Prosecution Insights
Last updated: April 19, 2026
Application No. 18/181,793

SYSTEM AND METHOD FOR DETERMINING THE DISTRIBUTION OF FORCES ALONG THE BLADE OF A LARYNGOSCOPE

Non-Final OA §102§112
Filed
Mar 10, 2023
Examiner
FRISBY, KESHA
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Cae Healthcare Canada Inc.
OA Round
4 (Non-Final)
53%
Grant Probability
Moderate
4-5
OA Rounds
3y 7m
To Grant
76%
With Interview

Examiner Intelligence

Grants 53% of resolved cases
53%
Career Allow Rate
397 granted / 755 resolved
-17.4% vs TC avg
Strong +24% interview lift
Without
With
+23.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
26 currently pending
Career history
781
Total Applications
across all art units

Statute-Specific Performance

§101
23.1%
-16.9% vs TC avg
§103
34.0%
-6.0% vs TC avg
§102
24.6%
-15.4% vs TC avg
§112
14.4%
-25.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 755 resolved cases

Office Action

§102 §112
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 . 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. Claim 11 is 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. This claims contain an instance of vague indefinite claim language, including the use of the phrase “can”. It is unclear whether the features following “can” in each claim is intended to be positively recited as part of the claimed invention. Claim Rejections - 35 USC § 102 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claim(s) 1-22 is/are rejected under 35 U.S.C. 102(a)(1)/102(a)(2) as being anticipated by Kotamarti et al. (U.S. Publication Number 2020/0375447). Referring to claim1, Kotmarti et al. discloses comprising a laryngoscope including a blade provided with a plurality of force sensors therealong (Fig. 1), the force sensors being adapted to detect forces applied thereon resulting from a user inserting or manipulating the laryngoscope inside a mouth and an airway (paragraph 0009), and to transmit respective force signals (Figs. 8, 9A, 9B and 10), a processing device comprising a processor and storage medium having stored thereon processor-readable instructions (Figs. 8, 9A, 9B and 10) for: processing force data derived from the respective force signals (Figs. 8, 9A, 9B and 10) and, determining a force distribution along the blade based on the force data (paragraph 0009); comparing the force distribution determined with a reference force distribution, the processing device comprising a trained predictive model for recognizing a force distribution pattern applied by the user based on previously learned force distribution patterns derived from previously recorded force data (Figs. 8, 9A, 9B and 10); and outputting for display a visual indication indicative of a deviation of the force distribution being applied along the blade from the reference force distribution, in real-time (Figs. 8, 9A, 9B and 10); and providing personalized feedback to the user regarding force adjustments needed along different portions of the blade to come closer to one of the previously learned force distribution patterns (paragraph 0007). Referring to claim 2, Kotamarti et al. discloses wherein the force sensors are provided on a flexible sensor strip positioned on an inner surface of the blade devised to be in contact with airway structures (310). Referring to claim 3, Kotamarti et al. discloses further comprising a display for displaying a graphical user interface, the graphical user interface comprising the visual indication (Figs. 8, 9A, 9B and 10). Referring to claim 4, Kotamarti et al. discloses further comprising a printed circuit board (PCB) including a communication unit, the communication unit including input connections for receiving the respective force signals from the force sensors, and one or more output connection(s) for sending the force data via a wired or wireless connection to the processing device (Figs. 8, 9A, 9B and 10). Referring to claim 5, Kotamarti et al. discloses wherein reference force distribution data is stored onto the storage medium of the processing device and the comparing is performed based on predetermined thresholds (Figs. 8, 9A, 9B and 10). Referring to claim 6, Kotamarti et al. discloses wherein the visual indication comprises a representation of the blade, and wherein the force distribution and/or the deviation is illustrated on or near the blade using color, icons, letters or numbers (paragraph 0007 – Feedback being given the manner in which is given in this claim does not provide an advantage for one or the other). Referring to claim 7, Kotamarti et al. discloses further comprising an on-board video camera provided on or near the blade, for capturing images during training sessions, the graphical user interface further displaying the images captured in real-time, in addition to the visual indication of the force distribution and/or deviation from the reference force distribution (Figs. 8, 9A, 9B and 10). Referring to claim 8, Kotamarti et al. discloses the graphical user interface comprises the visual indication, said visual indication comprising a visual representation of the blade, wherein the force distribution and/or deviation from the reference force distribution is illustrated along the blade as the user manipulates the blade (Figs. 8, 9A, 9B and 10). Referring to claim 9, Kotamarti et al. discloses wherein: the processing device is configured for storing several force distribution patterns associated with a user over time(Figs. 8, 9A, 9B and 10); and the processing device is further configured for providing, using the trained predictive model, an indication of an improvement of a performance of the user over time, in reaching a standard force distribution pattern (Figs. 8, 9A, 9B and 10). Referring to claim 10, Kotamarti et al. discloses wherein the processing device further comprises an additional trained predictive model trained on previously captured laryngoscopy images labelled as valid or invalid, to determine whether the blade is properly positioned (Figs. 8, 9A, 9B and 10). Referring to claim 11, Kotamarti et al. discloses wherein the additional trained predictive model can further determine a grade or degree of aperture of the larynx based on previously labelled laryngoscopy images (Figs. 8, 9A, 9B and 10). Referring to claim 12, Kotamarti et al. discloses wherein the processing device is configured for processing in real time a plurality of time buffers, and for computing, for each time buffer, statistical data of the forces measured by each of the sensors during a predetermined period while an instructor or clinician performs a laryngoscopy using the laryngoscope, the trained predictive model being configured to detect force distribution patterns along the blade using the statistical data computed for the plurality of time buffers (Figs. 8, 9A, 9B and 10). Referring to claim 13, Kotamarti et al. discloses wherein the trained predictive model is a support-vector machine (SVM) model (Figs. 8, 9A, 9B and 10). Referring to claim 14, Kotamarti et al. discloses comprising a step of associating the distribution of forces applied by the user to a given force distribution pattern determined using a predictive model (paragraph 0040). Referring to claim 15, Kotamarti et al. discloses comprising determining additional practice time required by the user to reach a standard force distribution pattern using the predictive model (Figs. 1-7C). Referring to claim 16, Kotamarti et al. discloses comprising: measuring force signals associated to forces applied to different portions of a blade of a laryngoscope manipulated by a user during the laryngoscopy (paragraph 0040); converting the force signals into force data indicative of a distribution of forces along the blade (Figs. 8, 9A, 9B and 10); comparing the distribution of forces along the blade with at least one previously determined force distribution pattern (Figs. 8, 9A, 9B and 10); and providing for output, in real time, an indication of whether too little, adequate or too much force is applied to each of the different portions of the blade, relative to the at least one previously determined force distribution pattern, while the user manipulates the laryngoscope (Figs. 8, 9A, 9B and 10). Referring to claim 17, Kotamarti et al. discloses wherein comparing the distribution of forces is performed using a predictive model trained on previously collected force signals, collected during a valid laryngoscopy procedure (Figs. 8, 9A, 9B and 10). Referring to claim 18, Kotamarti et al. discloses comprising determining additional practice time required by the user to reach a standard force distribution pattern using the predictive model (Figs. 1-7C). Referring to claim 19, Kotamarti et al. discloses a processor to: process force data derived from force signals indicative of forces applied to different portions of a blade of a laryngoscope manipulated by a user during the laryngoscopy determine a distribution of forces along the blade (Figs. 8, 9A, 9B and 10); compare the distribution of forces along the blade with at least one previously determined force distribution pattern (Figs. 8, 9A, 9B and 10); and provide for output, in real time, an indication of whether too little or too much force is applied to each of the portions of the blade, relative to the at least one previously determined force distribution pattern, while the user manipulates the laryngoscope (Figs. 8, 9A, 9B and 10). Referring to claim 20, Kotamarti et al. discloses further comprising instructions for causing the processor to: use a predictive model trained on previously collected force signals, collected during a valid laryngoscopy procedure (Figs. 8, 9A, 9B and 10). Referring to claim 21, Kotamarti et al. discloses further comprising instructions for causing the processor to: determine additional practice time required by the user to reach a standard force distribution pattern using the predictive model (Figs. 1-7C). Referring to claim 22, Kotamarti et al. discloses wherein the visual indication comprises whether too little, adequate or too much force is applied to each of the different portions of the blade, relative to the at least one previously determined force distribution pattern, while the user manipulates the laryngoscope (Figs. 8, 9A, 9B and 10 & paragraph 0040). Response to Arguments Applicant’s arguments, see Remarks, filed 9/25/2025, with respect to 35 USC 101 have been fully considered and are persuasive. The rejection of claims 1-22 have been withdrawn. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to KESHA FRISBY whose telephone number is (571)272-8774. The examiner can normally be reached Monday-Friday 730AM-4PM. 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, Xuan Thai can be reached at 571-272-7147. 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. /KESHA FRISBY/Primary Examiner, Art Unit 3715
Read full office action

Prosecution Timeline

Mar 10, 2023
Application Filed
Mar 23, 2024
Non-Final Rejection — §102, §112
Sep 26, 2024
Response Filed
Jan 30, 2025
Final Rejection — §102, §112
Feb 18, 2025
Response after Non-Final Action
Mar 27, 2025
Request for Continued Examination
Mar 28, 2025
Response after Non-Final Action
May 27, 2025
Non-Final Rejection — §102, §112
Aug 25, 2025
Interview Requested
Sep 25, 2025
Response Filed
Dec 24, 2025
Non-Final Rejection — §102, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12586483
MODULAR CIRCUIT CARD ASSEMBLY FOR ADVANCED TRAINING APPLICATIONS
2y 5m to grant Granted Mar 24, 2026
Patent 12573310
SYSTEMS AND METHODS FOR USING A VOCATIONAL MASK WITH A HYPER-ENABLED WORKER
2y 5m to grant Granted Mar 10, 2026
Patent 12555489
Large Language Model-Enabled Artificial Intelligence-Based Virtual Interactive Reading Assistant
2y 5m to grant Granted Feb 17, 2026
Patent 12542066
SYSTEMS AND METHODS FOR GENERATING PERSONALIZED INTERFACE CONTENT PLANS
2y 5m to grant Granted Feb 03, 2026
Patent 12536920
TRANSFORMER TRAINING LAB
2y 5m to grant Granted Jan 27, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

4-5
Expected OA Rounds
53%
Grant Probability
76%
With Interview (+23.7%)
3y 7m
Median Time to Grant
High
PTA Risk
Based on 755 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month