DETAILED ACTION
Status of Claims
This action is in reply to the communication filed on 22 January, 2026.
Claims 1, 20, 22, 26, 28 and 48 have been amended.
Claim 8 has been cancelled.
Claim 59 has been added.
Claims 1, 2, 5, 7, 11, 12, 14, 15, 17, 19, 20, 22, 24, 26, 28, 47, 48 and 59 are currently pending and have been examined.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 22 January, 2026 has been entered.
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.
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.
Claims 2, 5, 7, 11, 12, 14, 15, 17, 19, 20, 22, 26, 28, 47 and 48 are rejected under 35 U.S.C. 103 as being unpatentable over Levings et al.: (US PGPUB 2017/0209657 A1) in view of Englehard et al.: (US PGPUB 2015/0100335 A1).
The Levings reference has a common assignee with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(1).
CLAIMS 1, 26 and 28
Levings discloses a respiratory therapy system that includes the following limitations:
A method of predicting compliance with a respiratory treatment regimen for a patient, (Levings Abstract); the method comprising:
collecting operational data and usage data from a respiratory pressure therapy device providing a supply of pressurized air at positive pressure through a user interface to the patient during a sleep session; (Levings 0033, 0087 – 0099, 0171 – 0185);
collecting demographic data of the patient; (Levings 0210, 0211); and
predicting compliance with the treatment based on inputting operational data, usage data and demographic data to a machine learning compliance prediction model having a compliance prediction output, wherein the machine learning model is trained from the operational data, usage data, demographic data and compliance data of a population of patients using respiratory pressure therapy devices; (Levings 0040, 0196, 0197, 0199, 0205, 0210, 0218, 0221, 0260 – 0264).
Levings discloses a respiratory therapy system and method that includes collecting operational data and usage data from a respiratory therapy device used by a patient, and patient demographics, and uses a trained machine learning model, such as a neural network, to predict future compliance with the regimen. The model is trained on historical operational, usage, demographic and compliance data from a population of therapy device users.
Levings further teaches the following limitations:
modifying the respiratory treatment regimen based on the determined type of usage data or operational data to increase predicted compliance with the treatment; (Levings 0039 – 0041, 0205, 0271 – 0276); and
communicating with the respiratory pressure therapy device to change operation of the respiratory pressure therapy device in supplying pressurized air to the patient based on the determined type of operational data in response to the modification of the respiratory treatment regimen; (Levings 0040, 0204, 0205, 0232, 0249, 0250).
Levings teaches modifying the treatment regimen to converge on an “optimal” therapy based on the device usage history or other changes to the patient’s profile. For example, the system may determine what actions to take “If leak is high”, or other conditions, and transmit control commands to the device.
With respect to the following limitations:
a compliance prediction output for each of a plurality of days of the treatment; displaying the predicted compliance for each of the plurality of days to show drops of the predicted compliance between days; (Englehard 0015, 0016, 0023, 0024, 0162 – 0166, 0169 – 0171, 0173, 0175, Figure 29, Figure 30).
Levings disclose generating a prediction of future compliance after each treatment session, but does not expressly disclose generating and displaying a prediction for each of a plurality of days. Englehard discloses a patient adherence monitoring system that includes detecting usage of a medical device, providing the data to an external device for analysis and display on a user interface. In particular, Englehard predicts a patient’s future adherence to a treatment protocol based on a patient’s historical adherence. (The terms adherence and compliance have the same meaning in this context.) The level of adherence for past, current or future time periods, such as day in a month, are displayed in a user interface on a client device including drops or improvements from day-to-day. Therefore, it would have been obvious to one of ordinary skill in the art, at the time the invention was filed, to have modified the respiratory therapy system of Levings to have included predicting and displaying treatment compliance for a plurality of days, in accordance with the teachings of Englehard, in order to manage patient compliance trends.
With respect to Claim 26, Levings teaches
A non-transitory computer program product comprising instructions which, when executed by a computer, cause the computer to carry out: the method of Claim 1 (Levings 0121, 0135).
With respect to CLAIM 28, Levings teaches
A system comprising: a respiratory pressure therapy device including a transmitter and an air control device a patient database a network; and a compliance analysis engine (Levings 0040, 0196, 0197, 0199, 0205, 0210, 0218, 0221, 0260 – 0264).
Claim 28 recites system components for executing the method of Claim 1 including a RPT device including a transmitter and flow control, patient database, network and compliance engine. Levings discloses a respiratory therapy system and method that includes the recited components for collecting device operational data and various other data including patient demographics, and uses a trained model, such as a neural network, to predict compliance. The model is trained on historical data from a population of therapy device users.
CLAIMS 2, 5, 7, 11, 12, 14, 15, 17, 19 and 47
The combination of Levings/Englehard discloses the limitations above relative to Claims 1 and 28. Additionally, Levings discloses the following limitations:
sending the compliance prediction to a user device operated by a health care provider associated with the patient or sending the compliance prediction to a user device operated by the patient; (Levings 0200 – 0203);
classifying the patient based on a plurality of classifications of the population of patients wherein the machine learning compliance prediction model includes an output based on the classification of the patient; (Levings 0218);
wherein the machine learning compliance prediction model outputs the prediction each day of the treatment regimen wherein the treatment regimen has a predetermined period of days; (Levings 0171, 0186 – 0193, 0196);
collecting physiological data from a health monitor, wherein the collected physiological data is input to the machine learning compliance prediction model to determine the prediction; wherein the health monitor includes at least one sensor, the at least one sensor selected from one of the group of an audio sensor, a heart rate sensor, a respiratory sensor, a ECG sensor, a photoplethysmography (PPG) sensor, an infrared sensor, an activity sensor, a radio frequency sensor, a SONAR sensor, an optical sensor, a doppler radar motion sensor, a thermometer, an impedance sensor, a piezoelectric sensor, a photoelectric sensor, or a strain gauge sensor; (Levings 0201);
wherein the machine learning compliance prediction model analyzes environmental data related to the patient in determining the prediction; (Levings 0210, 0211);
wherein the machine learning compliance prediction model analyzes demographic data related to the patient in determining the prediction; (Levings 0210, 0211);
further comprising deriving at least one of duration of usage of the respiratory therapy device, leaks of the interface, AHI, or mask type from the collected operational data; (Levings 0186 – 0191);
collecting patient input data from a survey, and wherein the machine learning compliance prediction model analyzes the patient input data in determining the prediction; (Levings 0200, 0212);
a display coupled to the compliance analysis engine, wherein the display displays the compliance prediction of the patient; (Levings 0144).
Levings expressly discloses the features recited in the cited paragraphs.
CLAIMS 20, 22 and 48
The combination of Levings/Englehard discloses the limitations above relative to Claims 1 and 47. Additionally, Englehard the following limitations:
displaying an indication of a compliance prediction of the patient completing the treatment regimen in a day of a calendar showing other days of a period for completing the treatment regimen; displaying an indication of a compliance prediction of the patient completing the treatment regimen in a day of a calendar showing other days of a period for completing the treatment; wherein the calendar shows past days of usage of the respiratory therapy device in compliance with a usage threshold and an indication on a day of a projected compliance period for completing the treatment regimen; (Englehard Figure 30)
Levings does not disclose calendar displays. Englehard discloses displaying a calendar on the user interface of a client device for each day of a user selected treatment period, for example, one month as disclosed (i.e. a period/projected compliance period for completing the treatment regimen). The calendar shows past, current and future days, (i.e. a calendar showing other days of a period for completing the treatment), and various levels of smiley/frowny face (i.e. an indication of compliance prediction) indicating compliance for each past day, or an indication of a compliance prediction for each future day. The calendar shows past usage in compliance with a treatment protocol that determines the amount and timing of treatments (i.e. a usage threshold). Therefore, it would have been obvious to one of ordinary skill in the art, at the time the invention was filed, to have modified the respiratory therapy system of Levings to have included a calendar view of compliance and compliance predictions, in accordance with the teachings of Englehard, in order to manage patient compliance over a period of time.
Claim 24 is rejected under 35 U.S.C. 103 as being unpatentable over Levings et al.: (US PGPUB 2017/0209657 A1) in view of Englehard et al.: (US PGPUB 2015/0100335 A1) in view of Levine et al.: (US PGPUB 2003/0011646 A1).
CLAIM 24
The combination of Levings/Englehard discloses the limitations above relative to Claim 19. With respect to the following limitations:
displaying information relating to a last contact attempt with the patient; (Levine 0153).
Levings discloses transmitting electronic messages to the patient, but does not disclose displaying the last contact attempt. Levine discloses a clinical management system that includes listing patient messages sent by the provider to the patient, including which messages have been read or not read. Therefore, it would have been obvious to one of ordinary skill in the art, at the time the invention was filed, to have modified the respiratory therapy system of Levings to have included a list of messages by date, in accordance with the teachings of Levine, in order to manage patient compliance.
Claim 59 is rejected under 35 U.S.C. 103 as being unpatentable over Levings et al.: (US PGPUB 2017/0209657 A1) in view of Englehard et al.: (US PGPUB 2015/0100335 A1) in view of Applebaum et al.: (US PGPUB 2022/0051773 A1).
CLAIM 59
The combination of Levings/Applebaum discloses the limitations above relative to Claim 1. With respect to the following limitations:
determining a shap value for each type of usage data and each type of operational data; based on the shap values, determining the contribution of each type of usage data and operational data on the predicted compliance with the treatment; determining a type of usage data or operational data that negatively contributes to the predicted compliance from the shap values; (Applebaum 0006 – 0009, 0014, 0021, 0022, 0025, 0041, 0047, 0048, 0050).
Levings discloses a predictive compliance model that uses weighted feature values, or parameters, as inputs; and that has been trained “according to conventional predictor training methods”. (@ 0260 – 0264) The weighting of the parameters may be increased or decreased, based on their importance (i.e. contribution on the predicted compliance), according to a predefined schedule. Levings does not disclose the use of shap values to determine the contribution each data element makes to the compliance prediction. Initially, Examiner asserts that shap values are old and well known. For example, shap values may be used as a feature selection technique to reduce the dimensionality of the input data in order to make the prediction using fewer processing resources “according to conventional predictor training methods”.
Nonetheless, whether shap values may be an Officially Noticed fact or not, Examiner relies on Appelbaum for these features. Applebaum discloses a system and method for managing a patient’s therapy regimen including a machine learning trained model or classifier for predicting future compliance, and adjusting the therapy regimen to improve compliance. In particular, Appelbaum discloses the use of Shapely Additive Explanation values – i.e. shap values – to determine the importance of each data element, and which data element most adversely affects the prediction. Therefore, it would have been obvious to one of ordinary skill in the art, at the time the invention was filed, to have modified the respiratory therapy system of Levings to have included determining shap values of input data, in accordance with the teachings of Applebaum, in order select the data elements having the greatest predictive power.
Response to Arguments
Applicant's arguments filed 22 January, 2026 with respect to the U.S.C. §112 and U.S.C. §101 Rejections have been fully considered and they are persuasive. The rejections have been withdrawn.
Applicant's arguments with respect to the U.S.C. §103 Rejections have been fully considered but they are not persuasive.
The U.S.C. §103 Rejection
Applicant asserts that Levings does not discloses predicting compliance for a plurality of days. Examiner agrees. However, on further search and consideration, a new grounds of rejection in view of Englehard is presented herein.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US PGPUB 2016/0235981 A1 to Southwell et al. discloses a system and method for monitoring medical treatments that includes displaying a monthly calendar made up of days defining a treatment period. Each day shows the treatment usage and a compliance indicator. (see Figure 29, 30 0216 – 0220)
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to John A. Pauls whose telephone number is (571) 270-5557. The Examiner can normally be reached on Mon. - Fri. 8:00 - 5:00 Eastern. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773.
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/JOHN A PAULS/Primary Examiner, Art Unit 3683
Date: 2 March, 2026