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 .
Status of the Claims
2. This Office Action is in response to the Applicant’s filing on 01/15/2026. Claims 1-20 were previously pending, of which claims 1-4, 7-12, 15-18 have been amended, claims 5-6, 13-14, 19-20 have been cancelled, and no new claims have been newly added. Accordingly, claims 1-4, 7-12, 15-18 are currently pending and are being examined below.
Response to Arguments
3. With respect to the Applicant’s remarks, see pages 8-15, filed on 01/15/2026; Applicant’s “Amendment and Remarks” have been fully considered. Applicant’s remarks will be addressed in sequential order as they were presented.
4. With respect to the rejection under 35 U.S.C. 103, applicant’s “Amendment and Remarks” have been fully considered and are persuasive. The prior art of record does not appear to disclose “determining a target damping force of the target door according to the state of the obstacle and a preset category of the obstacle; and applying the damping force to the target door by controlling a damper corresponding to the target door according to the target damping force; wherein, the preset category comprises a first preset category, a second preset category, and a third preset category, determining the target damping force of the target door comprises: in response to the state of the obstacle is dynamic and the obstacle is of the first preset category, determining the target damping force is a first preset damping force corresponding to the first preset category; in response to the state of the obstacle is dynamic and the obstacle is of the second preset category, determining the target damping force is a second preset damping force corresponding to the second preset category: in response to the state of the obstacle is static, determining the target damping force is a third preset damping force corresponding to the third preset category.” as amended in claim 1. However, due to the nature of the applicant’s amendments, the scope of the applicant’s invention has changed and thus requires new analysis and new application of prior art and further search found that Broadhead, Mayer, and Bozich did disclose this limitation as mapped in the final office action below.
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.
Claim(s) 1, 9, & 15 are rejected under 35 U.S.C. 103 as being unpatentable over US20210254387A1 (hereinafter, “Battlogg”), and further in view of US20160348413A1 (hereinafter, “Broadhead”), and further in view of US20180216693A1 (hereinafter, “Mayer”), and further in view of US20230106562A1 (hereinafter, “Bozich”).
7. Regarding claim 1, 9, & 15, Battlogg discloses a method for controlling doors of a vehicle, the method comprising [0001] - [0002]: A door device for controlling the doors of a vehicle to prevent bumps that could cause damage to the door from occurring.
in response to a vehicle been stopped moving, and/or an indication of opening a door of the vehicle is received, detecting whether any obstacle in a target area of the vehicle is present, the target area comprising an opening area of each of the doors and a rear area of each of the doors ([0069], [0072] - [0073] Fig. 2); An indication of opening a door is received when the door handle to the door is operated by a user for the purpose of opening a door to the vehicle (200). Sensor component (4) detects whether an object is within its detection range (25) (target area) or not. This detection range (25) encompasses a rear area of the doors as shown in figure 2.
8. Battlogg does not explicitly teach in response to an obstacle in the target area is detected, obtaining obstacle information of the obstacle comprising a speed of the obstacle, a state of the obstacle according to the speed of the obstacle;
However, Broadhead in the same field of endeavor, teaches in response to an obstacle in the target area is detected, obtaining obstacle information of the obstacle comprising a speed of the obstacle, a state of the obstacle according to the speed of the obstacle [0059] – [0061], [0064]; Broadhead teaches sensors (68) that can determine a detected obstacle’s speed (state of the obstacle) relative to the vehicle (12).
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Battlogg with the teachings of Broadhead, to avoid any impacts that involve a moving obstacle.
9. Battlogg teaches determining a target door, of the doors of the vehicle, corresponding to the obstacle [0051], [0088], The sensor component (4) is attached to a target door [Fig. 1]. When that sensor component (4) detects an object in the travel path of that target door, it will activate a damping force on that target door because an active door damper is arranged on the vehicle door to enable braking of the door movement [0051]. The sensor component (4) being attached to a specific target door is already an indicator of which door will be determined to have detected the object in its travel path in order to control the target door by a damping force. The damping characteristic can be controlled according to a transmitting unit where the transmitting unit can send a signal related to the object information to the receiving unit [0088].
10. Battlogg teaches …of the target door…to the target door…to the target door… [0051], [0088] The sensor component (4) is attached to a target door [Fig. 1]. When that sensor component (4) detects an object in the travel path of that target door, it will activate a damping force on that target door because an active door damper is arranged on the vehicle door to enable braking of the door movement [0051]. The sensor component (4) being attached to a specific target door is already an indicator of which door will be determined to have detected the object in its travel path in order to control the target door by a damping force. The damping characteristic can be controlled according to a transmitting unit where the transmitting unit can send a signal related to the object information to the receiving unit [0088].
Battlogg does not explicitly teach determining a target damping force…according to the state of the obstacle and a preset category of the obstacle; and applying the damping force…by controlling a damper corresponding…according to the target damping force;
However, Mayer teaches determining a target damping force…and applying the damping force…by controlling a damper corresponding…according to the target damping force [0029], [0047], [0058], [0108] – [0109]; Mayer teaches different damping forces such as a low damping force [0029], a high damping force [0029], and a maximum damping force [0047], [0058]. These damping forces occur during the opening of a vehicle door to prevent the vehicle door from making impact with the detected obstruction [0108] – [0109]. These damping actions are settable and controllable therefore the selection of a damping action level constitutes as determination of a damping force as each level maps to a specific force output of the damper device.
Battlogg does not explicitly teach according to the state of the obstacle and a preset category of the obstacle;
However, Broadhead teaches …according to the state of the obstacle… [0059] – [0061], [0064]; Broadhead teaches sensors (68) that can determine a detected obstacle’s speed (state of the obstacle) relative to the vehicle (12).
Battlogg does not explicitly teach …and a preset category of the obstacle;
However, Bozich teaches …and a preset category of the obstacle ([0013] – [0014] Fig. 3); Bozich teaches all preset categories of an obstacle being detected. The system shown in figure 3 can detect obstacles such as other vehicles (first preset category) [0013], pedestrians (second preset category) [0014], and static objects such as stones and trees (third preset category) [0014]. Although Bozich doesn’t explicitly label these detections of different types of entities as preset categories, it would’ve been obvious to one of ordinary skill in the art to consider these different types of entities that are detected as different detection preset categories of obstacles.
Battlogg, Mayer, Broadhead, and Bozich are analogous art because Battlogg teaches determining which door on the vehicle is the target door that is detecting the object as it is being opened while Mayer teaches three different types of damping forces while Broadhead teaches detecting an obstacle and its speed while Bozich teaches detecting multiple types of entities such as other vehicles, pedestrians, and static objects such as trees and stones. One of ordinary skill would have the motivation to combine Battlogg, Mayer, Broadhead, and Bozich with each other because all address complementary issues. They all deal with opening a vehicle door and detecting if an obstacle is present and preventing an impact from occurring during the opening process.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Mayer, Broadhead, and Bozich to modify the teachings of Battlogg to include the teachings of Mayer, Broadhead, and Bozich to further enhance the safety of opening a vehicle door.
11. Battlogg teaches …of the target door comprises: wherein, the preset category comprises a first preset category, a second preset category, and a third preset category, determining the target damping force of the target door comprises:
Battlogg does not explicitly teach wherein, the preset category comprises a first preset category, a second preset category, and a third preset category, determining the target damping force… However, Bozich teaches wherein, the preset category comprises a first preset category, a second preset category, and a third preset category,… ([0013] – [0014] Fig. 3) Bozich teaches all preset categories of an obstacle being detected. The system shown in figure 3 can detect obstacles such as other vehicles (first preset category) [0013], pedestrians (second preset category) [0014], and static objects such as stones and trees (third preset category) [0014]. Although Bozich doesn’t explicitly label these detections of different types of entities as preset categories, it would’ve been obvious to one of ordinary skill in the art to consider these different types of entities that are detected as different detection preset categories of obstacles.
Battlogg does not explicitly teach …determining the target damping force…
However, Mayer teaches …determining the target damping force… [0029], [0047], [0058], [0108] – [0109] Mayer teaches different damping forces such as a low damping force [0029], a high damping force [0029], and a maximum damping force [0047], [0058]. These damping forces occur during the opening of a vehicle door to prevent the vehicle door from making impact with the detected obstruction [0108] – [0109]. These damping actions are settable and controllable therefore the selection of a damping action level constitutes as determination of a damping force as each level maps to a specific force output of the damper device.
Battlogg, Bozich, and Mayer are analogous art because Battlogg teaches determining which door on the vehicle is the target door that is detecting the object as it is being opened while Bozich teaches detecting multiple types of entities such as other vehicles, pedestrians, and static objects such as trees and stones while Mayer teaches three different types of damping forces.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Bozich and Mayer, to modify the teachings of Battlogg to include the teachings of Bozich and Mayer to designate certain detections to specific categories for data recording or to alert the operator of what specifically was detected.
12. Battlogg does not explicitly teach in response to the state of the obstacle is dynamic and the obstacle is of the first preset category, determining the target damping force is a first preset damping force corresponding to the first preset category;
in response to the state of the obstacle is dynamic and the obstacle is of the second preset category, determining the target damping force is a second preset damping force corresponding to the second preset category:
in response to the state of the obstacle is static, determining the target damping force is a third preset damping force corresponding to the third preset category.
However, Broadhead teaches in response to the state of the obstacle is dynamic…
in response to the state of the obstacle is dynamic…
in response to the state of the obstacle is static,… [0059] – [0061], [0064]; Broadhead teaches sensors (68) that can determine a detected obstacle’s speed (state of the obstacle) relative to the vehicle (12). Once the controller (22) determines the speed of an obstacle relative to the vehicle (12), the obstacle’s motion state is known since an obstacle having a non-zero relative speed is, by definition, considered dynamic, where an obstacle having a zero relative speed is considered static. Accordingly, even though Broadhead does not explicitly recite “detecting dynamic and static objects”, the determination of obstacle speed includes the capability to classify objects as dynamic or static.
Battlogg does not explicitly teach …and the obstacle is of the first preset category, determining the target damping force is a first preset damping force corresponding to the first preset category;
…and the obstacle is of the second preset category, determining the target damping force is a second preset damping force corresponding to the second preset category:
determining the target damping force is a third preset damping force corresponding to the third preset category.
However, Bozich teaches …and the obstacle is of the first preset category,…
…and the obstacle is of the second preset category,…
…corresponding to the third preset category ([0013] – [0014] Fig. 3). Bozich teaches all preset categories of an obstacle being detected. The system shown in figure 3 can detect obstacles such as other vehicles (first preset category) [0013], pedestrians (second preset category) [0014], and static objects such as stones and trees (third preset category) [0014]. Although Bozich doesn’t explicitly label these detections of different types of entities as preset categories, it would’ve been obvious to one of ordinary skill in the art to consider these different types of entities that are detected as different detection preset categories of obstacles.
Battlogg does not explicitly teach …determining the target damping force is a first preset damping force corresponding to the first preset category;
…determining the target damping force is a second preset damping force corresponding to the second preset category:
determining the target damping force is a third preset damping force…
However, Mayer teaches …determining the target damping force is a first preset damping force corresponding to the first preset category;
…determining the target damping force is a second preset damping force corresponding to the second preset category:
determining the target damping force is a third preset damping force… [0029], [0047], [0058], [0108] – [0109]; Mayer teaches different damping forces such as a low damping force [0029], a high damping force [0029], and a maximum damping force [0047], [0058]. These damping forces occur during the opening of a vehicle door to prevent the vehicle door from making impact with the detected obstruction [0108] – [0109]. These damping actions are settable and controllable therefore the selection of a damping action level constitutes as determination of a damping force as each level maps to a specific force output of the damper device. It would’ve been obvious to one of ordinary skill to assign the different detected entities from Bozich (preset categories) above to a designated target damping force for that specific type of entity that was detected that Mayer teaches.
Broadhead, Bozich, and Mayer are analogous art to Battlogg because Broadhead teaches determining if a detected obstacle is dynamic or static while Bozich teaches detecting multiple types of entities such as other vehicles, pedestrians, and static objects such as trees and stones while Mayer teaches three different types of damping forces.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Broadhead, Bozich, and Mayer, to modify the teachings of Battlogg to include the teachings of Broadhead, Bozich, and Mayer to further apply a damping force to a specific type of entity detected to prevent sudden braking of a vehicle door when it is unnecessary.
13. Regarding claim 8, Battlogg teaches the method of claim 1, wherein determining the target damping force of the target door further comprising:
in response to the state of the obstacle is static, calculating an opening angle of the target door according to a door parameter of the target door and a distance between the obstacle and the target door, and controlling the target door to open according to the opening angle [0036], [0072], [0077]. The target door is already pre-configured based on the door devices (50) being on their own respective doors of the vehicle. When a door is being opened and a static object is detected such as a pillar, an angle is calculated and is controlled by a braking device (40) so that the door has enough distance between it and the object to prevent a bump from occurring [0072].
Regarding claim 9 specifically, Battlogg discloses a vehicle-mounted device comprising: a processor; and a storage device that stories a plurality of instructions, which when executed by the processor, cause the processor to [0067] – [0068]: Battlogg deals with analyzing sensor data which implies that some sort of processor or controller is present.
Claim(s) 2, 10, & 16 are rejected under 35 U.S.C. 103 as being unpatentable over US20210254387A1 (hereinafter, “Battlogg”), and further in view of US20160348413A1 (hereinafter, “Broadhead”), and further in view of US20180216693A1 (hereinafter, “Mayer”), and further in view of US20230106562A1 (hereinafter, “Bozich”), and further in view of US20210293061A1 (hereinafter, “Blank”).
16. Regarding claims 2, 10, & 16, the modified Battlogg reference does not explicitly teach the method of claim 1, further comprising determining whether the indication of opening the door of the vehicle is received, and comprising:
in response to a touch signal been received from a touch sensor of the door, determining the indication is received.
However, Blank in the same field of endeavor, teaches the method of claim 1, further comprising determining whether the indication of opening the door of the vehicle is received, and comprising:
in response to a touch signal been received from a touch sensor of the door, determining the indication is received ([0024] Fig. 6). Vehicle door handle has touch pads (22) which constitutes as a touch sensor of the door. When these touch pads (22) are touched, the printed circuit board assembly (PCBA) (20) may generate a signal to control an aspect of the vehicle which is an indication that the touch signal has been received.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of the modified Battlogg reference with the teachings of Blank, to have a more accurate reading of when the door is being touched and provide a quicker response time [0024].
Claim(s) 3 – 4, 11 – 12, 17 - 18 are rejected under 35 U.S.C. 103 as being unpatentable over US20210254387A1 (hereinafter, “Battlogg”), and further in view of US20160348413A1 (hereinafter, “Broadhead”), and further in view of US20180216693A1 (hereinafter, “Mayer”), and further in view of US20230106562A1 (hereinafter, “Bozich”), and further in view of US20210293061A1 (hereinafter, “Blank”), and further in view of US20120206380A1 (hereinafter, “Zhao”), and further in view of US20180061415A1 (hereinafter, “Penilla”).
18. Regarding claims 3, 11, & 17, the modified Battlogg reference does not explicitly teach the method of claim 2, wherein in response to the touch signal been received from the touch sensor of the door, determining the indication is received further comprises:
obtaining a decoded signal by decoding the touch signal;
extracting touch characteristics from the decoded signal;
performing a prediction of the touch characteristics by applying the extracted touch characters to a prediction model; obtaining a prediction result and determining the indication is received according to the prediction result, wherein the prediction model is trained by applying preset touch characteristics and a corresponding indication of each the preset touch characteristics.
Blank teaches the method of claim 2, wherein determining whether a user in the vehicle has an intention to open a door of the vehicle further comprises:
obtaining a decoded signal by decoding the touch signal [0030] – [0034]; The touch pads (22) are being decoded by implementing a touch algorithm based on thresholds of the touch, whether a re-touch has occurred, or having simultaneous touch events occur.
extracting touch characteristics from the decoded signal [0030] – [0034]; Touch characteristics may include a failed touch, re-touch, or simultaneous touch events.
The modified Battlogg reference does not appear to explicitly teach performing a prediction of the touch characteristics by applying the extracted touch characters to a prediction model; obtaining a prediction result and determining the indication is received according to the prediction result, wherein the prediction model is trained by applying preset touch characteristics and a corresponding indication of each the preset touch characteristics.
However, Zhao teaches performing a prediction of the touch characteristics by applying the extracted touch characters to a prediction model; obtaining a prediction result [0034] – [0035] and determining the indication is received according to the prediction result,… [0023] The computing device (102) has a contact tracking service (142) and a predicted touch contact tracking (144) module. Both the contact tracking service (142) and the predicted touch contact tracking (144) together act as a prediction model because both are essentially doing the prediction of a touch pattern and determining the result of that specific touch pattern by incorporating various procedures and algorithms to make that determination [0034] – [0035]. This prediction-based touch contact tracking can be implemented into any touch-based devices that incorporate touch related sensors [0023]. Zhao does not rely on touchscreen geometry. Zhao operates on contact component sequences and algorithmic steps required for prediction. Therefore, a person of ordinary skill would have found it obvious to implement the teachings of Zhao into the vehicle door-handle touch pads of Blank in order to apply the prediction techniques to the vehicle door-handle touch pads in order to more precisely predict the user’s intentions when operating a vehicle door.
The modified Battlogg reference does not explicitly teach …wherein the prediction model is trained by applying preset touch characteristics and a corresponding indication of each the preset touch characteristics.
However, Penilla teaches …wherein the prediction model is trained by applying preset touch characteristics and a corresponding indication of each the preset touch characteristics [0046], [0048]. Penilla teaches creating user touch profiles which have preset touch characteristic identifiers which will correspond to a user intention [0048]. If a user has a set intention in mind, that user will make that intention happen based off of the touch characteristic that user is inputting. Since Zhao teaches prediction-based touch contact tracking to improve touch detection and Penilla teaches analyzing touch characteristics and storing user touch profiles to selected moderated system responses, it would have been obvious to one of ordinary skill to combine prediction/tracking of Zhao along with the profile-based response selection of Penilla. Both run on compatible touch sensitive hardware and would yield the predictable advantage of more accurate profile selection and improve user experience. Therefore, if Penilla was implemented into Battlogg, Blank, and Zhao, we can have a prediction model being trained to apply preset touch characteristics in the form of user touch profiles with each user touch profiles corresponding to a preset touch characteristic identifier [0048].
The combination of Blank, Zhao and Penilla are analogous art to Battlogg because Blank teaches on touch pads that are touch sensitive and can detect a type of touch along the door handle of a vehicle door in order to determine a user’s intentions. Zhao teaches on applying prediction results and a prediction model that are based on touch sensitive gestures/patterns. Penilla teaches on creating user touch profiles which constitute as preset touch characteristics with each user touch profile corresponding to a user’s intention.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Blank, Zhao, and Penilla, to modify the teachings of the modified Battlogg reference to include the teachings of Blank, Zhao, and Penilla to create a user system that determine a user’s touch on a vehicle door and more accurately determine a user’s intentions based on that touch as well as a quicker response time due to having preset touch characteristics already saved.
18. Regarding claims 4, 12, and 18, the modified Battlogg reference does not explicitly teach the method of claim 3, wherein extracting touch characteristics from the decoded signal comprises extracting, from the decoded signal, at least one or a combination of a touch position, a touch speed, a touch shape, a touch duration, and a touch intensity.
However, Zhao in the same field of endeavor, teaches the method of claim 3, wherein extracting touch characteristics from the decoded signal comprises extracting, from the decoded signal, at least one or a combination of a touch position, a touch speed, a touch shape, a touch duration, and a touch intensity [0030] – [0032]. Zhao teaches on touch position and incorporates touch positioning into its prediction model. This prediction model being both the contact tracking service (142) and the predicted touch contact tracking (144) which use procedures and algorithms to predict these touch characteristics [0034] – [0035].
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of the modified Battlogg reference with the teachings of Zhao, to have a touch characteristic be implemented in order to more accurately determine a prediction based on specific conditions of that touch characteristic.
Claim(s) 7 is rejected under 35 U.S.C. 103 as being unpatentable over US20210254387A1 (hereinafter, “Battlogg ‘387”), and further in view of US20160348413A1 (hereinafter, “Broadhead”), and further in view of US20180216693A1 (hereinafter, “Mayer”), and further in view of US20230106562A1 (hereinafter, “Bozich”), and further in view of US20210179021A1 (hereinafter, “Battlogg ‘021”).
20. Regarding claim 7, the modified Battlogg ‘387 reference does not explicitly teach the method of claim 1, wherein applying the damping force to the target door by controlling the damper corresponding to the target door according to the target damping force comprises:
by adjusting a parameter of the damper according to the damping force.
However, Battlogg ‘021 in the same field of endeavor, teaches the method of claim 1, wherein applying the damping force to the target door by controlling the damper corresponding to the target door according to the target damping force comprises:
by adjusting a parameter of the damper according to the damping force [0045], [0048], [0080]. Battlogg ‘021 uses thresholds and parameters as a way to control and adjust a damping force of either a low damping force or a high damping force [0045]. Parameters are used to determine the target amount of damping force needed [0080]. Battlogg ‘021 is configured to actuate damping based on a detected obstacle parameter. It would have been obvious to one of ordinary skill to modify the system to determine whether an obstacle is moving or static and to select a corresponding damping preset. This damping preset being based on if an obstacle is static, then most likely it wouldn’t be above a certain threshold which would cause a low damping force. If the object is dynamic, most likely it would be above a certain threshold which would cause a high damping force. Sensors used in the system of Battlogg ‘021 are capable of determining an obstacle speed [0042]. According to figure 1 and 2, the door devices (50) are equipped to each door. Whichever door detects an object will already be an indicator of which target door needs the damping force due to each door having its own door device (50).
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of the modified Battlogg ‘387 reference with the teachings of Battlogg ‘021, to further adjust the damping force faster by simplying adjusting a parameter.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID MESQUITI OVALLE JR. whose telephone number is (571)272-6229. The examiner can normally be reached Monday - Friday 7:30am - 5pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin Piateski can be reached on (571) 270-7429. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
/DAVID MESQUITI OVALLE/ Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669