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 .
Claim Rejections - 35 USC § 102
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.
Claim(s) 17 and 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Cail (US 2020/0281521 – provided by Applicant in the IDS).
Regarding claim 17, Cail as modified teaches a system for improving sleep comprising: a server (see paragraph [0073]) platform in network communication with at least one regulating device (see 330, paragraph [0055], see step 545) and at least one sensor (see sensory array noted in Abstract, 310, Fig. 1, paragraph [0016]), wherein the at least one regulating device is operable to adjust one or more parameters of at least one sleeping article (see paragraph [0024]), wherein the server platform receives data from the at least one sensor (see paragraphs [0020]-[0021]), wherein the server platform includes an artificial intelligence module operable to determine a recommended adjustment to the one or more parameters (see paragraph [0022]), and wherein the artificial intelligence module selects a machine learning module operable to determine the recommended adjustment based on historical sensor data associated with a user (see paragraph [0057]).
Regarding claim 19, Cail teaches the system of claim 17, wherein a magnitude and timing of the recommended adjustment is based on the historical sensor data (see paragraph [0060]).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-4, 7-9, 11-15 are rejected under 35 U.S.C. 103 as being unpatentable over Cail (US 2020/0281521 – provided by Applicant in the IDS) in view of Scorcioni (US 2016/0136385 – provided by Applicant in the IDS).
Regarding claim 1, Cail system for improving sleep (see Abstract, Title) comprising:
at least one sensor operable to measure one or more conditions of a user and/or an environment (see sensory array noted in Abstract, 310, Fig. 1, paragraph [0016]));
at least one user device operable to receive a user command (320, Fig. 1, see paragraph [0016]); at least one regulating device operable to adjust one or more parameters of at least one sleeping article (see 330, paragraph [0055], see step 545); and
at least one processor in communication with the at least one sensor, the at least one regulating device, and the at least one user device (see paragraph [0017]),
the at least one processor configured to: receive data from the at least one sensor (see paragraphs [0020]-[0021]);
determine, via an artificial intelligence module, a recommended adjustment to the one or more parameters based on the sensor data (see paragraph [0022]);
cause the at least one regulating device to adjust the one or more parameters based on the recommended adjustment (see paragraph [0024]).
Cail does not specifically teach: receive the user command from the at least one user device; and override the recommended adjustment based on the user command.
Scorcioni teaches a sleep managing system (Scorcioni, Title) which features allowing the user to override a controller operation in order to independently operate the thermal-comfort profile (Scorcioni, claim 20).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date, to provide Cail with overriding the recommended adjustment, as taught by Scorcioni, in order to provide the user greater control over the system.
Regarding claim 2, Cail as modified teaches the system of claim 1, wherein the at least one processor is further configured to determine a status of a user based on the sensor data (Cail, paragraph [0029]).
Regarding claim 3, Cail as modified teaches the system of claim 2, wherein the at least one processor is further configured to determine a heuristic-based adjustment for the at least one sleep article based on the status of the user (see Cail, paragraphs [0029]-[0030]).
Regarding claim 4, Cail as modified teaches the system of claim 3, wherein the at least one processor is operable to override the recommended adjustment based on the heuristic-based adjustment (met through the combination with Scorcioni in claim 1).
Regarding claim 7, Cail as modified teaches the system of claim 1, wherein the at least one sensor includes at least one heart rate sensor (see Cail, paragraph [0028]).
The following limitations are not required as the claim is claimed in the alternative, “at least one respiration sensor, at least one microphone, at least one analyte sensor, at least one pressure sensor, and/or at least one movement sensor.”
Regarding claim 8, Cail as modified teaches the system of claim 1, wherein the one or more parameters include a temperature of the at least one sleep article (Cail, paragraph [0030]).
Regarding claim 9, Cail as modified teaches the system of claim 1, wherein the artificial intelligence module selects a machine learning model for the user based on historical sensor data associated with the user and real-time sensor data from the user (Cail, paragraph [0057] at least).
Regarding claim 11, Cail teaches a system for improving sleep comprising: a server platform in network communication (see paragraph [0073]) with at least one regulating device (see 330, paragraph [0055], see step 545) and at least one sensor (see sensory array noted in Abstract, 310, Fig. 1, paragraph [0016]),
wherein the at least one regulating device is operable to adjust one or more parameters of at least one sleep article (see paragraph [0024]),
wherein the server platform receives sensor data from the at least one sensor (see paragraphs [0020]-[0021]),
wherein the server platform includes an artificial intelligence module operable to determine a recommended adjustment to the one or more parameters based on the sensor data (see paragraph [0022]),
wherein the at least one regulating device is operable to adjust the one or more parameters based on the recommended adjustment (see paragraph [0024]), wherein the server platform is operable to determine a status of a user based on the sensor data and determine a heuristic-based adjustment to the one or more parameters based on the status (see paragraph [0024]).
Cail does not teach wherein the heuristic-based adjustment is operable to override the recommended adjustment.
Scorcioni teaches a sleep managing system (Scorcioni, Title) which features allowing the user to override a controller operation in order to independently operate the thermal-comfort profile (Scorcioni, claim 20).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date, to provide Cail with overriding the recommended adjustment, as taught by Scorcioni, in order to provide the user greater control over the system.
Regarding claim 12, Cail as modified teaches the system of claim 11, wherein the one or more parameters include a temperature of the at least one sleep article (Cail, paragraph [0028]).
Regarding claim 13, Cail as modified teaches the system of claim 11, wherein the at least one sensor includes at least one heart rate sensor (see Cail, paragraph [0028]).
The following limitations are not required as the claim is claimed in the alternative, “at least one respiration sensor, at least one microphone, at least one analyte sensor, at least one pressure sensor, and/or at least one movement sensor.”
Regarding claim 14, Cail as modified teaches the system of claim 11, wherein the server platform is operable to receive commands to adjust the one or more parameters of the at least one sleeping article from at least one user device (see paragraph Cail [0037]), and wherein the received commands are operable to override the heuristic-based adjustment (met through the combination with Scorcioni).
Regarding claim 15, Cail as modified teaches the system of claim 11, wherein the artificial intelligence module selects a machine learning model for the user based on historical sensor data associated with each individual user and real-time sensor data from the user (Cail, paragraph [0057] at least).
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Cail in view of Scorcioni, further in view of Brykalski (US 2010/0011502 – provided by Applicant in the IDS).
Regarding claim 5, Cail as modified teaches the system of claim 1, but does not teach the at least one regulating device includes at least one fluid reservoir including one or more modules for heating and/or cooling fluid.
Brykalski teaches a sleep system (Brykalski, Title) which features a regulating device (see thermoelectric device noted in paragraph [0143] of Brykalski) wherein the regulating device comprises a fluid reservoir (Brykalski, 60, Fig. 19) including one or more modules for heating and/or cooling fluid (Brykalski, paragraph [0012], [0148]-[0149]).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date, to provide Cail as modified with the at least one regulating device includes at least one fluid reservoir including one or more modules for heating and/or cooling fluid, as taught by Brykalski, in order to provide greater temperature control of the system for the user.
Regarding claim 6, Cail as modified teaches the system of claim 5, wherein the at least one regulating device is operable to circulate the fluid into and out of the at least one sleeping article (Brykalski, paragraph [0148]).
Claims 10 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Cail in view of Scorcioni, further in view of Hu (US 2011/01267196 – provided by Applicant in the IDS).
Regarding claim 10, Cail as modified teaches the system of claim 9, but does not teach the historical sensor data includes previous sleep stages for each individual user.
Hu teaches a sleep quality feedback (Hu, Title) which features a learning algorithm which can optimize a users sleep based off of data collection on a user's sleep pattern (Hu, paragraph [0027]). Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date, to provide Cail as modified with a learning model based on historical data associated with a users sleep pattern, as taught by Hu, in order increase the comfort or ergonomics during individual sleeps (Hu, paragraph [0027]).
Regarding claim 16, Cail as modified teaches the system of claim 15, but does not teach the historical sensor data includes previous sleep stages for the user.
Hu teaches a sleep quality feedback (Hu, Title) which features a learning algorithm which can optimize a users sleep based off of data collection on a user's sleep pattern (Hu, paragraph [0027]). Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date, to provide Cail as modified with a learning model based on historical data associated with a users sleep pattern, as taught by Hu, in order increase the comfort or ergonomics during individual sleeps (Hu, paragraph [0027]).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Cail in view of Hu (US 2011/01267196 – provided by Applicant in the IDS).
Regarding claim 18, Cail teaches the system of claim 17, wherein the historical sensor data includes previous sleep stages for the user.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Cail in view of Scorcioni (US 2016/0136385 – provided by Applicant in the IDS).
Regarding claim 20, Cail teaches the system of claim 17, but does not teach the server platform is operable to determine a heuristic-based adjust based on a status of the user, wherein the heuristic-based adjustment is operable to override the recommended adjustment.
Scorcioni teaches a sleep managing system (Scorcioni, Title) which features allowing the user to override a controller operation in order to independently operate the thermal-comfort profile (Scorcioni, claim 20).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date, to provide Cail with overriding the recommended adjustment, as taught by Scorcioni, in order to provide the user greater control over the system.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAEL N BABAA whose telephone number is (571)270-3272. The examiner can normally be reached M-F, 9-5 EST.
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/NAEL N BABAA/Primary Examiner, Art Unit 3763
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