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 .
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.
Notice of Amendment
In response to the amendment(s) filed on 10/10/25, amended claim(s) 1 and 5-14, canceled claim(s) 2-4, and new claim(s) 15-23 is/are acknowledged. The following new and/or reiterated ground(s) of rejection is/are set forth:
Claim Objections
Claim 1 is objected to because of the following informalities: “to Vth value” (line 27) appears that it should be “to the Vth value.”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
Claim(s) 1 and 5-23 is/are 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.
For claim 1, the claim language “calculate, using a first machine-learning-trained body-motion model, a plurality of body-motion scores including an acceleration-based score and a vocal-volume-based score from the acquired body motion data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a plurality of body-motion scores including an acceleration-based score and a vocal-volume-based score from the acquired body motion data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine-learning-trained body-motion model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 1, the claim language “calculate, using a second machine-learning-trained vital model, a vital score from the heart-rate data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a vital score from the heart-rate data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine-learning-trained vital model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 12, the claim language “calculate, using a machine learning fusion model and as a calculated body motion/vital score, a body motion/vital score based on the body motion data and the time-series vital data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a body motion/vital score based on the body motion data and the time-series vital data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine learning fusion model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 13, the claim language “calculate, using a first machine-learning-trained body-motion model, a plurality of body-motion scores including an acceleration-based score and a vocal-volume-based score from the acquired body motion data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a plurality of body-motion scores including an acceleration-based score and a vocal-volume-based score from the acquired body motion data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine-learning-trained body-motion model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 13, the claim language “calculate, using a second machine-learning-trained vital model, a vital score from the heart-rate data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a vital score from the heart-rate data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine-learning-trained vital model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 14, the claim language “calculating, using a first machine-learning-trained body-motion model, a plurality of body-motion scores including an acceleration-based score and a vocal-volume-based score from the acquired body motion data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a plurality of body-motion scores including an acceleration-based score and a vocal-volume-based score from the acquired body motion data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine-learning-trained body-motion model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 14, the claim language “calculating, using a second machine-learning-trained vital model, a vital score from the heart-rate data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a vital score from the heart-rate data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine-learning-trained vital model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 22, the claim language “calculating, using a machine learning fusion model and as a calculated body motion/vital score, a body motion/vital score based on the body motion data and the time-series vital data” does not appear to be 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of calculating a body motion/vital score based on the body motion data and the time-series vital data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “machine learning fusion model” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? What biases are relied upon? Is the training supervised or unsupervised? What are the weightings? Are other training concepts used such as regression? How is the clustering problem solved, if applicable? What is the loss function and how is it minimized? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
Dependent claim(s) 5-12 and 15-23 fail to cure the deficiencies of independent claims 1 and 13, thus claim(s) 1 and 5-23 is/are rejected under 35 U.S.C. 112(a).
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) 1 and 5-23 is/are rejected under 35 U.S.C. 101 because the claimed invention, considering all claim elements both individually and in combination as a whole, do not amount to significantly more than a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea).
Claim 1 is a claim to a process, machine, manufacture, or composition of matter and therefore meets one of the categorical limitations of 35 U.S.C. 101. However, claim 1 meets the first prong of the step 2A analysis because it is directed to a/an abstract idea, as evidenced by the claim language of “acquire, from the body motion sensor and the vital sensor via the communication interface, time-series body motion data, as acquired body motion data of a target and including acceleration and vocal volume, and time-series vital data of the target including heart-rate data,” “calculate, using a first machine-learning-trained body-motion model, a plurality of body-motion scores including an acceleration-based score and a vocal-volume-based score from the acquired body motion data,” “calculate, using a second machine-learning-trained vital model, a vital score from the heart-rate data,” “perform decision making by comparing each of the body-motion scores with respective ones of body-motion threshold (Bth) values, respective to ones of the each of the body-motion scores, and comparing the vital score with a vital threshold (Vth) value,” “determine, as an indication of an agitation state of the target, that the target exhibits a predictive sign of agitation based on determining that the vital score is greater than or equal to the Vth value while each of the body-motion scores is less than the respective ones of the Bth values,” “determine, as the agitation state and based on determining that any one of the body-motion scores is greater than or equal to a respective one of the Bth values, that the target is agitated,” and “output a notification to a bed terminal or a nurse station.” This claim language, under the broadest, reasonable interpretation, encompasses subject matter that may be performed by a human using mental steps or with pen and paper that can involve basic critical thinking, which are types of activities that have been found by the courts to represents abstract ideas (i.e., the mental comparison in Ambry Genetics, or the diagnosing an abnormal condition by performing clinical tests and thinking about the results in Grams). The claim language also meets prong 2 of the step 2A analysis because the above-recited claim language does not integrate the abstract idea into a practical application. That is, there appears to be no tangible improvement in a technology, effect of a particular treatment or prophylaxis, a particular machine or manufacture that is integrated, or transformation/reduction of a particular article to a different state or thing as a result of this claimed subject matter. As a result, step 2A is satisfied and the second step, step 2B, must be considered.
With regard to the second step, the claim does not appear to recite additional elements that amount to significantly more. The additional elements are “a body motion sensor including an accelerometer and a microphone,” “a vital sensor including a heart-rate sensor,” “a communication interface,” “at least one memory configured to store processing instructions,” and “at least one processor configured to execute processing instructions.” However, these elements are not “significantly more” because they are well-known, routine, and/or conventional as evidenced by para [0055] of U.S. Patent Application Publication No. 2020/0341548 to Giordano and Bilski, which held that generic computer structures (such as memories and processors) are not enough to be significantly more. Therefore, these elements do not add significantly more and thus the claim as a whole does not amount to significantly more than a judicial exception.
Additionally, the ordered combination of elements do not add anything significantly more to the claimed subject matter. Specifically, the ordered combination of elements do not have any function that is not already supplied by each element individually. That is, the whole is not greater than the sum of its parts.
In view of the above, independent claim 1 fails to recite patent-eligible subject matter under 35 U.S.C. 101. Independent claim(s) 13-14 fail to recite patent-eligible subject matter for similar, if not the exact same, reasoning as that of independent claim 1. Dependent claim(s) 5-12 and 15-23 fail to cure the deficiencies of independent claim 1 by merely reciting additional abstract ideas and/or further limitations on abstract ideas already recited. Thus, claim(s) 1 and 5-23 is/are rejected under 35 U.S.C. 101.
Response to Arguments
Applicant’s arguments filed 10/10/25 have been fully considered.
With respect to the 112 rejection(s), Applicant’s amendments and arguments are persuasive and thus the previous rejection(s) is/are withdrawn. However, Applicant’s amendments have warranted new 112 rejections.
With respect to the 101 rejection(s), Applicant’s amendments and arguments are not persuasive. The grounds for the 101 rejection(s) is/are set forth above. Applicant’s arguments with respect to the 101 rejection(s) will be treated in the order they were presented in the response filed 10/10/25. With respect to the first argument, example 38 from the subject matter examples is related to simulating an analog mixer. The claimed subject matter of is for simulating a physical circuit and in the instant case the claimed subject matter is not simulating a physical circuit. With respect to the second argument, example 39 from the subject matter examples is related to training a neural network by applying mathematical transformations on acquired sets of facial images. The claimed subject matter of the instant application is not transformation any set of images (i.e., at least two-dimensional data), but instead calculating scores (i.e., one-dimensional data). With respect to the third argument, the BRI of the claim language is broad enough to encompass single integers. For example, the claim term “scores” can encompass numbers such as 5 or 10 under broadest, reasonable interpretation and the human mind can think of numbers such as these. As another example, “time-series body motion data” can be, under broadest, reasonable interpretation, can be two data points, one at 1 second, one at 2 seconds, and those data points can be different magnitude, such as 40 db and 50 db. With respect to the fourth argument, “predicting signs of a patient’s agitation and various determinantal results from that difficulty” is not a technology and therefore an improvement in a prediction is not an improvement in technology. With respect to the fifth argument, “reducing missed events and false alarms” is not a practical application because it does not fall into one the categories set out in the MPEP of a tangible improvement in a technology, effect of a particular treatment or prophylaxis, a particular machine or manufacture that is integrated, or transformation/reduction of a particular article to a different state or thing. Reducing missed events and false alarms is not tangible, it is intangible and broadly falls under the umbrella of information. With respect to the sixth argument, the newly recited structures are found to not be significantly more in view of the newly cited art in the 101 rejection(s) above.
With respect to the 102/103 rejection(s), Applicant’s amendments and arguments and persuasive and thus the rejections are withdrawn.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL LEE CERIONI whose telephone number is (313) 446-4818. The examiner can normally be reached M - F 8:00 AM - 5:00 PM PT.
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/DANIEL L CERIONI/Primary Examiner, Art Unit 3791