with one set of ten repetitions. The personalized training protocols of others can be automatically updated with 90% MVC resistances and revived exercise sessions. Also the processor can be configured to aggregate trajectory and performance data generated by users, providing the ability to learn from individual user and aggregate user behavior, the system can thus automatically assess user performance, and the quality of a user’s training, exercise, and recovery movements and overall programs without the need for direct human intervention or supervision, the system is further able to provide suggestions for correcting a user movement, providing recommendations for correcting or improving the user movement, and/or suggest or automatically generate personalized training and recover programs to address a user’s needs). However, if applicant is not in agreement with the Office’s position, such limitations are taught by Zolezzi. Zolezzi teaches a processing device (i.e., controller) communicatively coupled to one or more motors of an electromechanical machine (¶ [23], [159]), wherein the processing device executes instructions implementing a control system/causing the processing device to: control, using one or more machine learning models trained using training data, at least one or more resistances provided by the one or more motors (see ¶ [26]-[27], [101], [103], [107], [110], [112], [119]-[120], [126]) and generate, based on certain criteria, via executing of the one or more machine learning models, a motion profile for an assembly of the electromechanical machine, wherein the certain criteria include information specifying one or more physical characteristics of the assembly of the electromechanical machine, wherein the motion profile comprises a movement shape of one or more portions of the electromechanical machine, and wherein the movement shape includes one or more spatial movement paths (i.e., one or more motion trajectories, see ¶ [26]-[27], [100]-[101], [103], [107], [110], [112], [119]-[120], [126]). It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Miller ‘165 in view of Miller ‘645 wherein the processing device executes instructions implementing the control system to control, using one or more machine learning models trained using training data, at least one of: one or more spools of the first set of one or more cables, one or more speeds of the one or more motors, one or more resistances provided by the one or more motors, and one or more ranges of motion of the carriage and assembly of the electromechanical machine as taught by Zolezzi in order to provide for a safer system in which one or more resistances provided by the one or more motors is adjusted to provide the maximum benefit for the specific user and his/her fitness/rehabilitation purposes based on performance information of other users with similar fitness/rehabilitation purposes.
Applicant’s similar arguments regarding claims 9 and 17 are moot in view of the above provided explanation.
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, the motivation to combine Miller ‘165 with Miller ‘645 and Zolezzi is found in the knowledge generally available to one of ordinary skill in the art.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2021/0369536 A1 to Mooney et al. (pertinent to claims 1, 9 and 17, see abstract, ¶ [103], [131] and [141]) and US 11,331,537 B1 to Ketchell, III et al. (pertinent to claims 1, 9 and 17, see col. 13 line 52 – col. 14 line 23 and col. 25 lines 25-42).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SHILA JALALZADEH ABYANEH/ Primary Examiner, Art Unit 3784