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 § 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.
Claim(s) 1-3, 6, 7, 11-13, 16, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication 2020/0058404 to Nazem et al. in view of U.S. Patent 11,183,080 to Wolf et al.
As to claims 1 and 11, Nazem discloses a system for generating cardiovascular health programs, the system comprising:
A sensor configured to collect a cardiovascular sample relating to a user (Nazem [0074], [0077], [0080])
a computing device, the computing device configured to:
receive at least a cardiovascular sample relating to a user (Nazem [0007]);
receive a plurality of physical activities (Nazem paragraph [0010]-[0011]);
generate at least a cardiovascular parameter as a function of the at least a cardiovascular sample (Nazem [0013]);
determine a cardiovascular profile as a function of the at least a cardiovascular parameter and at least a cardiovascular deficiency, wherein:
the at least a cardiovascular deficiency is compared to a cardiovascular threshold (Nazem [0013]);
the cardiovascular profile includes a numerical cardiovascular health score correlated to the at least a cardiovascular parameter (Nazem [0013]); and
the cardiovascular profile comprises an atherosclerosis indicator correlated to the at least a cardiovascular parameter, wherein the atherosclerosis indicator includes a location in a user’s body wherein a vein or artery is accumulating plaque buildup (Nazem [0071]-[0073]);
generate a lifestyle program as a function of the cardiovascular profile, wherein generating the lifestyle program comprises:
correlating at least a physical activity from the plurality of physical activities to the at least a cardiovascular parameter (Nazem [0109]); and
assigning the at least a physical activity to the user as a function of the correlation (Nazem [0109]).
However, Nazem does not explicitly teach identifying, by the computing device, a plurality of nutritional elements as a function of the cardiovascular profile, wherein identifying the plurality of nutritional elements comprises classifying the cardiovascular profile to a cardiovascular disease category using a classifier machine-learning model; train a nutrition element machine-learning model using a first correlation between the identified nutritional elements as a function of the cardiovascular profile and the at least a cardiovascular deficiency, wherein the trained nutrition element machine-learning model is configured to output a nutrition element. Wolf discloses identifying, by the computing device, a plurality of nutritional elements as a function of the cardiovascular profile, wherein identifying the plurality of nutritional elements comprises classifying the cardiovascular profile to a cardiovascular disease category using a classifier machine-learning model; train a nutrition element machine-learning model using a first correlation between the identified nutritional elements as a function of the cardiovascular profile and the at least a cardiovascular deficiency, wherein the trained nutrition element machine-learning model is configured to output a nutrition element, generate a lifestyle program as a function of the nutritional element (Wolf abstract and column 2 lines 53-67 and column 3 lines 1-52).
It would have been obvious to utilize machine learning to generate nutritional recommendations for a cardiovascular profile as in Wolf in the system of Nazem to improve the accuracy of nutritional advice.
As to claims 2 and 12, see the discussion of claim 1, additionally, Nazem discloses the system wherein generating the lifestyle program comprises receiving a user choice regarding an activity (Nazem [0053]).
As to claims 3 and 13, see the discussion of claim 1, additionally, Nazem discloses the system wherein computing device is further configured to generate the lifestyle program using a lifestyle program classifier (Nazem [0053]).
As to claims 6 and 16, see the discussion of claim 1, additionally, Nazem discloses the system wherein the computing device is further configured to calculate the numerical cardiovascular health score, wherein calculating the numerical cardiovascular health score comprises:
assigning a first numerical score to the at least a cardiovascular parameter as a function of the cardiovascular threshold (Nazem [0094]-[0098]);
assigning a second numerical score to at least a physical activity associated with the at least a cardiovascular parameter (Nazem [0094]-[0098]); and
calculating the numerical cardiovascular score as a function of the second numerical score and the first numerical score (Nazem [0094]-[0098]).
As to claim 7 and 17, see the discussion of claim 6, additionally, Nazem discloses the system wherein the computing device is further configured to minimize the numerical cardiovascular score as a function of the at least a physical activity from the plurality of physical activities (Nazem [0094]-[0098]).
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.
Claim(s) 4, 5, 8-10, 14, 15, and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication 2020/0058404 to Nazem et al. in view of U.S. Patent 11,183,080 to Wolf et al. in view of U.S. Patent Application Publication 2021/0241139 to Jain et al.
As to claims 4 and 14, see the discussion of claim 3, however, Nazem does not explicitly teach the system wherein the computing device is further to train a classification machine learning model using a lifestyle training set. Jain discloses wherein the computing device is further to train a classification machine learning model using a lifestyle training set (Jain [0353]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing of the invention by applicant to train a model using lifestyle data as in Jain in the system of Nazem to gain insights using known risk factors to improve the therapeutic value of assigned activities.
As to claims 5 and 15, see the discussion of claim 4, additionally, Jain discloses the system wherein the lifestyle training set comprises previous iterations classification machine learning model (Jain [0353] and [0338]).
As to claims 8 and 18, see the discussion of claim 1, however, Nazem does not explicitly teach the system wherein generating the lifestyle program comprises generating an activity adherence score. Jain discloses wherein generating the lifestyle program comprises generating an activity adherence score (Jain [0272]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing of the invention by applicant to monitor adherence as in Jain in the system of Nazem to improve patient outcomes by ensuring proper treatment of their conditions.
As to claims 9 and 19, see the discussion of claim 1, however, Nazem does not explicitly teach the system wherein the computing device is further configured to modify the activity adherence score. Jain discloses wherein the computing device is further configured to modify the activity adherence score (Jain [0272], [0277]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing of the invention by applicant to monitor adherence as in Jain in the system of Nazem to improve patient outcomes by ensuring proper treatment of their conditions.
As to claim 10 and 20, see the discussion of claim 1, however, Nazem does not explicitly teach the system wherein the computing device is further configured to modify the lifestyle program as a function of the activity adherence score. Jain discloses wherein the computing device is further configured to modify the lifestyle program as a function of the activity adherence score (Jain [0272]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing of the invention by applicant to monitor adherence as in Jain in the system of Nazem to improve patient outcomes by ensuring proper treatment of their conditions.
Response to Arguments
Applicant's arguments filed 4/24/26 have been fully considered but they are not persuasive.
The prior rejections under 101 are withdrawn in light of Applicants amendments and arguments. Applicant asserts that the amended subject matter is not taught by the references, the newly added features of the claims are rejected for the reasons set forth above
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Eliza Lam whose telephone number is (571)270-7052. The examiner can normally be reached Monday-Friday 8-4:30PST.
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/ELIZA A LAM/Primary Examiner, Art Unit 3681
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