Prosecution Insights
Last updated: April 19, 2026
Application No. 17/494,314

Sleep Monitoring Based on Wireless Signals Received by a Wireless Communication Device

Non-Final OA §103
Filed
Oct 05, 2021
Examiner
STEINBERG, AMANDA L
Art Unit
3792
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Cognitive Systems Corp.
OA Round
6 (Non-Final)
50%
Grant Probability
Moderate
6-7
OA Rounds
3y 10m
To Grant
78%
With Interview

Examiner Intelligence

Grants 50% of resolved cases
50%
Career Allow Rate
177 granted / 352 resolved
-19.7% vs TC avg
Strong +28% interview lift
Without
With
+27.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 10m
Avg Prosecution
56 currently pending
Career history
408
Total Applications
across all art units

Statute-Specific Performance

§101
12.6%
-27.4% vs TC avg
§103
45.6%
+5.6% vs TC avg
§102
16.4%
-23.6% vs TC avg
§112
19.9%
-20.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 352 resolved cases

Office Action

§103
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 1/7/2026 has been entered. Response to Arguments Applicant’s amendments and remarks dated 12/10/2025 merit new grounds for rejection in view of the Zhang reference, already cited. Zhang teaches “based on an average variation rate of one or more parameters associated with one or more frequency components in the first channel information” (¶[0050] intensity and periodicity of sleep motion, ¶[0272] and Fig. 11, TSSF is extracted from motion data and used to compute statistics of intensity of motion, ¶¶[0244-0245] detrended statistics are extracted from frequency information and includes mean ¶[0160], ¶[0289]). Applicant’s remarks amount to a general allegation that the combination of Zhang, Raymann, and Gavish as previously applied does not teach newly amended claim limitations. The remarks do not assert that Zhang as modified does not teach the amendments, but rather that the previous grounds for rejection did not show that Zhang as modified teaches the newly added limitations. Therefore, the remarks are unpersuasive in light of the teachings of Zhang, below. Claim Interpretation Applicant has used contingent claiming in the instant claims. See MPEP § 2111.04, II. The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met. For example, assume a method claim requires step A if a first condition happens and step B if a second condition happens. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim. If the claimed invention requires the first condition to occur, then the broadest reasonable interpretation of the claim requires step A. If the claimed invention requires both the first and second conditions to occur, then the broadest reasonable interpretation of the claim requires both steps A and B. Claim Rejections - 35 USC § 103 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. 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) 1-6 and 8-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (U.S. Patent Application Publication No. 2020/0397365) hereinafter referred to as Zhang; in view of Raymann et al. (U.S. Patent Application Publication No. 2018/0042547) hereinafter referred to as Raymann; in view of Gavish (U.S. Patent Application Publication No. 2015/0367097) hereinafter referred to as Gavish; in view of Blackadar et al. (U.S. Patent Application Publication No. 2013/0217979) hereinafter referred to as Blackadar. Regarding claim 1, Zhang teaches a method comprising: receiving, at a wireless communication device operating as a client in a wireless communication network, first wireless signals transmitted through a space from an access point of the wireless communication network, wherein the first wireless signals are received over a first time period (¶[0133], ¶[0135], ¶[0137] list of client devices for performing the system operations of Zhang, all of which may be local client devices, including smart phones in contrast to the “hub device” disclosed by Zhang, see ¶[0141], ¶[0269] local computations, reference app are locally performed); by operation of one or more processors of the wireless communication device (Abstract): generating first channel information from the first wireless signals (¶¶[0049-0050]); processing the first channel information to identify a degree of motion in the space during the first time period based on an average variation rate of one or more parameters associated with one or more frequency components in the first channel information (¶[0050] intensity and periodicity of sleep motion, ¶[0272] and Fig. 11, TSSF is extracted from motion data and used to compute statistics of intensity of motion, ¶¶[0244-0245] detrended statistics are extracted from frequency information and includes mean ¶[0160], ¶[0289]); processing the first channel information to identify a breathing rate of a person in the space during the first time period (¶[0132] breathing rate in the motion data); and performing a sleep monitoring process in response to a determination that: the degree of motion is below a first threshold, wherein the first threshold is determined by the wireless communication device (¶[0109] adaptive upper and lower boundary thresholds, ¶¶[0165-0166] states that the threshold may be pre-determined, adaptively/dynamically determined, and/or determined by a finite state machine and ¶¶[0167-0168] includes that the threshold may be determined and adjusted based on training and adaptively adjusted periodically and based on iterative algorithm adjustment from prior acquired data); and the breathing rate is below a second threshold (¶[0260] sleep is detected when motion is below a threshold, ¶[0263] NREM sleep is detected when breathing rate decreases below a threshold, ¶[0267] initiating sleep assessment, which is “a sleep monitoring process”), wherein the second threshold is determined by the wireless communication device (¶[0109] adaptive upper and lower boundary thresholds, ¶[0166] states that the threshold may be pre-determined, adaptively/dynamically determined, and/or determined by a finite state machine and ¶¶[0167-0168] includes that the threshold may be determined and adjusted based on training and adaptively adjusted periodically and based on iterative algorithm adjustment from prior acquired data; furthermore with respect to determination occurring on the wireless client device, ¶¶[0311-0312] explicitly states that the processing may occur in a unified or distributed software package among the system as disclosed and ¶[0076] describes that the disclosed processing may be on any combination of Type 1 and Type 2 devices including where they are one single device, lastly ¶[0140] is a list of contemplated Type 1 and Type 2 client devices); performing the sleep monitoring process on the wireless communication device, wherein the sleep monitoring process comprises: receiving, at the wireless communication device, second wireless signals transmitted through the space, wherein the second wireless signals are received over a second time period (Fig. 9); and by operation of the one or more processors of the wireless communication device: generating second channel information from the second wireless signals; and processing the second channel information to identify a category of sleep during the second time period (¶[0269]). Zhang does not teach initiating a sleep monitoring process in response to detecting that the person is asleep, wherein detecting that the person is asleep comprises a determination that a degree of motion is below a first threshold that represents a degree of motion and an average breathing rate is below a second threshold that represents an average breathing rate. Zhang further does not teach wherein the first wireless signals include pre-existing data traffic. Attention is drawn to the Raymann reference, which teaches initiating a sleep monitoring process (Fig. 8, step 810 “Start Time for Sleep” which monitors the sleep duration from sleep onset to wake, ¶[0065] monitoring includes distinguishing between light and deep sleep) in response to detecting that the person is asleep (Fig. 8, steps 806-808, sleep latency is the time between a user attempts to go to sleep and successfully sleeps, ¶[0078]), wherein detecting that the person is asleep comprises a determination that a degree of motion is below a first threshold that represents a predetermined degree of motion (¶[0024] below a threshold frequency and/or magnitude of motion) and an average breathing rate is below a second threshold that represents a predetermined average breathing rate (¶[0026] breathing rate, rate variability, and/or amplitude below respective thresholds, ¶[0022] combination of motion and breathing). It would have been obvious to one of ordinary skill in the art at the time of filing to modify the sleep onset detection of Zhang to include initiating a sleep monitoring process based on respective motion and breathing rate thresholds, as taught by Raymann, because Raymann teaches that automatically determining sleep latency can improve user experiences by helping a user feel more rested (Raymann ¶[0005]), and that using a combination of signals improves the probability that sleep determination is correct (Raymann ¶[0022]). Zhang as modified does not teach calculating an average breathing rate of a person in the space during the first time period, or wherein the first wireless signals include pre-existing data traffic. Attention is drawn to the Gavish reference, which teaches processing the first channel information to identify an average breathing rate of a person in the space during the first time period (¶[0093] average respiration rate) and detecting onset of sleep based on the average breathing rate (Fig. 7, element 774 “Respiration Characterizes Sleep? ¶[0093]) including setting of an adaptive threshold that is set statistically based on user behavior from previous monitoring (¶[0066] predetermined or obtained adaptively via statistical analysis of previous characteristics, ¶[0088] where the time derivative of the respiration signal is compared to the adaptive threshold for detecting a phase change for stimulation or not). It would have been obvious to one of ordinary skill in the art at the time of filing to modify the breathing rate calculated by Zhang to use an average breathing rate, as taught by Gavish, because Gavish teaches that the respiration analysis in Gavish improves known methods including detection of the awake-to-sleep transition based on respiration characteristics (Gavish ¶[0005]). Zhang as modified further does not teach wherein the first wireless signals include pre-existing data traffic. Attention is drawn to the Blackadar reference, which teaches first wireless signals in a wireless communication network, comprising pre-existing data traffic (¶[0159], ¶[0169], ¶[0171], ¶[0186]). It would have been obvious to one of ordinary skill in the art at the time of filing to modify the wireless communication device, and received signals of Zhang as modified to include receiving pre-existing data traffic, as taught by Blackadar, because Blackadar teaches that versatile sensors in a network improve data handling, data processing, and power usage in a network of sensors, and enrich informational content of the data obtained (Blackadar ¶[0169], ¶[0212]). Regarding claim 2, Zhang as modified teaches the method of claim 1. Zhang further teaches wherein the degree of motion is a first degree of motion and processing the second channel information to identify a category of sleep comprises: processing the second channel information to identify a second degree of motion in the space during the second time period (¶[0269]); comparing the second degree of motion with threshold values associated with a plurality of sleep categories (¶¶[0269-0270]); and identifying the category of sleep based on the comparison (¶[0263-0266]). Regarding claim 3, Zhang as modified teaches the method of claim 2. Zhang further teaches wherein the plurality of sleep categories includes: a first category of sleep that is identified if the second degree of motion is below a third threshold; a second category of sleep that is identified if the second degree of motion is above the third threshold and below a fourth threshold; and a third category of sleep that is identified if the second degree of motion is above the fourth threshold (¶[0277] first category awake, respiration is relatively low ratio to motion; second category NREM, respiration at middle level ratio to motion; third category REM, respiration rate relatively high ratio to motion). Regarding claim 4, Zhang as modified teaches the method of claim 2. Zhang further teaches wherein the sleep monitoring process comprises: receiving, at the wireless communication device, third wireless signals transmitted through the space, wherein the third wireless signals are received over a third time period (¶[0133], ¶[0135], ¶[0137]); and by operation of the one or more processors of the wireless communication device (Abstract): generating third channel information from the third wireless signals (¶[0048] multipath channel); and processing the third channel information to identify a third degree of motion in the space during the third time period (Fig. 9, Motion statistics and Breathing rate estimates); and terminating the sleep monitoring process in response to a determination that the third degree of motion is above a third threshold (Fig. 9, Awake determination). Regarding claim 5, Zhang as modified teaches the method of claim 1. Zhang further teaches wherein processing the second channel information to identify a category of sleep comprises identifying multiple categories of sleep during the second time period, wherein the multiple categories of sleep are associated with respective time segments within the second time period (Fig. 9, ¶[0220] awake, REM, NREM). Regarding claim 6, Zhang as modified teaches the method of claim 5. Zhang further teaches comprising: generating a graphical representation of the multiple categories of sleep associated with the respective time segments (¶[0178] information displayed includes sleeping/resting characteristics of the user, which include time information ¶[0220] “time periods of REM, time periods of NREM, time periods of awake…etc.” ¶[0224] assess overall sleep quality); and displaying the graphical representation on a display component of the wireless communication device (¶[0075] presentation may be graphical). Regarding claim 8, Zhang as modified teaches the method of claim 1. Zhang further teaches, wherein the first channel information is processed to identify a breathing rate of a person in the space during the first time period in response to a determination that the degree of motion is below the first threshold (Fig. 9, ¶[0263] after sleep determination due to degree of motion below a first threshold). Zhang does not teach calculating an average breathing rate of a person in the space during the first time period. Attention is drawn to the Gavish reference, which teaches processing the first channel information to identify an average breathing rate of a person in the space during the first time period (¶[0093] average respiration rate) and detecting onset of sleep based on the average breathing rate (Fig. 7, element 774 “Respiration Characterizes Sleep? ¶[0093]). It would have been obvious to one of ordinary skill in the art at the time of filing to modify the breathing rate calculated by Zhang to use an average breathing rate, as taught by Gavish, because Gavish teaches that the respiration analysis in Gavish improves known methods including detection of the awake-to-sleep transition based on respiration characteristics (Gavish ¶[0005]). Regarding claims 9 and 10, Zhang as modified teaches the method of claim 1. Zhang further teaches wherein at least a portion of the sleep monitoring process is performed by a motion detection system that is included in an operating system installed on the wireless communication device (¶[0269] client hardware, including ¶[0140] handheld computing devices). Regarding claim 19, Zhang as modified teaches the method of claim 1. Zhang further teaches wherein determining the first threshold by the wireless communication device comprises automatically adjusting the first threshold based on observed over-night behavior of the person (¶¶[0167-0168] the threshold is set and modified based on training depending from user history and/or current state; furthermore with respect to determination occurring on the wireless client device, ¶¶[0311-0312] explicitly states that the processing may occur in a unified or distributed software package among the system as disclosed and ¶[0076] describes that the disclosed processing may be on any combination of Type 1 and Type 2 devices including where they are one single device, lastly ¶[0140] is a list of contemplated Type 1 and Type 2 client devices). Regarding claims 11-18 and 20, the claims are directed to a device comprising substantially the same subject matter as claims 1-6, 8-10, and 19 and are rejected under substantially the same sections of Zhang, Raymann, Gavish, and Blackadar. Regarding claims 21 and 22, Zhang as modified teaches the method/wireless communication device of claim 1/11. Blackadar further teaches wherein the first wireless signals include eavesdropped signals addressed to one or more other wireless communication devices (¶[0159], ¶[0169], ¶[0171], ¶[0186]). 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 AMANDA L STEINBERG whose telephone number is (303)297-4783. The examiner can normally be reached Mon-Fri 8-4. 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, James Kish can be reached at (571) 272-5554. 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. /AMANDA L STEINBERG/ Examiner, Art Unit 3792
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Prosecution Timeline

Oct 05, 2021
Application Filed
Jul 27, 2023
Non-Final Rejection — §103
Oct 31, 2023
Response Filed
Jan 26, 2024
Non-Final Rejection — §103
Apr 25, 2024
Response Filed
Aug 19, 2024
Final Rejection — §103
Oct 18, 2024
Response after Non-Final Action
Dec 19, 2024
Request for Continued Examination
Dec 20, 2024
Response after Non-Final Action
Jan 11, 2025
Non-Final Rejection — §103
Jul 07, 2025
Response Filed
Sep 05, 2025
Final Rejection — §103
Nov 07, 2025
Interview Requested
Nov 18, 2025
Applicant Interview (Telephonic)
Nov 18, 2025
Examiner Interview Summary
Dec 10, 2025
Response after Non-Final Action
Jan 07, 2026
Request for Continued Examination
Feb 17, 2026
Response after Non-Final Action
Mar 03, 2026
Non-Final Rejection — §103 (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

6-7
Expected OA Rounds
50%
Grant Probability
78%
With Interview (+27.5%)
3y 10m
Median Time to Grant
High
PTA Risk
Based on 352 resolved cases by this examiner. Grant probability derived from career allow rate.

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