DETAILED ACTION
This is the Final rejection based on the 18/629,585 application filed on 04/08/2024 and which claims as amended on 01/27/2026 have been considered in the ensuing 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 .
Priority
Application 18/629,585 is a continuation of application 17/902,473 filed on 09/02/2022 now US Patent 11,951,359, which is a continuation of application 17/395,645 filed on 08/06/2021 now US Patent 11,433,276, which is a continuation in part of application 16/869,954 filed 05/08/2020 now US Patent 11,957,956, which has priority to provisionals filed 05/10,2019 and 06/06/2019. Additionally, application 17/902,473 has priority a provisional filed 03/30/2021.
The subject matter of modifying the controllable portions independently of each other, found in the independent claims, can only be found in 17/395,645. Therefore the claims have priority to 08/06/2021.
Response to Amendment
The amendments have been sufficient to overcome the claim objections. The amendments have not been sufficient to overcome the double patenting rejection.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 03/06/2025, 12/23/2024, 10/16/2024, 07/19/2024, 07/18/2025, 09/25/2025, 11/10/2025 and 12/17/2025 were in compliance with the provisions of 37 CFR 1.97. However, the IDS submitted on 05/22/2025 and 06/25/2024 includes 466 cited references, hundreds of which are immaterial to the patentability of applicant' s invention and appear to have not been reviewed for relevance to the instant application prior to submission.
The voluminous immaterial contents of the IDS submitted on 05/22/2025 and 06/25/2024 has overburdened the examiner and prevented a complete and thorough review of each of the cited references from being conducted. Accordingly, to the extent possible, the information disclosure statement is being considered by the examiner.
In order to efficiently utilize the limited examination time afforded to all applicants, the Office requires all future information disclosure statements filed by this applicant' s representative to be constrained to include only those references which are material to the patentability of applicant' s invention.
Refer to 37 CFR 1.56, “Duty to disclose information material to patentability,” and MPEP § 2001.05, “Materiality under 37 CFR 1.56(b),” to ensure that only references which are material to patentability are cited in an information disclosure statement.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11,951,359. Although the claims at issue are not identical, they are not patentably distinct from each other because of the following:
Instant application 18/629,585
US Patent 11,951,359
Claim
Limitation
Claim
Limitation
1
A computer-implemented method for using an artificial intelligence engine to modify resistance of at least two controllable portions of an electromechanical machine, wherein the computer- implemented method comprises:
1
A computer-implemented method for using an artificial intelligence engine to modify resistance of one or more pedals of an exercise device, wherein the computer-implemented method comprises:
The examiner notes that the at least two controllable portions reads on the one or more pedals, as pedals are a controllable portion of an exercise device and that the electromechanical machine reads of the exercise device
1
receiving one or more measurements from one or more sensors associated with the electromechanical machine;
1
while a user performs an exercise using the exercise device, receiving one or more measurements from one or more sensors associated with the one or more pedals of the exercise device
1
generating, by the artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, one or more control instruction that cause the electromechanical machine to modify, independently of each other, the resistance of the one or more controllable portions;
1
generating, by the artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, a control instruction that causes the exercise device to modify, independently of each other, the resistance of the one or more pedals;
1
and transmitting the one or more control instruction to the electromechanical machine to cause the resistances provided by the at least two controllable portions to be modified independently of each other.
1
and transmitting the control instruction to the exercise device to cause the resistance provided by the one or more pedals to be modified independently of each other.
2
wherein the outputting further comprises determining, based on the one or more measurements, a quantifiable or qualitative modification to the resistance provided by a first controllable portion of the at least two controllable portions, wherein the resistance provided by another controllable portion of the at least two controllable portions is not modified.
2
the outputting further comprises determining, based on the one or more measurements, a quantifiable or qualitative modification to the resistance provided by a first pedal of the one or more pedals, wherein the resistance provided by another pedal of the one or more pedals is not modified.
3
wherein the first controllable portion is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post-habilitation, or some combination thereof.
3
the first pedal is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post-habilitation, or some combination thereof.
4
wherein the another controllable portion of the at least two controllable portions is actuated by a second limb.
4
the another pedal of the one more pedals is actuated by a second limb.
5
further comprising presenting a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
5
further comprising presenting a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by a first pedal.
6
causing a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
6
further comprising causing a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by a first pedal.
7
the control instruction automatically causes the resistance provided by a first controllable portion of the at least two controllable portions to be modified in real-time or near real-time.
7
wherein the control instruction automatically causes the resistance provided by a first pedal to be modified in real-time or near real-time.
8
wherein the at least two controllable portions comprise foot pedals, hand pedals, or some combination thereof.
8
the one or more pedals comprise foot pedals, hand pedals, or some combination thereof.
9
receiving one or more subsequent measurements from the one or more sensors; determining whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modifying the resistance to be provided by the at least two controllable portions.
9
receiving one or more subsequent measurements from the one or more sensors; determining whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modifying the resistance to be provided by the one or more pedals.
10
receiving input from the user, wherein the input comprises an instruction to modify an operating parameter of the electromechanical machine, and the input is received via a microphone, a touchscreen, a keyboard, a mouse, a proprioceptive sensor, or some combination thereof.
10
receiving input from the user, wherein the input comprises an instruction to modify an operating parameter of the exercise device, and the second input is received via a microphone, a touchscreen, a keyboard, a mouse, a proprioceptive sensor, or some combination thereof.
11
the control instruction causes the electromechanical machine to modify a range of motion of the at least two controllable portions independently of each other.
11
the control instruction causes the exercise device to modify a range of motion of the one or more pedals independently of each other.
12
A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:
12
A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:
12
while a user performs an exercise using an electromechanical machine, receive one or more measurements from one or more sensors associated with the electromechanical machine;
12
while a user performs an exercise using an exercise device, receive one or more measurements from one or more sensors associated with one or more pedals of the exercise device;
12
generate, by an artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, a control instruction that causes the electromechanical machine to modify, independently of each other, the resistance of at least two controllable portions of the electromechanical machine;
12
generate, by an artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, a control instruction that causes the exercise device to modify, independently of each other, the resistance of the one or more pedals;
The examiner notes that the at least two controllable portions reads on the one or more pedals, as pedals are a controllable portion of an exercise device and the electromechanical machine reads on the exercise device
12
and transmit the control instruction to the electromechanical machine to cause the resistances provided by the at least two controllable portions to be modified independently of each other.
12
and transmit the control instruction to the exercise device to cause the resistance provided by the one or more pedals to be modified independently of each other.
13
a first controllable portion of the at least two controllable portions is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post- habilitation, or some combination thereof.
13
a first pedal of the one or more pedals is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post-habilitation, or some combination thereof.
14
a second controllable portion of the at least two controllable portions is actuated by a second limb.
14
a second pedal of the one or more pedals is actuated by a second limb.
15
the processing device is configured to present a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
15
the processing device is configured to present a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by a first pedal of the one or more pedals.
16
the processing device is configured to cause a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
16
the processing device is configured to cause a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by a first pedal of the one or more pedals.
17
the control instruction automatically causes the resistance provided by a first controllable portion of at least two controllable portions to be modified in real-time or near real-time.
17
the control instruction automatically causes the resistance provided by a first pedal of the one or more pedals to be modified in real-time or near real-time.
18
the at least two controllable portions comprise foot pedals, hand pedals, or some combination thereof.
18
the one or more pedals comprise foot pedals, hand pedals, or some combination thereof.
19
the processing device is configured to: receive one or more subsequent measurements from the one or more sensors; determine whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modify the resistance to be provided by the at least two controllable portions.
19
the processing device is configured to: receive one or more subsequent measurements from the one or more sensors; determine whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modify the resistance to be provided by the one or more pedals.
20
A system comprising: a memory device storing instructions
20
A system comprising: a memory device storing instructions;
20
and a processing device communicatively coupled to the memory device, wherein the processing device executes the instructions to: while a user performs an exercise using an electromechanical machine, receive one or more measurements from one or more sensors associated with the electromechanical machine;
20
and a processing device communicatively coupled to the memory device, wherein the processing device executes the instructions to: while a user performs an exercise using an exercise device, receive one or more measurements from one or more sensors associated with one or more pedals of the exercise device;
20
generate, by an artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, a control instruction that causes the electromechanical machine to modify, independently of each other, the resistance of at least two controllable portions of the electromechanical machine;
20
generate, by an artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, a control instruction that causes the exercise device to modify, independently of each other, the resistance of the one or more pedals;
The examiner notes that the one or more controllable portions reads on the one or more pedals, as pedals are a controllable portion of an exercise device
20
and transmit the control instruction to the electromechanical machine to cause the resistances provided by the two or more controllable portions to be modified independently of each other.
20
transmit the control instruction to the exercise device to cause the resistance provided by the one or more pedals to be modified independently of each other.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11,433,276. Although the claims at issue are not identical, they are not patentably distinct from each other because of the following:
Instant application 18/629,585
US Patent 11,433,276
Claim
Limitation
Claim
Limitation
1
A computer-implemented method for using an artificial intelligence engine to modify resistance of at least two controllable portions of an electromechanical machine, wherein the computer- implemented method comprises:
1
A computer-implemented method for using an artificial intelligence engine to modify resistance of one or more pedals of an exercise device, wherein the computer-implemented method comprises:
1
receiving one or more measurements from one or more sensors associated with the electromechanical machine;
1
while a user performs an exercise using the exercise device, receiving the one or more measurements from one or more sensors associated with the one or more pedals of the exercise device;
1
generating, by the artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, one or more control instruction that cause the electromechanical machine to modify, independently of each other, the resistance of the one or more controllable portions;
1
generating, by the artificial intelligence engine, a machine learning model trained to receive one or more measurements as input; outputting, based on the one or more measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the one or more pedals;
The examiner notes that the at least two controllable portions reads on the one or more pedals, as pedals are a controllable portion of an exercise device and that the electromechanical machine reads on the exercise device
1
and transmitting the one or more control instruction to the electromechanical machine to cause the resistances provided by the at least two controllable portions to be modified independently of each other.
1
and transmitting the control instruction to the exercise device to cause the resistance provided by the first pedal to be modified.
The Examiner notes that the phrase above indicates that the pedals/controllable members are modifiable independent of each other
2
wherein the outputting further comprises determining, based on the one or more measurements, a quantifiable or qualitative modification to the resistance provided by a first controllable portion of the at least two controllable portions, wherein the resistance provided by another controllable portion of the at least two controllable portions is not modified.
1
determining, based on the one or more measurements, a quantifiable or qualitative modification to the resistance provided by a first pedal of the one or more pedals, wherein the resistance provided by another pedal of the one or more pedals is not modified;
3
wherein the first controllable portion is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post-habilitation, or some combination thereof.
2
The first pedal is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post-habilitation, or some combination thereof.
4
wherein the another controllable portion of the at least two controllable portions is actuated by a second limb.
3
the another pedal of the one or more pedals is actuated by a second limb.
5
further comprising presenting a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
4
presenting a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by the first pedal.
6
causing a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
5
a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by the first pedal.
7
the control instruction automatically causes the resistance provided by a first controllable portion of the at least two controllable portions to be modified in real-time or near real-time.
6
the control instruction automatically causes the resistance provided by the first pedal to be modified in real-time or near real-time.
8
wherein the at least two controllable portions comprise foot pedals, hand pedals, or some combination thereof.
7
the one or more pedals comprise foot pedals, hand pedals, or some combination thereof.
9
receiving one or more subsequent measurements from the one or more sensors; determining whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modifying the resistance to be provided by the at least two controllable portions.
8
receiving one or more subsequent measurements from the one or more sensors; determining whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modifying the resistance to be provided by the one or more pedals.
10
receiving input from the user, wherein the input comprises an instruction to modify an operating parameter of the electromechanical machine, and the input is received via a microphone, a touchscreen, a keyboard, a mouse, a proprioceptive sensor, or some combination thereof.
9
receiving second input from the user, wherein the second input comprises an instruction to modify an operating parameter of the exercise device, and the second input is received via a microphone, a touchscreen, a keyboard, a mouse, a proprioceptive sensor, or some combination thereof.
11
the control instruction causes the electromechanical machine to modify a range of motion of the at least two controllable portions independently of each other.
10
the control instruction causes the exercise device to modify a range of motion of the one or more pedals independently from each other.
12
A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:
11
A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:
12
while a user performs an exercise using an electromechanical machine, receive one or more measurements from one or more sensors associated with the electromechanical machine;
11
while a user performs an exercise using the exercise device, receive the one or more measurements from one or more sensors associated with the one or more pedals of the exercise device;
12
generate, by an artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, a control instruction that causes the electromechanical machine to modify, independently of each other, the resistance of at least two controllable portions of the electromechanical machine;
11
generate, by an artificial intelligence engine, a machine learning model trained to receive one or more measurements as input; output, based on the one or more measurements, a control instruction that causes an exercise device to modify, independently from each other, a resistance of one or more pedals;
The examiner notes that the one or more controllable portions reads on the one or more pedals, as pedals are a controllable portion of an exercise device
12
and transmit the control instruction to the electromechanical machine to cause the resistances provided by the at least two controllable portions to be modified independently of each other.
11
transmit the control instruction to the exercise device to cause the resistance provided by the first pedal to be modified.
The Examiner notes that the phrase above indicates that the pedals/controllable members are modifiable independent of each other
13
a first controllable portion of the at least two controllable portions is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post- habilitation, or some combination thereof.
12
the first pedal is actuated by an affected limb, and the affected limb is associated with rehabilitation, prehabilitation, post-habilitation, or some combination thereof.
14
a second controllable portion of the at least two controllable portions is actuated by a second limb.
13
the another pedal of the one or more pedals is actuated by a second limb.
15
the processing device is configured to present a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
14
the processing device is configured to present a notification on a user interface of a computing device associated with the user, wherein the notification comprises a prompt to modify the resistance provided by the first pedal.
16
the processing device is configured to cause a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by a first controllable portion of the at least two controllable portions.
15
the processing device is configured to cause a speaker to generate a notification, wherein the notification comprises a prompt to modify the resistance provided by the first pedal.
17
the control instruction automatically causes the resistance provided by a first controllable portion of at least two controllable portions to be modified in real-time or near real-time.
16
the control instruction automatically causes the resistance provided by the first pedal to be modified in real-time or near real-time.
18
the at least two controllable portions comprise foot pedals, hand pedals, or some combination thereof.
17
the one or more pedals comprise foot pedals, hand pedals, or some combination thereof.
19
the processing device is configured to: receive one or more subsequent measurements from the one or more sensors; determine whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modify the resistance to be provided by the at least two controllable portions.
18
the processing device is configured to: receive one or more subsequent measurements from the one or more sensors; determine whether the one or more subsequent measurements indicate at least two strength characteristic levels for at least two limbs of the user; and responsive to determining that the one or more subsequent measurements indicate at least one of the at least two strength characteristic levels for the at least two limbs, modify the resistance to be provided by the one or more pedals.
20
A system comprising: a memory device storing instructions
20
A system comprising: a memory device storing instructions;
20
and a processing device communicatively coupled to the memory device, wherein the processing device executes the instructions to: while a user performs an exercise using an electromechanical machine, receive one or more measurements from one or more sensors associated with the electromechanical machine;
and a processing device communicatively coupled to the memory device, wherein the processing device executes the instructions to:…….. while a user performs an exercise using the exercise device, receive the one or more measurements from one or more sensors associated with the one or more pedals of the exercise device;
20
generate, by an artificial intelligence engine, a machine learning model trained to: receive the one or more measurements as input, and output, based on the one or more measurements, a control instruction that causes the electromechanical machine to modify, independently of each other, the resistance of at least two controllable portions of the electromechanical machine;
generate, by an artificial intelligence engine, a machine learning model trained to receive one or more measurements as input; output, based on the one or more measurements, a control instruction that causes an exercise device to modify, independently from each other, a resistance of one or more pedals;
The examiner notes that the one or more controllable portions reads on the one or more pedals, as pedals are a controllable portion of an exercise device
20
and transmit the control instruction to the electromechanical machine to cause the resistances provided by the two or more controllable portions to be modified independently of each other.
transmit the control instruction to the exercise device to cause the resistance provided by the first pedal to be modified.
The Examiner notes that the phrase above indicates that the pedals/controllable members are modifiable independent of each other
Examiner’s Note
The Examiner notes that no prior art has been used to reject the claims, however, the claims have been rejected under double patenting twice.
Response to Arguments
No arguments have been submitted. While the Applicant states that the double patenting rejection has been overcome, no arguments or evidence has been provided.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEGAN M ANDERSON whose telephone number is (313)446-6531. The examiner can normally be reached M-TH 6 a.m. -4 p.m. (Arizona).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, LoAn Jimenez can be reached at 571-272-4966. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Megan Anderson/Primary Examiner, Art Unit 3784