Office Action Predictor
Last updated: April 16, 2026
Application No. 18/316,154

ANTI-SNORING PILLOW

Non-Final OA §101§103§112
Filed
May 11, 2023
Examiner
KERZHNER, ALEKSANDR
Art Unit
2165
Tech Center
2100 — Computer Architecture & Software
Assignee
Aiworks Global, INC.
OA Round
1 (Non-Final)
71%
Grant Probability
Favorable
1-2
OA Rounds
3y 9m
To Grant
84%
With Interview

Examiner Intelligence

Grants 71% — above average
71%
Career Allow Rate
162 granted / 229 resolved
+15.7% vs TC avg
Moderate +13% lift
Without
With
+13.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 9m
Avg Prosecution
5 currently pending
Career history
234
Total Applications
across all art units

Statute-Specific Performance

§101
14.0%
-26.0% vs TC avg
§103
46.4%
+6.4% vs TC avg
§102
25.5%
-14.5% vs TC avg
§112
4.8%
-35.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 229 resolved cases

Office Action

§101 §103 §112
DETAILED ACTION This Office action is in response to the original application filed on May 11, 2023. Claims 1-20 are pending in the application, of which, claims 1, 7 and 14 are presented in independent form. 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 . Information Disclosure Statement The information disclosure statements (IDS) submitted on 05/11/2023 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner. Drawings The drawings are objected to because they do not possess satisfactory reproduction characteristics. See 37 C.F.R. 1.84(l). For example, Fig 1A is blurry, Fig 1B is unreadable, Fig 2-4D and 6 are blurry and unreproducible, Fig 5 contains text and lines that are not reproducible. Please see MPEP 608.02(V). Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance. Claim Objections Claim 17 is objected to because of the following informalities: claim appears to be missing a “wherein” clause as well as a linking verb between the words “the settings adjustable”. Examiner suggest amending the claim to recite “The mobile application of claim 14, wherein the settings are adjustable…”. Appropriate correction is required. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1, 7 and 14 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. Claims 1, 7 and 14 contain the trademark/trade names “WiFi” and “Bluetooth”. Where a trademark or trade name is used in a claim as a limitation to identify or describe a particular material or product, the claim does not comply with the requirements of 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph. See Ex parte Simpson, 218 USPQ 1020 (Bd. App. 1982). The claim scope is uncertain since the trademark or trade name cannot be used properly to identify any particular material or product. A trademark or trade name is used to identify a source of goods, and not the goods themselves. Thus, a trademark or trade name does not identify or describe the goods associated with the trademark or trade name. In the present case, the trademark/trade name is used to identify/describe a particular product and, accordingly, the identification/description is indefinite. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 14-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because they are directed to “[a] mobile application” which is software per se. See MPEP 2106.03(I). 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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hung-Nan Hsieh (U.S. Pub No. 2017/0105867 A1), hereinafter Hsieh, in view of Jorasch et al. (U.S. Pub No. 2021/0400142 A1), hereinafter Jorasch. Regarding claim 1, Hsieh teaches: a method for detecting and reducing snoring of a user via a system, the system comprising an anti-snoring pillow ([0007], Fig. 2 #1), a mobile application for use with the anti-snoring pillow ([0009], [0018], Fig. 3), a processor ([0017] where controllers are taught), wherein the anti-snoring pillow, the mobile application, are in communication with each other by WiFi ([0008], Fig. 1 #21,31); wherein the mobile application and the anti-snoring pillow can connect to each other by Bluetooth ([0008] blue-tooth wireless transmission interface is taught); wherein the system is configured to perform operations comprising detecting snoring, and intervening with a position of the user’s head until the snoring is reduced ([0019] where height adjustment is performed utilizing snore-stopping function); the anti-snoring pillow comprising: a pillow component having an interior for housing a plurality of air bags, a microphone board for the detection of snoring, a control box having an air pump, and a printed circuit board assembly, and an outlet pipe for connecting the air pump to the plurality of air bags ([0017], Fig. 1); wherein the mobile application is accessible by the user on a mobile device, and the mobile application comprises controls for adjusting settings of the operations performed by the system (Fig. 3, [0009], [0018]); the method comprising: detecting a first occurrence of snoring from the user ([0010] sound sensor, [0019] snore-stopping function); intervening with the user’s head position by inflating or deflating one or more of the air bags of the plurality of air bags ([0019] where height adjustment is performed utilizing snore-stopping function); analyzing the patterns from the user, wherein the patterns comprise presence or absence of snoring, volume of snoring ([0010] sound sensor, [0019] snore-stopping function). Hsieh does not expressly disclose: the system comprising … a database server … in communication with each other by WiFi; operations comprising detecting snoring, massaging a head of the user; the anti-snoring pillow comprising … a head position sensor; wherein the processor is configured to perform operations comprising utilizing artificial intelligence learning to analyze patterns from the user and optimizing the settings based on the performed analysis; wherein the database server comprises cloud storage for data received from the mobile application and the anti-snoring pillow; analyzing the patterns from the user, wherein the patterns comprise… frequency of snoring; comparing the patterns from the user before and after the intervention; optimizing the settings based on the analyzing and the comparing steps for achieving a desired pattern from the user; and storing the data related to the analysis, comparison, and the optimization in the database server. However, Jorasch teaches: the system comprising … a database server … in communication with each other by WiFi ([0080] where databases are taught, [2059] where sensory data feedback, [3101] WiFi); operations comprising detecting snoring ([2058]-[2059]), massaging a head of the user ([0766] where massage mode is taught); the anti-snoring pillow comprising … a head position sensor ([0907], [2171] where head position sensors are taught); wherein the processor is configured to perform operations comprising utilizing artificial intelligence learning to analyze patterns from the user and optimizing the settings based on the performed analysis ([2058]-[2059] the central controller AI analysis providing feedback); wherein the database server comprises cloud storage for data received from the mobile application and the anti-snoring pillow ([2058]-[2059] the central controller AI analysis providing feedback, [0080] cloud computing environment); analyzing the patterns from the user, wherein the patterns comprise… frequency of snoring ([2058], [2168] characteristic sounds of sleep apnea are detected, frequency of snoring is a characteristic of sleep apnea); comparing the patterns from the user before and after the intervention ([2059] where monitoring of sensory data for feedback and analysis from the central controller AI system is taught); optimizing the settings based on the analyzing and the comparing steps for achieving a desired pattern from the user ([2059] where monitoring of sensory data for feedback and analysis from the central controller AI system is taught); and storing the data related to the analysis, comparison, and the optimization in the database server ([2058]-[2059] the central controller AI analysis providing feedback, [0080] cloud computing environment). Hsieh and Jorasch are analogous art because they are from the same field of endeavor of control and operation of accessories (such as snore preventive pillows). It would have been obvious to a person of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified the functionality, control, and components of snore prevention pillow of Hsieh with including remote database with AI analysis, massage functionality and head position sensor as disclosed in Jorasch. One of ordinary skill in the art would be motivated to do so as to provide continual monitoring of sensory data for feedback as taught by Jorasch at [2058]. Regarding claims 7 and 14, these claims recite limitations substantially identical to those of claim 1 but in system and mobile application form where the scope of the claim under BRI of claim 1 is either identical or narrower than of limitations in claims 7 and 14. Therefore, the same analysis applies and claims are rejected for substantially the same reasons as rendered obvious by Hsieh in view of Jorasch. Regarding claims 2, 9 and 19, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claims 1 and 7 above, and further teach wherein the desired pattern is an absence of snoring (Hsieh: [0019] snore-stopping function; Jorasch: [2168]). Regarding claims 3, 10 and 20, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claims 1, 7 and 14 above, and further teach wherein the artificial intelligence learning of the processor is used to compare data from continued uses of the system by the user of at least two sleeping sessions (Jorasch: [2058]-[2059] the central controller AI analysis providing feedback, [2168]). Regarding claims 4, 11 and 16, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claims 1, 7 and 14 above, and further teach wherein the mobile application is configured to perform tasks comprising viewing information related to the anti-snoring pillow, upgrading firmware related to the anti-snoring pillow, and scheduling a period of time for detection and reduction of snoring (Hsieh: [0009], [0018], Fig. 3; Jorasch: [1264]-[1265] where peripheral can be scheduled to be utilized, [2551]). Regarding claims 5 and 12, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claims 1 and 7 above, and further teach wherein the settings adjustable via the mobile application comprises turning the anti-snoring pillow on or off, sensitivity of the detection of snoring, intensity of the massage, and sensitivity of the intervention of the position of the user’s head (Hsieh: [0009], [0018], Fig. 3; Jorasch: [0907], [2168], [2171] where head position sensors are taught); Regarding claim 6, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claim 1 above, and further teach wherein the control box comprises buttons for turning the anti-snoring pillow on or off, and adjusting the settings of the operations performed by the system (Hsieh: [0007], [0017], Fig. 2-3). Regarding claim 8 and 18, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claim 7 and 14 above, and further teach wherein the patterns from the user comprise presence or absence of snoring, volume of snoring, and frequency of snoring (Hsieh: [0010] sound sensor, [0019] snore-stopping function; Jorasch: [2058]-[2059], [2168] characteristic sounds of sleep apnea are detected). Regarding claim 13, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claim 7 above, and further teach wherein the control box comprises buttons for turning the anti-snoring pillow on or off, and adjusting settings of the snoring reduction, the settings sensitivity of the detection of snoring, intensity of the massage, and sensitivity of the intervention of the position of the user’s head (Hsieh: [0009], [0018], Fig. 3; Jorasch: [0907], [2168], [2171] where head position sensors are taught). Regarding claim 15, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claim 14 above, and further teach wherein the database server comprises cloud storage for data received from the mobile application and the anti-snoring pillow (Jorasch: [2058]-[2059] the central controller AI analysis providing feedback, [0080] cloud computing environment). Regarding claim 17, Hsieh in view of Jorasch teach all the limitations as set forth in the rejection of claim 14 above, and further teach the settings adjustable via the mobile application comprises sensitivity of the detection of snoring, intensity of the massage, and sensitivity of the intervention of the position of the user’s head (Hsieh: [0009], [0018], Fig. 3; Jorasch: [0907], [2168], [2171] where head position sensors are taught). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Aleksandr Kerzhner whose telephone number is (571)270-1760. The examiner can normally be reached M-F 8:00 AM - 4:00 PM. 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, Cordelia (Dede) Zecher can be reached at (571)272-7771. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ALEKSANDR KERZHNER/Supervisory Patent Examiner, Art Unit 2165
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Prosecution Timeline

May 11, 2023
Application Filed
Aug 13, 2025
Non-Final Rejection — §101, §103, §112 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
71%
Grant Probability
84%
With Interview (+13.0%)
3y 9m
Median Time to Grant
Low
PTA Risk
Based on 229 resolved cases by this examiner. Grant probability derived from career allow rate.

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