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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 December 4, 2025 has been entered.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. AU 2021/050126, filed on February 12, 2021.
Response to Amendment
In the amendment filed on November 7, 2025, the following has occurred: claim(s) 33-34, 41-44, 51, 54-59, 61 have been amended. Now, claim(s) 33-34, 41-44, 47, 51-63 are pending.
Claim Objections
Claim 44 objected to because of the following informalities: “the improvement adjustment” in p. 3, ll. 17. This appears to be a typographical error. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the at least one sleep pattern improvement adjustment”.
Claim 51 objected to because of the following informalities: “the differential equations” in p. 4, ll. 4. This appears to be a typographical error. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the ordinary differential equations”.
Claim 54 objected to because of the following informalities: “the at least one instruction” in p. 5, ll. 5. This appears to be a typographical error. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the at least one device control instruction”.
Claim 59 objected to because of the following informalities: “the improvement adjustment” in p. 6, ll. 6. This appears to be a typographical error. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the at least one sleep pattern improvement adjustment”.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 33-34, 41-44, 47, 51-63 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The newly amended independent claims 33 and 54 recite "at least one sleep pattern improvement adjustment". The Applicant's Specification does not disclose "at least one sleep pattern improvement adjustment", "adjust" and "adjustment" are mentioned three times in the Specification on p. 15, ll. 20, p. 34, ll. 2, and p. 39, ll. 31. However, these recitations do not describe adjustments to "at least one sleep pattern improvement adjustment". The Applicant's Remarks from November 7, 2025 do not recite where in the Specification the support for the newly amended addition of "at least one sleep pattern improvement adjustment" can be found. The Examiner does not acknowledge that the Applicant’s written description describes “at least one sleep pattern improvement adjustment” in a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor.
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.
Claim(s) 33-34, 41-44, 47, 51-63 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 33-34, 41-44, 47, 51: Step 2A Prong One
Claim 33 recite(s)
receiving, data relating to at least one sleep pattern metric;
processing, the data to generate at least one sleep pattern improvement adjustment;
processing, the at least one sleep pattern improvement adjustment to generate at least one device control instruction, cause to implement a device action for facilitating the at least one sleep pattern improvement adjustment
These limitations, as drafted, given the broadest reasonable interpretation, but for the recitation of generic computer components, encompass managing interactions between people (including following rules or instructions), which is a subgrouping of Certain Methods of Organizing Human Activity. For example, but for the “…by a computing system,…”, “…from a remote data acquiring device;” language, the “receiving” function in the context of this claim encompasses a user following instructions to obtain data related to at least one sleep pattern metric. Similarly, but for the “…by a computing system,…”, “…using a model driven recommendation model, wherein the model driven recommendation model uses at least one of a bio-mathematical sleep model and a system of ordinary differential equations based on neurobiological mechanisms;” language, the “processing” function in the context of the claim encompasses a user following instructions to determine at least one sleep pattern improvement adjustment. Finally, but for the “…by a computing system,…”, “…to a remote actuation device…” language, the “processing” function in the context of this claim encompasses a user following instructions to determine at least one device control instruction based on the at least one sleep pattern improvement adjustment. These steps could be accomplished by a person managing medical information to be shown to another person by following rules or instructions, and therefore encompass Certain Methods of Organizing Human Activity.
Claims 34, 41-44, 47, 51 incorporate the abstract idea identified above and recite additional limitations that expand on the abstract idea. For example, claim 34 includes the abstract idea identified above and describes formatting the data to a common data format. Similarly, claims 35, 43, 47, 51 include the abstract idea identified above and further describe determining the at least one sleep pattern improvement adjustment. Similarly, claims 41-42 include the abstract idea identified above and further describe the generic computer components. Finally, claim 44 includes the abstract idea identified above and describes how the at least one sleep pattern improvement adjustment is shown to another user. Such steps encompass Certain Methods of Organizing Human Activity.
Claims 33-34, 41-44, 47, 51: Step 2A Prong Two
This judicial exception is not integrated into a practical application because the remaining
elements amount to no more than general purpose computer components programmed to perform
the abstract idea, and insignificant extra-solution activity.
Claims 34, 41-44, 47, 51, directly or indirectly, recite the following generic computer components, “…by a computing system,…” “…from a remote data acquiring device;”, “…to a remote actuation device…” configured to implement the abstract idea: “Computing device 110 may comprise one or more computers, servers, or other computing devices, and may be a distributed server system or a cloud based computing system in some embodiments. According to some embodiments, computing device 110 may be a smart phone, wearable, laptop, or desktop computer. Processor 112 may comprise one or more microprocessors, central processing units (CPUs), application specific instruction set processors (ASIPs), or other processors capable of reading and executing instruction code.” (See Specification in p. 9, ll. 22-29). As set forth in the 2019 Eligibility Guidance, 84 Fed. Reg. at 55 “merely include[ing] instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
Additionally, the claims recite “…using a model driven recommendation model, wherein the model driven recommendation model uses at least one of a bio-mathematical sleep model and a system of ordinary differential equations based on neurobiological mechanisms;” at a high degree of generality, amount no more than generally linking the abstract idea to a particular technical environment. The recitation is also similar to adding the words “apply it” to the abstract idea. As set forth in MPEP 2106.05(f), merely reciting the words “apply it” or an equivalent, is an example of when an abstract idea has not been integrated into a practical application.
Additionally, the limitation of “displaying, by the computing system, the at least one sleep pattern improvement adjustment to the user;”, “sending, by the computing system, the at least one device control instruction to the remote actuation device, wherein the device action is distinct from the displaying of the sleep pattern improvement adjustment” do not integrate the judicial exception into a practical application because they merely recite insignificant, extra-solution activity of data gathering of the abstract idea.
Claims 33-34, 41-44, 47, 51: Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to
significantly more than the judicial exception because as discussed above with respect to integration into a practical application, the additional elements are recited at a high level of
generality, and the written description indicates that these elements are generic computer
components. Using generic computer components to perform abstract ideas does not provide a
necessary inventive concept. See Alice, 573 U.S. at 223 ("mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.")
Insignificant, extra solution, data gathering activity has been found to not amount to
significantly more than an abstract idea (See MPEP 2106.05(g)). Therefore, whether considered
alone or in combination, the additional elements do not amount to significantly more than the
abstract idea.
Additionally, generally linking the abstract idea to a particular technological environment does not amount to significantly more than the abstract idea (See MPEP 2016.05(h) and Affinity Labs of Texas v. DirectTV, LLC, 838 F.3d 1253, 120 USP12d 1201 (Fed. Cir. 2016)). The claims are not patent eligible.
Claims 52-53 recite the same functions as claim 33, but in non-transitory machine-readable medium and apparatus form.
The addition of “one or more processors, cause an electronic apparatus” in independent claim 52, and “processing circuitry and a machine-readable medium storing non-transitory instructions” in independent claim 53 amount to no more than general purpose computer components programmed to perform the abstract idea. (“Computing device 110 may comprise one or more computers, servers, or other computing devices, and may be a distributed server system or a cloud based computing system in some embodiments. According to some embodiments, computing device 110 may be a smart phone, wearable, laptop, or desktop computer. Processor 112 may comprise one or more microprocessors, central processing units (CPUs), application specific instruction set processors (ASIPs), or other processors capable of reading and executing instruction code.” (See Specification in p. 9, ll. 22-29)).
Claims 54-61: Step 2A Prong One
Claim 54 recite(s)
receiving, data relating to at least one sleep pattern metric;
processing, the data to generate at least one sleep pattern improvement adjustment;
processing, the at least one sleep pattern improvement adjustment to generate at least one device control instruction
These limitations, as drafted, given the broadest reasonable interpretation, but for the recitation of generic computer components, encompass managing interactions between people (including following rules or instructions), which is a subgrouping of Certain Methods of Organizing Human Activity. For example, but for the “…by a computing system,…”, “…from a remote data acquiring device;” language, the “receiving” function in the context of this claim encompasses a user following instructions to obtain data related to at least one sleep pattern metric. Similarly, but for the “…by a computing system,…” language, the “processing” function in the context of the claim encompasses a user following instructions to determine at least one sleep pattern improvement adjustment using a decision tree. Finally, but for the “…by a computing system,…”, “…to a remote actuation device…” language, the “processing” function in the context of this claim encompasses a user following instructions to determine at least one device control instruction based on the at least one sleep pattern improvement adjustment. These steps could be accomplished by a person managing medical information to be shown to another person by following rules or instructions, and therefore encompass Certain Methods of Organizing Human Activity.
Claims 55-61 incorporate the abstract idea identified above and recite additional limitations that expand on the abstract idea. For example, claim 55 includes the abstract idea identified above and describes formatting the data to a common data format. Similarly, claims 56-57 include the abstract idea identified above and further describe the generic computer components. Similarly, claims 58-60 include the abstract idea identified above and further describe determining the at least one sleep improvement adjustment. Finally, claim 61 includes the abstract idea identified above and describes the sleep pattern improvement adjustment that ordinary differential equations are based on. Such steps encompass Certain Methods of Organizing Human Activity.
Claims 54-61: Step 2A Prong Two
This judicial exception is not integrated into a practical application because the remaining
elements amount to no more than general purpose computer components programmed to perform
the abstract idea, and insignificant extra-solution activity.
Claims 54-61, directly or indirectly, recite the following generic computer components, “…a remote data acquiring device;” configured to implement the abstract idea: “Computing device 110 may comprise one or more computers, servers, or other computing devices, and may be a distributed server system or a cloud based computing system in some embodiments. According to some embodiments, computing device 110 may be a smart phone, wearable, laptop, or desktop computer. Processor 112 may comprise one or more microprocessors, central processing units (CPUs), application specific instruction set processors (ASIPs), or other processors capable of reading and executing instruction code.” (See Specification in p. 9, ll. 22-29). As set forth in the 2019 Eligibility Guidance, 84 Fed. Reg. at 55 “merely include[ing] instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
Additionally, the claims recite “…to a remote actuation device, to cause the remote actuation device to implement a device action for facilitating the at least one sleep pattern improvement adjustment;”, “…using a decision tree” at a high degree of generality, amount no more than generally linking the abstract idea to a particular technical environment. The recitation is also similar to adding the words “apply it” to the abstract idea. As set forth in MPEP 2106.05(f), merely reciting the words “apply it” or an equivalent, is an example of when an abstract idea has not been integrated into a practical application.
Additionally, the limitation of “displaying, by the computing system, the at least one sleep pattern improvement adjustment to the user;”, “sending, by the computing system, the at least one instruction to the remote actuation device, wherein the device action is distinct from the displaying of the sleep improvement adjustment” do not integrate the judicial exception into a practical application because they merely recite insignificant, extra-solution activity of data gathering of the abstract idea.
Claims 54-61: Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to
significantly more than the judicial exception because as discussed above with respect to integration into a practical application, the additional elements are recited at a high level of
generality, and the written description indicates that these elements are generic computer
components. Using generic computer components to perform abstract ideas does not provide a
necessary inventive concept. See Alice, 573 U.S. at 223 ("mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.")
Insignificant, extra solution, data gathering activity has been found to not amount to
significantly more than an abstract idea (See MPEP 2106.05(g)). Therefore, whether considered
alone or in combination, the additional elements do not amount to significantly more than the
abstract idea.
Additionally, generally linking the abstract idea to a particular technological environment does not amount to significantly more than the abstract idea (See MPEP 2106.05(h) and Affinity Labs of Texas v. DirectTV, LLC, 838 F.3d 1253, 120 USP12d 1201 (Fed. Cir. 2016)). The claims are not patent eligible.
Claims 62-63 recite the same functions as claim 33, but in non-transitory machine-readable medium and apparatus form.
The addition of “one or more processors, cause an electronic apparatus” in independent claim 62, and “processing circuitry and a machine-readable medium storing non-transitory instructions” in independent claim 53 amount to no more than general purpose computer components programmed to perform the abstract idea. (“Computing device 110 may comprise one or more computers, servers, or other computing devices, and may be a distributed server system or a cloud based computing system in some embodiments. According to some embodiments, computing device 110 may be a smart phone, wearable, laptop, or desktop computer. Processor 112 may comprise one or more microprocessors, central processing units (CPUs), application specific instruction set processors (ASIPs), or other processors capable of reading and executing instruction code.” (See Specification in p. 9, ll. 22-29)).
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.
Claims 54, 56-60, 62-63 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being unpatentable over Proud (U.S. Patent Publication No. 10,004,451).
As per independent claim 54, Proud teaches a method for improving sleep patterns in users, the method comprising:
receiving, by a computing system, data relating to at least one sleep pattern metric from a remote data acquiring device (See col. 12, ll. 23-32: The Cloud System includes three subsystems which can communicate asynchronously, this includes one or more a synchronization system that is responsible for receiving data uploaded by monitor device, verifying authenticity and integrity of the data uploaded, sending commands to monitor device, which the Examiner is interpreting receiving data to encompass receiving data relating to at least one sleep pattern metric (See col. 8, ll. 62-67, col. 9, ll. 35: User monitoring can include sleep, including but not limited to: sleep patterns, type of sleep etc.), and the monitor device to encompass a remote data acquiring device);
processing, by the computing system, the data to generate at least one sleep pattern improvement adjustment (See col. 58, ll. 60-67, col. 59, ll. 1-49: The system, motion detection device, and cloud system automates parts of the reaction aspects of cognitive behavior therapy (CBT), the system, motion detection device and cloud system can be used to provide solutions to a person’s sleep issues, which the Examiner is interpreting examples (i)-(XVI) to encompass at least one sleep pattern improvement adjustment) using a decision tree (See col. 56, ll. 1-6: In one embodiment stepped care models of treatment are utilized using system and/or Cloud System, matching the appropriate level of intervention, starting with the least restrictive and most effective, enhances treatment outcomes, controls healthcare costs, and helps allocate scarce mental health resources more effectively, which the Examiner is interpreting the stepped care models to encompass the decision tree as the Applicant’s Specification on p. 6 and 33 recites “In some embodiments, processing the data to generate at least one sleep pattern recommendation comprises using a decision tree.” and “At step 1140, processor112 then executes modules160, 170 and 180 to perform a shift work management process to generate recommendations and implementations for the user. The shift work management process may include using a decision tree informed by best practice circadian principles in some embodiments.”);
processing, by the computing system, the at least one sleep pattern improvement adjustment to generate at least one device control instruction to a remote actuation device, to cause the remote actuation device to implement a device action for facilitating the at least one sleep pattern improvement adjustment (See col. 11, ll. 44-67, col. 12, ll. 1-4: The monitor device receives commands and data from the Cloud System after each upload, the monitor device can communicate with a person’s mobile device, the mobile device can send command information directed to one or more of: activating sensors, including but not limited to light, sound and the like, which the Examiner is interpreting the sensors to encompass a remote actuation device, command information directed to activating sensors to encompass at least one device control instruction);
displaying, by the computing system, the at least one sleep pattern improvement adjustment to the user (See col. 59, ll. 4-53: The system, motion detection device and cloud system are used to provide a message regarding relaxation tools and/or reschedule worry-times to earlier in the day, which the Examiner is interpreting the message to encompass displaying to the user, and interpreting relaxation tools and/or reschedule worry-times to earlier in the day to encompass the at least one sleep pattern improvement adjustment); and
sending, by the computing system, the at least one device control instruction to the remote actuation device,
wherein the device action is distinct from the displaying of the sleep pattern improvement adjustment (See col. 11, ll. 44-67, col. 12, ll. 1-4: The monitor device receives commands and data from the Cloud System after each upload, the monitor device can communicate with a person’s mobile device, the mobile device can send command information directed to one or more of: activating sensors, including but not limited to light, sound and the like, which the Examiner is interpreting the sensors to encompass a remote actuation device, command information directed to activating sensors to encompass at least one device control instruction.)
Claim(s) 62-63 mirror claim 33 only within (a) different statutory category/categories, and is rejected for the same reason as claim 33.
The addition of “…when executed by one or more processors, cause an electronic apparatus to perform…” in independent claim 62 is encompassed by Proud in col. 7, ll. 14-29: The engine will typically include software instructions that are stored in non-volatile memory (also referred to as secondary memory) and a processor with instructions to execute the software.
The addition of “…processing circuitry …” in independent claim 63 is encompassed by Proud in col. 7, ll. 14-29: The engine will typically include software instructions that are stored in non-volatile memory (also referred to as secondary memory) and a processor with instructions to execute the software.
As per claim 56, Proud discloses the method of claim 54 as described above. Proud further teaches wherein the remote data acquiring device comprises at least one of a home monitoring hub, a car monitoring hub, a recovery system, a wearable device, a smart cup, an augmented reality device, a virtual reality device, a biological data device, a bed partner input device, an emotion detection system, a manual entry system, a light sensor and a work place monitoring hub (See col. 59, ll. 54-67: The monitoring device can include light, sound temperature and humidity sensors, a motion/movement gesture detection device, which the Examiner is interpreting the remote data acquiring device to encompass a biological data device.)
As per claim 57, Proud discloses the method of claim 54 as described above. Proud further teaches wherein the remote actuation device comprises at least one of a change coaching system, a calendar input system, an augmented reality device, a virtual reality device, an engagement system, a biological feedback system, a home automation system, a communication system, a behaviour recommendation system, a long term connection system, and a car (See col. 32, ll. 49-65: The features can be implemented on a computer system, which the Examiner is interpreting to encompass a communication system as the components of the system can be connected by any form or medium of digital data communication such as a communication network.)
As per claim 58, Proud discloses the method of claim 54 as described above. Proud further teaches wherein processing the data to generate at least one sleep pattern improvement adjustment for presenting to the user is performed based on the determined value of the sleep pattern metric (See col. 32, ll. 49-54, col. 57, ll. 65-67, col. 58, ll. 1-67, col. 59, ll. 1-49: To provide interaction with a user, the features can be implemented on a computer having a display device for displaying information to the user and the motion detection device can determine changes to a person's sleep habits, the data can be used to identify a message to be sent to the person due to the sleep habits, which the Examiner is interpreting sleep habits (latency, consistency of bed time) to encompass the sleep pattern metric.)
As per claim 59, Proud discloses the method of claim 54 as described above. Proud further teaches wherein displaying the at least one sleep pattern improvement adjustment to the user is performed sequentially or alongside a degree of effectiveness of the at least one sleep pattern improvement adjustment (See Fig. 54 and col. 7, ll. 9-10: Cause a graphical display to display one or more of the selected activities in an arrangement that is based on the scores of the selected activities relevant to one another.)
As per claim 60, Proud discloses the method of claim 54 as described above. Proud further teaches further comprising deriving at least one sleep pattern parameter from the data (See col. 32, ll. 49-54, col. 57, ll. 65-67, col. 58, ll. 1-67, col. 59, ll. 1-49: To provide interaction with a user, the features can be implemented on a computer having a display device for displaying information to the user and the motion detection device can determine changes to a person's sleep habits, the data can be used to identify a message to be sent to the person due to the sleep habits which the Examiner is interpreting sleep habits (latency, consistency of bed time) to encompass at least one sleep pattern parameter.)
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.
Claims 33, 41-44, 47, 52-53 are rejected under 35 U.S.C. 103 as being unpatentable over Proud (U.S. Patent Publication No. 10,004,451) in view of D’Alessandro et al. (U.S. Patent Publication No. 10,398,389).
As per independent claim 33, Proud teaches a computer-implemented method for improving sleep patterns in users, the method comprising:
receiving, by a computing system, data relating to at least one sleep pattern metric from a remote data acquiring device (See col. 12, ll. 23-32: The Cloud System includes three subsystems which can communicate asynchronously, this includes one or more a synchronization system that is responsible for receiving data uploaded by monitor device, verifying authenticity and integrity of the data uploaded, sending commands to monitor device, which the Examiner is interpreting receiving data to encompass receiving data relating to at least one sleep pattern metric (See col. 8, ll. 62-67, col. 9, ll. 35: User monitoring can include sleep, including but not limited to: sleep patterns, type of sleep etc.), and the monitor device to encompass a remote data acquiring device);
processing, by the computing system, the at least one sleep pattern improvement adjustment to generate at least one device control instruction to a remote actuation device, to cause the remote actuation device to implement a device action for facilitating the at least one sleep pattern improvement adjustment (See col. 11, ll. 44-67, col. 12, ll. 1-4: The monitor device receives commands and data from the Cloud System after each upload, the monitor device can communicate with a person’s mobile device, the mobile device can send command information directed to one or more of: activating sensors, including but not limited to light, sound and the like, which the Examiner is interpreting the sensors to encompass a remote actuation device, command information directed to activating sensors to encompass at least one device control instruction);
displaying, by the computing system, the at least one sleep pattern improvement adjustment to the user (See col. 59, ll. 4-53: The system, motion detection device and cloud system are used to provide a message regarding relaxation tools and/or reschedule worry-times to earlier in the day, which the Examiner is interpreting the message to encompass displaying to the user, and interpreting relaxation tools and/or reschedule worry-times to earlier in the day to encompass the at least one sleep pattern improvement adjustment); and
sending, by the computing system, the at least one device control instruction to the remote actuation device,
wherein the device action is distinct from the displaying of the sleep pattern improvement adjustment (See col. 11, ll. 44-67, col. 12, ll. 1-4: The monitor device receives commands and data from the Cloud System after each upload, the monitor device can communicate with a person’s mobile device, the mobile device can send command information directed to one or more of: activating sensors, including but not limited to light, sound and the like, which the Examiner is interpreting the sensors to encompass a remote actuation device, command information directed to activating sensors to encompass at least one device control instruction.)
While Proud discloses the method as described above, Proud may not explicitly teach processing, by the computing system, the data to generate at least one sleep pattern improvement adjustment using a model driven recommendation model, wherein the model driven recommendation model uses at least one of a bio-mathematical sleep model and a system of ordinary differential equations based on neurobiological mechanisms.
D’Alessandro teaches a method for processing, by the computing system, the data to generate at least one sleep pattern improvement adjustment (See col. 6, ll. 60-67: The body simulation module therefore can provide quantitative, scientific backing for external applications to recommend behavioral changes and inform individuals to make educated health decisions, which the Examiner is interpreting recommend behavioral changes to encompass at least one sleep pattern improvement adjustment (col. 6, ll. 14-25: the health and body simulation system generally, also may allow for the manual entry of data including, for example, lifestyle or user information such as type, intensity and duration of exercise, sleep patterns, gender, height, weight, and the like)) using a model driven recommendation model (See col. 7, ll. 1-10: The body simulation module can be configured to allow clinicians to proactively model the relationships between body subcomponents to understand treatment, which the Examiner is interpreting the body simulation module to encompass a model driven recommendation model (col. 7, ll. 11-29)), wherein the model driven recommendation model uses at least one of a bio-mathematical sleep model and a system of ordinary differential equations based on neurobiological mechanisms (See col. 8, ll. 54-67, col. 9, ll. 1-42: A model simulation is generated with the current parameter set, for example, once the model is uniquely defined by the values assigned to parameters, the model can be simulated by solving the set of differential algebraic equations, or the like, that defines the model as embodied in the modules and the interconnections of the modules that describe the biological system being modeled, which the Examiner is interpreting the set of differential algebraic equations to encompass a system of ordinary differential equations based on neurobiological mechanisms as the health and body simulation can be used to model various health scenarios, which can include specific biological functions (col. 7, ll. 12-19), and the model to encompass one of a bio-mathematical sleep model.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the method of Proud to include processing, by the computing system, the data to generate at least one sleep pattern improvement adjustment using a model driven recommendation model, wherein the model driven recommendation model uses at least one of a bio-mathematical sleep model and a system of ordinary differential equations based on neurobiological mechanisms as taught by D’Alessandro. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Proud with D’Alessandro with the motivation of providing an improved physiological health and body simulation system that can provide a platform for a wide range of applications (See Detailed Description of the Preferred Embodiments of D’Alessandro in col. 5, ll. 49-63).
Claim(s) 52-53 mirror claim 33 only within (a) different statutory category/categories, and is rejected for the same reason as claim 33.
The addition of “…when executed by one or more processors, cause an electronic apparatus to perform…” in independent claim 52 is encompassed by Proud in col. 7, ll. 14-29: The engine will typically include software instructions that are stored in non-volatile memory (also referred to as secondary memory) and a processor with instructions to execute the software.
The addition of “…processing circuitry …” in independent claim 53 is encompassed by Proud in col. 7, ll. 14-29: The engine will typically include software instructions that are stored in non-volatile memory (also referred to as secondary memory) and a processor with instructions to execute the software.
As per claim 41, Proud/D’Alessandro discloses the method of claim 33 as described above. Proud further teaches wherein the remote data acquiring device comprises at least one of a home monitoring hub, a car monitoring hub, a recovery system, a wearable device, a smart cup, an augmented reality device, a virtual reality device, a biological data device, a bed partner input device, an emotion detection system, a manual entry system, a light sensor and a work place monitoring hub (See col. 59, ll. 54-67: The monitoring device can include light, sound temperature and humidity sensors, a motion/movement gesture detection device, which the Examiner is interpreting the monitoring device to encompass a biological data device.)
As per claim 42, Proud/D’Alessandro discloses the method of claim 33 as described above. Proud further teaches wherein the remote actuation device comprises at least one of a change coaching system, a calendar input system, an augmented reality device, a virtual reality device, an engagement system, a biological feedback system, a home automation system, a communication system, a behaviour recommendation system, a long term connection system, and a car (See col. 32, ll. 49-65: The features can be implemented on a computer system, which the Examiner is interpreting to encompass a communication system as the components of the system can be connected by any form or medium of digital data communication such as a communication network.)
As per claim 43, Proud/D’Alessandro discloses the method of claim 33 as described above. Proud further teaches wherein processing the data to generate at least one sleep pattern improvement adjustment for presenting to the user is performed based on the determined value of the sleep pattern metric (See col. 32, ll. 49-54, col. 57, ll. 65-67, col. 58, ll. 1-67, col. 59, ll. 1-49: To provide interaction with a user, the features can be implemented on a computer having a display device for displaying information to the user and the motion detection device can determine changes to a person's sleep habits, the data can be used to identify a message to be sent to the person due to the sleep habits, which the Examiner is interpreting sleep habits (latency, consistency of bed time) to encompass the sleep pattern metric.)
As per claim 44, Proud/D’Alessandro discloses the method of claim 33 as described above. Proud further teaches wherein displaying the at least one sleep pattern improvement adjustment to the user is performed sequentially or alongside a degree of effectiveness of the at least one sleep pattern improvement adjustment (See Fig. 54 and col. 7, ll. 9-10: Cause a graphical display to display one or more of the selected activities in an arrangement that is based on the scores of the selected activities relevant to one another.)
As per claim 47, Proud/D’Alessandro discloses the method of claim 33 as described above. Proud further teaches further comprising deriving at least one sleep pattern parameter from the data (See col. 32, ll. 49-54, col. 57, ll. 65-67, col. 58, ll. 1-67, col. 59, ll. 1-49: To provide interaction with a user, the features can be implemented on a computer having a display device for displaying information to the user and the motion detection device can determine changes to a person's sleep habits, the data can be used to identify a message to be sent to the person due to the sleep habits which the Examiner is interpreting sleep habits (latency, consistency of bed time) to encompass at least one sleep pattern parameter.)
Claim 34 is rejected under 35 U.S.C. 103 as being unpatentable over Proud (U.S. Patent Publication No. 10,004,451) in view of D’Alessandro et al. (U.S. Patent Publication No. 10,398,389) in further view of Connelly (U.S. Pre-Grant Patent Publication No. 2019/0065692).
As per claim 34, Proud/D’Alessandro discloses the method of claim 33 as described above. Proud/D’Alessandro may not explicitly teach further comprising pre-processing the data received from the remote data acquiring device to format the data to a common data format.
Connelly teaches a method further comprising pre-processing the data received from the first remote device to format the data to a common data format (See Paragraphs [0064]-[0065]: This normalization of health data creates a unique and universal health model that will allow for homogenized data for both internal and external data sets, creating a standard measurement and formula for health data, which the Examiner is interpreting the data scoring to encompass pre-processing.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the method of Proud/D’Alessandro to include pre-processing the data received from the remote data acquiring device to format the data to a common data format as taught by Connelly. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Proud/D’Alessandro with Connelly with the motivation of improve individual health quality (See Background of Invention of Connelly in Paragraph [0006]).
Claim 51 is rejected under 35 U.S.C. 103 as being unpatentable over Proud (U.S. Patent Publication No. 10,004,451) in view of D’Alessandro et al. (U.S. Patent Publication No. 10,398,389) in further view of Olivier et al. (U.S. Pre-Grant Patent Publication No. 2017/0209103).
As per claim 51, Proud/D’Alessandro discloses the method of claim 33 as described above. Proud/D’Alessandro may not explicitly teach wherein the ordinary differential equations are based on neurobiological mechanisms of sleep and circadian regulation.
Olivier teaches a method wherein the ordinary differential equations are based on neurobiological mechanisms of sleep and circadian regulation (See Paragraphs [0024]-[0026]: Examples of ODE models with shared variables that are combined to construct virtual physiological systems include, but are not limited to, models of cardiovascular systems, cardiopulmonary systems, cellular respiratory system, and database metrics, biological metrics and demographic data serve as input to enable probabilistic modelling of user physiology and behaviour by utilizing stochastic models such as Hidden Markov models (HMM) and/or exhaustive simulations in parallel with predictive ODE models.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the method of Proud/D’Alessandro to include the ordinary differential equations are based on neurobiological mechanisms of sleep and circadian regulation as taught by Olivier. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Proud/D’Alessandro with Olivier with the motivation of providing relevant inferences and predictions computed from limited data streams (See Background of Invention of Olivier in Paragraph [0006]).
Claim 55 is rejected under 35 U.S.C. 103 as being unpatentable over Proud (U.S. Patent Publication No. 10,004,451) in view of Connelly (U.S. Pre-Grant Patent Publication No. 2019/0065692).
As per claim 55, Proud discloses the method of claim 54 as described above. Proud may not explicitly teach further comprising pre-processing the data received from the remote data acquiring device to format the data to a common data format.
Connelly teaches a method further comprising pre-processing the data received from the remote data acquiring device to format the data to a common data format (See Paragraphs [0064]-[0065]: This normalization of health data creates a unique and universal health model that will allow for homogenized data for both internal and external data sets, creating a standard measurement and formula for health data, which the Examiner is interpreting the data scoring to encompass pre-processing.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the method of Proud to include pre-processing the data received from the remote data acquiring device to format the data to a common data format as taught by Connelly. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Proud with Connelly with the motivation of improve individual health quality (See Background of Invention of Connelly in Paragraph [0006]).
Claim 61 is rejected under 35 U.S.C. 103 as being unpatentable over Proud (U.S. Patent Publication No. 10,004,451) in view of Olivier et al. (U.S. Pre-Grant Patent Publication No. 2017/0209103).
As per claim 61, Proud discloses the method of claims 54 and 60 as described above. Proud may not explicitly teach wherein the sleep pattern improvement adjustment is generated using differential equations based on neurobiological mechanisms of sleep and circadian regulation.
Olivier teaches a method wherein the sleep pattern improvement adjustment is generated using differential equations based on neurobiological mechanisms of sleep and circadian regulation (See Paragraphs [0024]-[0026]: Examples of ODE models with shared variables that are combined to construct virtual physiological systems include, but are not limited to, models of cardiovascular systems, cardiopulmonary systems, cellular respiratory system, central nervous systems, and database metrics, biological metrics and demographic data serve as input to enable probabilistic modelling of user physiology and behaviour by utilizing stochastic models such as Hidden Markov models (HMM) and/or exhaustive simulations in parallel with predictive ODE models, and the Examiner is interpreting central nervous systems to encompass neurobiological mechanisms of sleep and circadian regulation.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the method of Proud to include the sleep pattern improvement adjustment is generated using differential equations based on neurobiological mechanisms of sleep and circadian regulation as taught by Olivier. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Proud with Olivier with the motivation of providing relevant inferences and predictions computed from limited data streams (See Background of Invention of Olivier in Paragraph [0006]).
Response to Arguments
In the Remarks filed on November 7, 2025, the Applicant argues that the newly amended and/or added claims overcome the Claim Objection(s), 35 U.S.C. 112(b) rejection(s), 35 U.S.C. 101 rejection(s), 35 U.S.C. 102 rejection(s), and 35 U.S.C. 103 rejection(s). The Examiner acknowledges that the newly added and/or amended claims overcome the previous Claim Objection(s), 35 U.S.C. 112(b) rejection(s). However, the Examiner does not acknowledge that the newly added and/or amended claims overcome the newly added Claim Objection(s), the newly added 35 U.S.C. 112(a) rejection(s), 35 U.S.C. 101 rejection(s), 35 U.S.C. 102 rejection(s), and 35 U.S.C. 103 rejection(s).
The Applicant argues that:
(1) the Examiner rejects claims 33-34, 41-44, 47, and 51-63 under 35 U.S.C. §101 as being directed to a judicial exception without reciting significantly more than the exception. The Examiner posits that the claim covers methods of managing interactions between people, which is a subgrouping of Certain methods of Organizing Human Activity. Specifically, the Examiner asserts that that claimed method could be accomplished by a person managing medical information to be shown to another person by following rules and instructions. The amended independent claims are directed to a practical application and are not "methods of organizing human activity." The present invention is directed to improvements to a conventional field of technology, namely, sleep management techniques for monitoring and controlling sleep patterns. As noted in the Background Section of the application, many employees are permanently assigned to working overnight or alternating shifts, particularly in industries such a nursing, mining, and transport. Overnight shift work has been shown to be a risk factor for health problems by disrupting circadian rhythms, which may increase the probability of developing cardiovascular disease, cognitive impairment, diabetes, and obesity, among other conditions. Furthermore, overnight shift work also contributes to emotional and mental strains. Conventional sleep management techniques are rudimentary at best and tend to be ineffective for the vast majority of people. For example, as noted in the current specification, conventional sleep scheduling systems exist, but require the user to input shifts manually every time, and do not automatically upload, update, and share shift schedules, or provide coaching support for sleep, mood, or alertness. Sleep, mood and alertness are three important areas that are commonly affected by overnight shift work schedules. Furthermore, conventional sleep pattern management systems tend to require tactile interaction with a mobile phone, tablet, or computer. They do not integrate with other devices like wearables or smart home devices. As a result, inputting information about shift schedules and life commitments manually every time can be arduous, and the input information can be inaccurate. Improvements to this field of technology would provide shift workers with a sleep pattern management tool that offers them help in the form of instructions or recommendations that assist them in dealing with their unconventional working hours and improve their recovery time for working shifts, so as to avoid shift work sleep disorders and to assist shift workers with raising their mood and alertness levels for family and work requirements. In particular, it would be helpful to provide shift workers with personalized recommendations. The present invention thus improves upon this conventional field of technology by employing data gathering techniques that take into account the user's responses to an on-boarding questionnaire or survey and then recommending improvement adjustments. Some embodiments relate to systems and methods for reducing the answer infidelity of user responses to such a questionnaire or survey, to improve the accuracy of the algorithm outcome and in tum the effectiveness of the recommendations that are generated for the user. The system and method of the present invention can also rank a set of recommendations provided to a user based on a profile of that user. In particular, some embodiments relate to systems and methods for ranking a set of recommendations for providing to a user relating to shift work and sleep patterns. Further, the present invention can provide users with assistance during shift work based on received data, including subjective and objective data.
(2) the Examiner characterizes the claims as "managing interactions between people," allegedly achievable by a person who "manually obtains data", "manually determines" a recommendation, and "manually shows" it. Without conceding the correctness of this characterization, Applicant submits that this characterization does not fit currently amended claim 33 (and claim 54) under the broadest reasonable interpretation standard. Specifically, Applicant submits that the claims are directed to specific neurobiology-based computations and requires that improvement adjustments be generated using a model-driven recommendation model employing at least one of a bio-mathematical sleep model and a system of ODEs based on neurobiological mechanisms. This is not a generic "apply it" instruction; it confines the computation to sleep/circadian neurobiology implemented via ODEs/biomathematical modeling, and serves to improve upon the conventional field of sleep related technology. The present invention also provides for mandatory control-instruction generation and actuation. Specifically, the system and method process the improvement adjustment into a device control instruction that is addressed and sent to a remote actuation device, and requires that the device implement a device action that is expressly "distinct from the displaying" of the improvement adjustment. Further, the mere display of a recommendation is not an "actuation" as claimed, and the claims change external state (e.g., turning smart lights off at 8 pm, advancing a calendar entry to facilitate an earlier routine, adjusting thermostat/vehicle settings). This is post-solution control, not data gathering or mere presentation. Still further, the claimed system and method provides for a closed-loop automated control system. The ordered combination includes: (i) neurobiology-grounded modeling [Wingdings font/0xE0] (ii) treatment computation [Wingdings font/0xE0] (iii) control instruction [Wingdings font/0xE0] (iv) non-display device action, performed by a "computing system" integrates the recited computation into a practical application that alters the user's environment/schedule to implement sleep treatment. Accordingly, under Step 2A Prong One the claims are not directed to a judicial exception as characterized, and under Step 2A Prong Two they are, in any event, integrated into a practical application. Under Step 2B, the ordered combination is not conventional: none of the cited art shows this pipeline culminating in a device action distinct from display. Further, to the extent that a judicial exception is present in the claims, the judicial exception is set forth in a practical application;
(3) Applicant also notes that the recent Desjardins decision issued by Director Squires directly bears upon this case. In the Desjardins decision, Director Squires deemed the claims, which were directed to a system that incorporated machine learning aspects, to integrate the exception into a practical application (the use of AI reduced system complexity and storage capacity requirements). In reaching this decision, Director Squires counseled that"... excluding AI innovations from patent protection in the United States jeopardizes America's leadership in this critical emerging technology. Yet, under the panel's reasoning, many AI innovations are potentially unpatentable - even if they are adequately described and non-obvious - because the panel essentially equated any machine learning with an unpatentable "algorithm" and the remaining additional elements as "generic computer components Examiners and panels should not evaluate claims at such a high level of generality." The Desjardins decision also noted, importantly, that "[a]t the same time, the claims at issue stand rejected under §103. This case demonstrates that §§102, 103 and 112 are the traditional and appropriate tools to limit patent protection to its proper scope. These statutory provisions should be the focus of examination." In light of the above, Applicant respectfully requests that the Examiner reconsider and withdraw the 35 U.S.C. §101 rejection of the claims;
(4) Applicant respectfully submits that the Proud reference does not anticipate amended claim 54 (nor amended claim 33). The Examiner maps Proud's messages/graphical displays to both sleep pattern recommendation and resulting device implementation. However, Proud fails to teach or suggest all of the features of the amended claims, which require:
a computed sleep pattern improvement adjustment (decision tree in claim 54; neurobiology-based ODE/biomathematical model in claim 33);
generating from that adjustment a device control instruction; and
a resulting device action that is distinct from display.
Proud’s "message to the person" is, by definition, a display. It is not a "device action distinct from the displaying of the sleep pattern improvement adjustment". Proud also does not disclose transforming a computed treatment into a control instruction addressed to a remote actuation device that then acts (e.g., calendar write; light/thermostat/vehicle control). For at least these reasons, Proud fails to anticipate the amended claims. With respect to claim 54's decision tree, the Examiner equates Proud’s "stepped-care" treatment framework with an algorithmic decision tree that outputs an improvement adjustment which is then operationalized into device control actions. Stepped-care is a clinical tiering concept; it is not disclosure of a decision-node/branching inference engine feeding a control-instruction pipeline. For at least these additional reasons, Proud does not anticipate claim 54. As such, Applicant respectfully urges the Examiner to reconsider and withdraw the 35 U.S.C. §102 rejection of the claims;
(5) Applicant respectfully notes that the combination of the Proud and D' Alessandro references do not render obvious the claimed invention. As an initial matter, Applicant wishes to note that the Examiner's repeated use of the term "encompass" in regard to alleged disclosures in the cited art is evidence that these documents do not clearly disclose, teach, or suggest the claimed features. For example, the Examiner states in regard to an alleged feature of Proud: "The motion detection device can determine changes to a person's sleep habits, the data can be used to identify a message to be sent to the person due to the sleep habits, which the Examiner is interpreting the sent message to encompass displaying the at least one sleep pattern recommendation to the user" (emphasis added). If a prior art citation discloses a broad concept, feature, or category (such as a sent message), it is not permissible to consider such a broad disclosure as a disclosure of all specific elements which could possibly fall within, or be "encompassed" by, the broad disclosure (such as a sleep pattern recommendation). Notwithstanding this impermissible approach to prior art citation analysis, we provide the below arguments. The Examiner turns to D' Alessandro to supply the "model-driven" and "ODE" aspects. Applicant notes that the alleged Examiner combination still omits selected claim requirements and changes the principle of operation of the invention:
1. Right domain and role of the model. Claim 33's model is a sleep/circadian biomathematical/neurobiology-based ODE model that produces an individual improvement adjustment. D' Alessandro is a generic health/body simulation platform (population-level/clinical planning). It neither operationalizes circadian/sleep ODEs nor generates forward-looking sleep improvement adjustments for individual-level solutions.
2. Recommendation-to-actuation pipeline. Even if one borrowed a generic ODE reference from D' Alessandro, the combination still lacks specificity as well as processing the computed improvement adjustment into device control instructions and causing a remote actuation device to perform a device action distinct from display.
3. Motivation/rationale. The articulated rationale ("provide an improved platform") is result-oriented and does not explain why a person of ordinary skill in the art would convert a clinical simulation tool into an individualized, real-time circadian control system that commands external devices to act. That is a change in purpose and principle of operation of the cited art.
Accordingly, Applicant submits that the combination of the teachings of the Proud and D'Alessandro references does not teach or suggest the claimed closed-loop neurobiology-grounded modeling and actuation pipeline. As such, the 35 U.S.C. §103 rejection of claim 33 should be reconsidered and withdrawn;
(6) with regard to claims 51 and 61, Applicant notes that the Olivier reference provides for a discussion of ODEs concerns virtual physiological systems and predictive inference from limited signals. The reference does not disclose sleep/circadian neurobiology-based ODE modeling that produces an improvement adjustment which is then processed into control instructions culminating in a non-display device action as claimed. Adding Olivier's general ODE discussion to the teachings of the other references still does not remedy the factual deficiencies of the Prod and D' Alessandro references. In view of the above amendments and arguments, Applicant believes that the pending application is in condition for allowance.
In response to argument (1), the Examiner does not find the Applicant’s argument(s) persuasive. The Examiner maintains that the Applicant’s amended claims are directed to Certain methods of Organizing Human Activity without significantly more. The Examiner does not acknowledge that the newly amended claims are directed to a practical application as the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration into a practical application. The Examiner does not acknowledge that the newly amended claims recite an improvement to a conventional field of technology as the claims are similar to “iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48” (See MPEP 2106.05(a)(II)) that the courts have indicated may not be sufficient to show an improvement to technology. The 35 U.S.C. 101 rejection(s) stand.
In response to argument (2), the Examiner does not find the Applicant’s argument(s) persuasive. The Examiner maintains that the claims as drafted, given the broadest reasonable interpretation, but for the recitation of generic computer components, encompass managing interactions between people (including following rules or instructions), which is a subgrouping of Certain Methods of Organizing Human Activity. For example, but for the “…by a computing system,…”, “…from a remote data acquiring device;” language, the “receiving” function in the context of this claim encompasses a user following instructions to obtain data related to at least one sleep pattern metric. Similarly, but for the “…by a computing system,…”, “…using a model driven recommendation model, wherein the model driven recommendation model uses at least one of a bio-mathematical sleep model and a system of ordinary differential equations based on neurobiological mechanisms;” language, the “processing” function in the context of the claim encompasses a user following instructions to determine at least one sleep pattern improvement adjustment. Finally, but for the “…by a computing system,…”, “…to a remote actuation device…” language, the “processing” function in the context of this claim encompasses a user following instructions to determine at least one device control instruction based on the at least one sleep pattern improvement adjustment. These steps could be accomplished by a person managing medical information to be shown to another person by following rules or instructions, and therefore encompass Certain Methods of Organizing Human Activity. Additionally, the claims recite “…using a model driven recommendation model, wherein the model driven recommendation model uses at least one of a bio-mathematical sleep model and a system of ordinary differential equations based on neurobiological mechanisms;” at a high degree of generality, amount no more than generally linking the abstract idea to a particular technical environment. The recitation is also similar to adding the words “apply it” to the abstract idea. As set forth in MPEP 2106.05(f), merely reciting the words “apply it” or an equivalent, is an example of when an abstract idea has not been integrated into a practical application. The particular technical environment being sleep monitoring. The Examiner maintains that the steps of “processing, by the computing system, the at least one sleep pattern improvement adjustment to generate at least one device control instruction to a remote actuation device, to cause the remote actuation device to implement a device action for facilitating the at least one sleep pattern improvement adjustment;’ and “sending, by the computing system, the at least one device control instruction to the remote actuation device” do not require the “remote actuation device” to act on or execute the device control instruction, only that the device control instruction is sent to the remote actuation device. The Examiner maintains that the recitations of the “computing system” as amount to no more than general purpose computer components programmed to perform the abstract idea. The Examiner maintains that the newly amended claims do not integrate the abstract idea into a practical application. The 35 U.S.C. 101 rejection(s) stand.
In response to argument (3), the Examiner does not find the Applicant’s argument(s) persuasive. The Examiner maintains that the Applicant’s recitation of machine learning (“model driven recommendation model”) is recited at a high degree of generality, that is similar to adding the words “apply it” to the abstract idea. As set forth in MPEP 2106.05(f), merely reciting the words “apply it” or an equivalent, is an example of when an abstract idea has not been integrated into a practical application. The 35 U.S.C. 101 rejection(s) stand.
In response to argument (4), the Examiner does not find the Applicant’s argument(s) persuasive. The Examiner maintains that Proud encompasses “a computed sleep pattern improvement adjustment (decision tree in claim 54)” in col. 56, ll. 1-6, col. 58, ll. 60-67, col. 59, ll. 1-49, Proud/D’Alessandro encompasses “a computed sleep pattern improvement adjustment (neurobiology-based ODE/biomathematical model in claim 33)” in D’Alessandro in col. 6, ll. 14-25, 60-67, col. 7, ll. 1-29, col. 8, ll. 54-67, col. 9, ll. 1-42, Proud encompasses “generating from that adjustment a device control instruction” in col. 11, ll. 44-67, col. 12, 1-4, and Proud encompasses “a resulting device action that is distinct from display” in col. 11, ll. 44-67, col. 12, 1-4. The Examiner has addressed the newly amended portion of “wherein the device action is distinct from the displaying of the sleep pattern improvement adjustment” in Proud in col. 11, ll. 44-67, col. 12, ll. 1-4: The monitor device receives commands and data from the Cloud System after each upload, the monitor device can communicate with a person’s mobile device, the mobile device can send command information directed to one or more of: activating sensors, including but not limited to light, sound and the like, which the Examiner is interpreting the sensors to encompass a remote actuation device, command information directed to activating sensors to encompass at least one device control instruction. The Applicant’s Specification describes “decision tree” as “In some embodiments, processing the data to generate at least one sleep pattern recommendation comprises using a decision tree.” and “At step 1140, processor112 then executes modules160, 170 and 180 to perform a shift work management process to generate recommendations and implementations for the user. The shift work management process may include using a decision tree informed by best practice circadian principles in some embodiments.” The Examiner maintains that broadest reasonable interpretation of “decision tree” as a tree-like model of decisions and possible consequences, the Examiner maintains that the ”stepped care models of treatment” disclosure encompasses the Applicant’s claimed portion of “decision tree” as recited and in light of the Applicant’s Specification. The 35 U.S.C. 102 and 35 U.S.C. 103 rejection(s) stand.
In response to argument (5), the Examiner does not find the Applicant’s argument(s) persuasive. The Examiner maintains that the claims 33, 41-44, 47, 52-53 are rejected under 35 U.S.C. 103 as being unpatentable over Proud (U.S. Patent Publication No. 10,004,451) in view of D’Alessandro et al. (U.S. Patent Publication No. 10,398,389). The Examiner maintains that “The system, motion detection device and cloud system are used to provide a message regarding relaxation tools and/or reschedule worry-times to earlier in the day” identifies that a message would be displayed on a screen as Proud discloses the use of computers and mobile devices that have display screens (See col. 7, ll. 30-62, col. 18, ll. 27-57). The Examiner maintains that D’Alessandro describes in col. 8, ll. 54-67, col. 9, ll. 1-42: A model simulation is generated with the current parameter set, for example, once the model is uniquely defined by the values assigned to parameters, the model can be simulated by solving the set of differential algebraic equations, or the like, that defines the model as embodied in the modules and the interconnections of the modules that describe the biological system being modeled, which the Examiner is interpreting the set of differential algebraic equations to encompass a system of ordinary differential equations based on neurobiological mechanisms as the health and body simulation can be used to model various health scenarios, which can include specific biological functions (col. 7, ll. 12-19), and the model to encompass one of a bio-mathematical sleep model. The health and body simulation can be used to model various health scenarios for individual subjects (col. 7, ll. 11-29), and testing and selection of intervention programs can use the health and body simulation, one of the intervention programs is directed to sleep (col. 11, ll. 4-36). The Examiner maintains that Proud/D’Alessandro encompasses the newly amended independent claim 33. The Examiner has relied upon Proud to reject the “Recommendation-to-actuation pipeline” as described above in the 35 U.S.C. 103 rejection(s). The Examiner maintains that the combination of Proud/D’Alessandro would be obvious to one of ordinary skill in the art with the motivation of providing an improved physiological health and body simulation system that can provide a platform for a wide range of applications as both Proud and D’Alessandro are directed to evaluate patient conditions and improve physiological health. The 35 U.S.C. 103 rejection(s) stand.
In response to argument (6), the Examiner does not find the Applicant’s argument(s) persuasive. The Examiner maintains that the combination of Proud/Olivier discloses Paragraphs [0024]-[0026]: Examples of ODE models with shared variables that are combined to construct virtual physiological systems include, but are not limited to, models of cardiovascular systems, cardiopulmonary systems, cellular respiratory system, central nervous systems, and database metrics, biological metrics and demographic data serve as input to enable probabilistic modelling of user physiology and behaviour by utilizing stochastic models such as Hidden Markov models (HMM) and/or exhaustive simulations in parallel with predictive ODE models, and the Examiner is interpreting central nervous systems to encompass neurobiological mechanisms of sleep and circadian regulation. The 35 U.S.C. 103 rejection(s) stand.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Papadopoulos et al. (U.S. Patent Pre-Grant Publication No. 2014/0155705), describes a method and system for wellness monitoring using one or more wellness indicator inputs and values.
Ray (U.S. Patent Pre-Grant Publication No. 2014/0052464), describes system for remotely monitoring a patient, the system comprises a plurality of input sources operable to acquire information corresponding to a well-being condition of a patient, an external database for storing analytical models and medical data, and a central controller being operable to receive the signal from the input sources, perform an algorithm to select an analytical model from the database based on the information and the data, perform an algorithm on the information and the data with the model to determine a state of the patient and formulate a health prediction, determine a recommendation as a result of the state and the health prediction, and transmit the recommendation to at least one external entity for providing support and assistance to the patient or to a caregiver of the patient.
Chua et al. (“Individual differences in physiologic measures are stable across repeated exposures to total sleep deprivation”), describes assess stability of individual differences, intraclass correlation coefficients (ICC) were determined using variance components analysis, and individual differences in PVT performance were reproducible across study visits, as were baseline sleep measures prior to sleep deprivation.
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/Bennett Stephen Erickson/Primary Examiner, Art Unit 3683