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 § 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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: The claims are directed to a method which falls within one of the statutory categories of invention. Step 2A, Prong One: 101 SME rejection for the claims needed as “acquiring historical exercise data” and “determining a target exercise recommendation result” falls within the mental process enumerated grouping of abstract ideas. “Outputting information” are extra solution activities. The additional elements “terminal device”, are conventional elements performing their generic functions see specs para 0138. The claim does not include sufficient additional limitations as an inventive concept to transform the abstract idea into patent eligible application, given the steps and components are generic. When looked at individually and as a whole, the claim limitations are determined to be an abstract idea without “significantly more” and thus not patent eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1)/102(a)(2) as being anticipated by Capodilupo et al. (U.S. Publication Number 2022/0273232).
Referring to claim 1, Capodilupo et al. discloses comprising: acquiring, by a terminal device, historical sleep data and historical exercise data of a target object, the historical sleep data comprising sleep data of at least one time period prior to a target time period, and the historical exercise data comprising exercise data of at least one time period prior to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); determining a target exercise recommendation result of the target time period for the target object according to the historical sleep data and the historical exercise data, the target exercise recommendation result comprising at least one of a target recommended exercise time or a target recommended exercise amount (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and outputting information about the target exercise recommendation result (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 1, Capodilupo et al. discloses wherein determining the target exercise recommendation result of the target time period for the target object according to the historical sleep data and the historical exercise data comprises: determining a candidate exercise time set based at least in part on historical exercise time data comprised in the historical exercise data, the candidate exercise time set comprising at least one
candidate exercise time (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and determining the target recommended exercise time from the candidate exercise time set based at least in part on the historical sleep data (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 3, Capodilupo et al. discloses wherein determining the target recommended exercise time from the candidate exercise time set based at least in part on the historical sleep data comprises: determining the target recommended exercise time from the candidate exercise time set based on a sleep type of the target object and at least part of the historical sleep data, wherein the sleep type comprises at least one of wakeup early, wakeup late, sleep early, sleep late, or insomnia (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 4, Capodilupo et al. discloses wherein determining the target recommended exercise time from the candidate exercise time set based at least in part on the historical sleep data comprises: determining an exercise time offset corresponding to a sleep type of the target object (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); determining an exercise time requirement according to the exercise time offset and at least part of historical sleep start time data comprised in the historical sleep data, the exercise time requirement comprising a latest exercise time (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and determining the target recommended exercise time from one or more candidate exercise times
in the candidate exercise time set that meet the exercise time requirement (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 5, Capodilupo et al. discloses wherein determining the target recommended exercise time from the candidate exercise time set based at least in part on the historical sleep data comprises: determining the target recommended exercise time from the at least one candidate exercise time based on at least part of the historical sleep data and an exercise frequency corresponding to the at least one candidate exercise time (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 6, Capodilupo et al. discloses wherein determining the target exercise recommendation result of the target time period for the target object according to the historical sleep data and the historical exercise data comprises: determining an initial exercise recommendation result of the target time period according to
first historical exercise data in the historical exercise data (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and performing adjustment processing on the initial exercise recommendation result of the target time period based on at least part of the historical sleep data, to obtain the target exercise recommendation result of the target time period for the target object (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 7, Capodilupo et al. discloses wherein the first historical exercise data comprises exercise data in at least one historical exercise recommendation cycle prior to a current exercise recommendation cycle to which the target time period belongs (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); or the at least part of the historical sleep data comprises sleep data during at least one time period
close to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 8, Capodilupo et al. discloses wherein determining the initial exercise recommendation result of the target time period according to the first historical exercise data in the historical exercise data comprises: determining an exercise recommendation strategy for the target time period according to a physiological measurement of the target object (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and
determining the initial exercise recommendation result of the target time period based on the exercise recommendation strategy for the target time period and the first historical exercise data (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367);
wherein the initial exercise recommendation result comprises an initial recommended
exercise amount, and the exercise recommendation strategy comprises increasing the exercise amount, decreasing the exercise amount, or maintaining the exercise amount (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 9, Capodilupo et al. discloses wherein performing adjustment processing on the initial exercise recommendation result of the target time period according to the at least part of the historical sleep data, to obtain the target exercise recommendation result of the target time period for the target object comprises: obtaining, according to the at least part of the historical sleep data, a sleep quality assessment result for the target object in at least one time period close to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and
performing adjustment processing on the initial exercise recommendation result of the target time period based on the sleep quality assessment result for the target object in the at least one time period, to obtain the target exercise recommendation result of the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 10, Capodilupo et al. discloses wherein performing adjustment processing on the initial exercise recommendation result of the target time period according to the at least part of the historical sleep data, to obtain the target exercise recommendation result of the target time period for the target object comprises: performing adjustment processing on the initial exercise recommendation result of the target time period according to at least part of the historical sleep data and second historical exercise data in the historical exercise data, to obtain the target exercise recommendation result of the target time period, wherein the second historical exercise data comprises exercise data during at least one time period within a current exercise recommendation cycle to which the target time period belongs and prior to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 11, Capodilupo et al. discloses wherein determining the target exercise recommendation result of the target time period for the target object according to the historical sleep data and the historical exercise data comprises: determining, at a first time point, an initial exercise recommendation result of the target time
period according to first historical exercise data in the historical exercise data, the first time point being a time point prior to a current exercise recommendation cycle to which the target time period belongs (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and performing, at a second time point, adjustment processing on the initial exercise recommendation result of the target time period based on at least part of the historical sleep data, to obtain the target exercise recommendation result of the target time period for the target object, the second time point being a time point within the current exercise recommendation cycle and prior to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 12, Capodilupo et al. discloses wherein determining the target exercise recommendation result of the target time period for the target object according to the historical sleep data and the historical exercise data comprises: determining, based on first historical exercise data included in the historical exercise data, an
initial exercise recommendation result for each of a plurality of time periods included in a current exercise recommendation cycle to which the target time period belongs, wherein the first historical exercise data includes exercise data of at least one time period prior to the current exercise recommendation cycle (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and performing adjustment processing on the initial exercise recommendation result of the target time period based at least in part on at least one of the historical sleep data or second historical motion data included in the historical motion data, to obtain the target exercise recommendation result of the target time period for the target object, wherein the second historical exercise data
includes exercise data of at least one time period within the current motion recommendation cycle and prior to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 13, Capodilupo et al. discloses wherein determining the target exercise recommendation result of the target time period for the target object according to the historical sleep data and the historical exercise data comprises: determining an initial exercise recommendation result of the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and performing adjustment processing on the initial exercise recommendation result of the target time period based on at least part of the historical sleep data and second historical exercise data in the historical exercise data, to obtain the target exercise recommendation result of the target time
period, wherein the at least part of the historical sleep data comprises sleep data during at least one time period close to the target time period, and the second historical exercise data comprises exercise data during the at least one time period close to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 14, Capodilupo et al. discloses wherein performing adjustment processing on the initial exercise recommendation result of the target time period according to the at least part of the historical sleep data and the second historical exercise data in the historical exercise data, to obtain the target exercise recommendation result of the target time period comprises: obtaining an exercise assessment result for the target object according to the second historical
exercise data, the exercise assessment result indicating an exercise accomplishment condition of the target object during at least one time period close to the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); obtaining a sleep quality assessment result for the target object according to at least part of
the historical sleep data (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and performing adjustment processing on the initial exercise recommendation result of the target time period according to the exercise assessment result and the sleep quality assessment result, to obtain the target exercise recommendation result of the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 15, Capodilupo et al. discloses wherein the sleep quality assessment result comprises a sleep recovery index (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and obtaining the sleep quality assessment result for the target object according to the at least part of the historical sleep data comprises: obtaining sleep heart rate variability (HRV) data of the target object according to the at
least part of the historical sleep data (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and obtaining the sleep recovery index of the target object based on the sleep HRV data of the target object (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 16, Capodilupo et al. discloses comprising: acquiring, by a terminal device, historical sleep data of a target object (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); determining, according to at least one of attribute information of the target object or expected sleep information of the target object, a target value of at least one sleep parameter of the target object (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); determining a sleep recommendation result of a target time period for the target object based on the target value of the at least one sleep parameter and the historical sleep data of the target object, the sleep recommendation result comprising at least one of a recommended sleep start time, a recommended wakeup time, or a recommended sleep time duration (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and outputting information about the sleep recommendation result (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 17, Capodilupo et al. discloses wherein the expected sleep information of the target object comprises an expected value of the at least one sleep parameter (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); and
determining, according to at least one of the attribute information of the target object or the expected sleep information of the target object, the target value of the at least one sleep parameter of the target object comprises: determining, in response to the expected sleep information of the target object comprising a valid expected value of a first sleep parameter, the valid expected value of the first sleep parameter as a target value of the first sleep parameter (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); or determining, in response to the expected sleep information of the target object not comprising a valid expected value of a second sleep parameter, a target value of the second sleep parameter according to the attribute information of the target object (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 18, Capodilupo et al. discloses wherein determining the sleep recommendation result of the target time period for the target object based on the target value of the at least one sleep parameter and the historical sleep data of the target object comprises at least one of: determining a sleep adjustment strategy for the target object based on the historical sleep data of the target object and the target value of the at least one sleep parameter, and obtaining the sleep recommendation result of the target time period for the target object according to the sleep adjustment strategy (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); processing the historical sleep data of the target object to obtain a current value of the at least
one sleep parameter of the target object, and obtaining, in response to a difference between the current value of the at least one sleep parameter and the target value of the at least one sleep parameter exceeding a preset difference range, the sleep recommendation result of the target time period for the target object by using a progressive adjustment strategy (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); obtaining, in response to a difference between a current value of the at least one sleep parameter indicated by the historical sleep data of the target object and the target value of the at least one sleep parameter exceeding a preset difference range, the sleep recommendation result of the target time period for the target object based on an adjustment step size and the current value of the at least one sleep parameter (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); or
determining, in response to the difference between the current value of the at least one sleep parameter indicated by the historical sleep data of the target object and the target value of the at least one sleep parameter being within the preset difference range, that the sleep recommendation result of the target time period for the target object comprises the target value of the at least one sleep parameter (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 19, Capodilupo et al. discloses further comprising at least one of:
obtaining a supplemental sleep recommendation result of the target time period for the target object based at least in part on regular sleep data of the target object during a previous time period of the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); or outputting a warning for time duration of supplemental sleep based at least in part on supplemental sleep data of the target object during the previous time period of the target time period (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Referring to claim 20, Capodilupo et al. discloses wherein obtaining the supplemental sleep recommendation result of the target time period for the target object based at least in part on the regular sleep data of the target object during the previous time period of the target time period comprises at least one of: determining, in response to the regular sleep data of the target object during the previous time period of the target time period indicating that a time duration of a regular sleep of the target object
during the previous time period does not reach a preset sleep time duration, that the supplemental sleep recommendation result of the target time period for the target object comprises a recommended time duration of supplemental sleep being a first time duration greater than zero (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367); or determining, in response to the regular sleep data of the target object during the previous time period of the target time period indicating that the time duration of the regular sleep of the target object during the previous time period reaches the preset sleep time duration, that the supplemental sleep recommendation result of the target time period for the target object comprises a recommended time duration of supplemental sleep being zero (paragraphs 0004, 0005, 0008, 0244-0251, 0271 & 0359-0367).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KESHA FRISBY whose telephone number is (571)272-8774. The examiner can normally be reached Monday-Friday 730AM-4PM.
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/KESHA FRISBY/Primary Examiner, Art Unit 3715
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