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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 03/01/24 has been considered by the examiner.
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 non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of claim 1 follows.
Regarding claim 1, the claim recites a method comprising: receiving, from a measurement device, one or more signals collected for a user of the measurement device during a time period. Thus, the claim is directed to a process, which is one of the statutory categories of invention
The claim is then analyzed to determine whether it is directed to any judicial exception. The following limitations set forth a judicial exception:
extracting measurements for a plurality of biomarkers based on the one or more signals collected for the user; wherein each biomarker characterizes an aspect of cardiovascular health of the user;
applying a heart function model to one or more of (1) the one or more signals collected by the measurement device and (2) the plurality of biomarkers
These limitations set forth a judicial exception. These steps describe a concept performed in the human mind (including an observation, evaluation, judgment, opinion). Thus, the claim is drawn to a Mental Process, which is an Abstract Idea.
Next, the claim as a whole is analyzed to determine whether the claim recites additional elements that integrate the judicial exception into a practical application. The claim fails to recite an additional element or a combination of additional elements to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limitation on the judicial exception. Claim 1 recites the heart function model outputs a heart function index that characterizes a likelihood whether the user will experience a heart failure event during a future time period; and generating, for transmission to a computing device of a clinician, an alert based on the heart function index, wherein the alert comprises a risk state of the user, the risk state determined based on a comparison of the heart function index to a threshold, which is merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). The presenting a heart function index that characterizes a likelihood whether the user will experience a heart failure and outputting an alert does not provide an improvement to the technological field, the method does not effect a particular treatment or effect a particular change based on the presented intrinsic frequency, nor does the method use a particular machine to perform the Abstract Idea
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, is sufficient to ensure that the claim amounts to significantly more than the exception. Besides the Abstract Idea, the claim recites additional steps of:
a measurement device
receiving, from a measurement device, one or more signals collected for a user of the measurement device during a time period
the one or more signals comprising a weight measurement for the user and electrical signals collected through the feet of the user;
Claim 2 recites the additional elements:
a plurality of electrical sensors
one or more load sensors integrated into the measurement device
The providing and recording steps are well-understood, routine and conventional activities for those in the field of medical diagnostics. Further, the providing and recording steps are each recited at a high level of generality such that it amounts to insignificant presolution activity, e.g., mere data gathering step necessary to perform the Abstract Idea. When recited at this high level of generality, there is no meaningful limitation, such as a particular or unconventional step that distinguishes it from well-understood, routine, and conventional data gathering and comparing activity engaged in by medical professionals prior to Applicant's invention. Furthermore, it is well established that the mere physical or tangible nature of additional elements such as the obtaining and comparing steps do not automatically confer eligibility on a claim directed to an abstract idea (see, e.g., Alice Corp. v. CLS Bank Int'l, 134 S.Ct. 2347, 2358-59 (2014)).
Consideration of the additional elements as a combination also adds no other meaningful limitations to the exception not already present when the elements are considered separately. Unlike the eligible claim in Diehr in which the elements limiting the exception are individually conventional, but taken together act in concert to improve a technical field, the claim here does not provide an improvement to the technical field. Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claim as a whole does not amount to significantly more than the exception itself. The claim is therefore drawn to non-statutory subject matter.
The same rationale applies to claims 13 and 20
Dependent claims 2-12 and 14-19 also fail to add something more to the abstract independent claims as they merely further limit the abstract idea.
Therefore, claims 1-20 are not patent eligible under 35 USC 101.
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.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable over Centen (U.S. Patent Application Document 2019/0046069 – cited by Applicant)
Regarding claim 1, Centen teaches a method [par. 14] comprising: receiving, from a measurement device, one or more signals collected for a user of the measurement device during a time period [par. 4, 5], wherein the one or more signals comprising a weight measurement for the user and electrical signals collected through the feet of the user [par. 5, 83]; extracting measurements for a plurality of biomarkers based on the one or more signals collected for the user, wherein each biomarker characterizes an aspect of cardiovascular health of the user [par. 5, 99, 131]; applying a heart function model to one or more of (1) the one or more signals collected by the measurement device and (2) the plurality of biomarkers, wherein the heart function model outputs a heart function index that characterizes a likelihood whether the user will experience a heart failure event during a future time period [par. 87, 131-133]; and generating, for transmission to a computing device of a clinician, an alert based on the heart function index, wherein the alert comprises a risk state of the user, the risk state determined based on a comparison of the heart function index to a threshold [par. 76, 84, 120]
Regarding claim 2, Centen further teaches the one or more signals are collected by a plurality of electrical sensors and one or more load sensors integrated into the measurement device as the user stands on the measurement device [par. 75, 99], the one or more signals comprising one or more of the following: a weight measurement for the user [par. 96]; an impedance plethysmograph signal; a ballistocardiograph signal; and an electrocardiograph signal [par. 5, 99]
Regarding claims 3 and 14, Centen further teaches extracting measurements for the plurality of biomarkers based on the one or more signals collected for the user comprises: identifying one or more features of each signal of the one or more signals collected by the measurement device, wherein a feature represents a characteristic or function of the signal [par. 32, 109]; and extracting a biomarker measurement from one or more features of the one or more signals collected by the measurement device, wherein the biomarker measurement is an aspect of cardiovascular health interpretable by a medical professional [par. 77, 85, 87]
Regarding claims 4 and 15, Centen further teaches extracting measurements for the plurality of biomarkers based on the one or more signals collected for the user comprises: determining measurements for one or more intermittent biomarkers from the one or more signals collected by the measurement device, wherein each intermittent biomarker can be derived from signals collected during a single use of the measurement device [par. 80, 87]; and determining measurements one or more longitudinal biomarkers based on measurements for an intermittent biomarker collected over different time periods, wherein each longitudinal biomarker represents a measurement collected over a time period greater than the single use of the measurement device [par. 30, 135]
Regarding claims 5 and 16, Centen further teaches for each of the plurality of biomarkers, determining a baseline measurement based on one or more of the following: measurements collected for the user during a period when a heart function index computed for the user indicated a low likelihood that the user would experience a heart failure event; or historical measurements collected for the user during a preceding time period [par. 129, 133]
Regarding claim 6, Centen further teaches the heart function model is a machine-learning model, the heart function model trained based on a training data set of biomarker measurements collected for a population of users, each entry of the training data set labeled with a heart failure event [par. 131]
Regarding claim 7, Centen further teaches the training data set is periodically updated with biomarker measurements and heart function indexes computed for subsequent time periods and the heart function model is periodically retrained based on the updated training data set [par. 129]
Regarding claims 8 and 17, Centen further teaches the heart function model comprises a congestion sub-model that computes a congestion index representing a fluid status for the user based on measurements collected for a subset of biomarkers characterizing fluid accumulation [par. 133]
Regarding claims 9 and 18, Centen further teaches determining an accuracy of a biomarker measurement based on the signals collected by the measurement device corresponding to the biomarker measurement [par. 129], wherein signals corresponding to inaccurate biomarker measurements contain regions affected by noise, movement during use of the measurement device, or early termination of use of the measurement device [par. 101, 116]; and responsive to determining the biomarker measurement is inaccurate, removing the biomarker measurement from the plurality of biomarker measurements input to the heart function model [par. 112]
Regarding claim 10, Centen further teaches the alert further comprises a graphic representation of a trend of heart function indices predicted relative to a risk threshold for entering an elevated-risk state and an alert threshold for entering an alert state [par. 120, 122]
Regarding claim 11, Centen further teaches determining the risk state based on comparison of the heart function index to a preceding heart function index [par. 120]
Regarding claims 12 and 19, Centen further teaches comparing the determined heart function index to ta first threshold [par. 120]; determining a rate of change of the heart function index [par. 120]; and responsive to determining the heart function index exceeds the first threshold [par. 120], generating, for transmission, an alert to the user or the clinician, the alert comprising the determined heart function index, the rate of change of the heart function index, and the risk state determined for the user [par. 84, 87, 131].
Regarding claim 13, Centon teaches a non-transitory computer-readable storage medium comprising stored instructions [par. 59], which when executed by at least one processor, cause the processor to [par. 59]: receive, from a measurement device, one or more signals collected for a user of the measurement device during a time period [par. 4, 5], wherein the one or more signals comprising a weight measurement for the user and electrical signals collected through the feet of the user [par. 5, 83]; extract measurements for a plurality of biomarkers based on the one or more signals collected for the user, wherein each biomarker characterizes an aspect of cardiovascular health of the user [par. 5, 99, 131]; apply a heart function model to one or more of (1) the one or more signals collected by the measurement device and (2) the plurality of biomarkers, wherein the heart function model outputs a heart function index that characterizes a likelihood whether the user will experience a heart failure event during a future time period [par. 87, 131-133]; and generate, for transmission to a computing device of a clinician, an alert based on the heart function index, wherein the alert comprises a risk state of the user, the risk state determined based on a comparison of the heart function index to a threshold [par. 76, 84, 120]
Regarding claim 20, Centen teaches a system [par. 6] comprising: a measurement device comprising one or more sensors configured to collect signals for a user of the measurement device during a time period [par. 4, 5], the one or more sensors comprising: a plurality of electrical sensors configured to collect one or more signals through the feet of the user [par. 35]; and one or more load sensors configured to collect a weight measurement of the user [par. 4]; and a non-transitory computer-readable storage medium comprising stored instructions, which when executed by at least one processor [par. 59], cause the processor to: receive, from a measurement device, one or more signals collected for a user of the measurement device during a time period [par. 4, 5], wherein the one or more signals comprising a weight measurement for the user and electrical signals collected through the feet of the user [par. 5, 83]; extract measurements for a plurality of biomarkers based on the one or more signals collected for the user, wherein each biomarker characterizes an aspect of cardiovascular health of the user [par. 5, 99, 131]; apply a heart function model to one or more of (1) the one or more signals collected by the measurement device and (2) the plurality of biomarkers, wherein the heart function model outputs a heart function index that characterizes a likelihood whether the user will experience a heart failure event during a future time period [par. 87, 131-133]; and generate, for transmission to a computing device of a clinician, an alert based on the heart function index, wherein the alert comprises a risk state of the user, the risk state determined based on a comparison of the heart function index to threshold [par. 76, 84, 120]
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GRACE L ROZANSKI whose telephone number is (571)272-7067. The examiner can normally be reached M-F 8:30am-5pm, alt F 8:30am-5pm.
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/GRACE L ROZANSKI/Examiner, Art Unit 3791
/AURELIE H TU/Primary Examiner, Art Unit 3791
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