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 .
Election/Restrictions
Claims 24-30 and 43 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to nonelected Groups I and III, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on November 10th, 2025.
Applicant’s election without traverse of Group II (Claims 31-42) in the reply filed on November 10th, 2025 is acknowledged.
Amendment Entered
In response to the amendment filed on November 10th, 2025, new claims 44-51 are entered. Claims 1-30 and 43 are canceled. Claims 31-42 and 44-51 are currently under examination.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 37, 40, and 49 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 37 recites “wherein the weighted sum weights heart rate variability measurements more heavily according to a likelihood of occurring during a period of slow wave sleep” in lines 1-3. It is unclear as to what “a likelihood of occurring” in line 2 is referring to. Clarification is requested.
Claim 40 recites “at least one of” in lines 1-2. Further in line 2, Claim 40 recites “and”. These two terms conflict one another. Examiner cannot definitively ascertain whether this is an alternative limitation or if both limitations are required. The Examiner will interpret the claim as in the alternative.
Claim 49 recites “a day” in line 3. It is unclear as to whether this limitation is referring to the previously introduced “calendar day” from Claim 46, or a separate element.
Claim 49 recites “a week” in line 3. It is unclear as to whether this limitation is referring to one of the previously introduced “consecutive weeks” from Claim 48, or a separate element.
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 31-42 and 44-51 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Each of Claims 31-42 and 44-51 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 1
Claims 31-42 and 44-51 recite a series of steps or acts for predicting a delivery date for pregnancy. Thus, the claims are directed to a process, which is one of the statutory categories of invention.
Step 2A, Prong 1
Each of Claims 31-42 and 44-51 recites at least one step or instruction for predicting a delivery date for pregnancy, which is grouped as a mental process under the 2019 PEG or a certain method of organizing human activity under the 2019 PEG. The claims recite abstract ideas in the form of mental processes, as consistent with Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66 (2012). If a claim, under its broadest reasonable interpretation, covers performance in the mind but for the recitation of generic computer components, then it is still in the mental processes category unless the claim cannot practically be performed in the mind, see Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318 (Fed. Cir. 2016). Determining a predicted delivery date based on the calculation of heart rate data may be performed by a human. The step of acquiring heart rate data from a wearable monitor is categorized as a data-gathering step, which is considered insignificant extra-solution activity.
Accordingly, each of Claims 31-42 and 44-51 recites an abstract idea.
Specifically, Claim 31 recites:
acquiring heart rate data from a wearable monitor worn by a user during a pregnancy of the user;
calculating a history of a heart rate metric for the user during the pregnancy based on the heart rate data; and
determining a predicted delivery date for the pregnancy based on a trend in the history of the heart rate metric for the user.
Further, dependent Claims 32-42 and 44-51 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed. Accordingly, each of the above-identified claims recites an abstract idea.
Step 2A, Prong 2
The above-identified abstract idea in each of independent Claim 31 (and its dependent Claims 32-42 and 44-51) is not integrated into a practical application under 2019 PEG because the additional elements (identified above in independent Claim 31), either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the additional elements of: “wearable monitor” in independent Claim 31 and “user device” in dependent Claim 44 are generically recited elements in the claims which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above in independent Claim 31 (and its dependent Claims 32-42 and 44-51) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer. In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claim 31 (and its dependent Claims 32-42 and 44-51) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claim 31 (and its dependent Claims 32-42 and 44-51) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 31-42 and 44-51 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of: “wearable monitor” in independent Claim 31 and “user device” in dependent Claim 44. The above-identified additional elements are generically claimed components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks and/or obtain data through data-gathering steps. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Those in the relevant field of art would recognize the above-identified additional elements as being well-understood, routine, and conventional means for data-gathering and computing, as demonstrated by the Applicant’s specification (e.g. paragraphs [0103-113]) which discloses that the processor(s) comprise generic computer components that are configured to perform the generic computer functions (e.g. calculating and determining) that are well-understood, routine, and conventional activities previously known to the pertinent industry; the Applicant’s Background in the specification; and the non-patent literature of record in the application.
Accordingly, in light of Applicant’s specification, the term “processor” is reasonably construed as a generic computing device. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the “processor”. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Claims 31-42 and 44-51 amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the method of Claims 31-42 and 44-51 are directed to applying an abstract idea as identified above on a general purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 31-42 and 44-51 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claim 31 (and its dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 31-42 and 44-51 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 31-42 and 44-51 amounts to significantly more than the abstract idea itself. Accordingly, Claims 31-42 and 44-51 are not patent eligible and rejected under 35 U.S.C. 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 31-34, 38-42, and 44-49 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bilic et al (WO2020229656A1; cited by Applicant).
Regarding Claim 31, Bilic discloses a method (system and method for precise determination of a date of childbirth with a wearable device; Abstract) comprising:
acquiring heart rate data from a wearable monitor (wearable device 1) worn by a user during a pregnancy of the user (Figure 1: shows a schematic illustration of an electronic system according to the invention for detecting the heart rate and further parameters related to the pregnancy of a person, the electronic system comprising a wearable device, in particular a wrist-worn bracelet, with an analysing module comprising a processor in the wearable device and/or in an external system; Page 15 Lines 10-14);
calculating a history of a heart rate metric for the user during the pregnancy based on the heart rate data (As illustrated schematically in Figure 1, the wearable device 1 comprises several sensor systems 100, including the first sensor system 101 with optical sensors configured to generate photoplethysmography (PPG) signals for measuring heart signals, heart rate, heart rate variability, perfusion, and breathing rate. For example, sensor system 101 comprises a PPG-based sensor system for measuring heart signals, heart rate and heart rate variability as described in Simon Arberet et al., "Photoplethysmography-Based Ambulatory Heartbeat Monitoring Embedded into a Dedicated Bracelet", Computing in Cardiology 2013; 40:935-938, included herewith by reference in its entirety; Page 16 Lines 24-32; the heart rate variability of the pregnant person is measured using the wearable device 1. Specifically, in the state of the device 1 being worn, e.g. on the wrist, the processor 13 of the wearable device 1 reads or receives from the first sensor system 101 the current heart rate variability of the pregnant person. The processor 13 stores the heart rate variability (value) in the data storage 12 together with a time stamp, including the current time and date…preferably, the measurements of the heart rate, the heart rate variability, and the acceleration of the pregnant person are performed concurrently. The measurements of the first and the second sensor system 101, 102 are performed periodically, for example the first sensor system 101 uses the optical sensors to measure the heart rate and heart rate variability every couple of milliseconds; Column 19 Lines 3-20); and
determining a predicted delivery date for the pregnancy based on a trend in the history of the heart rate metric for the user (In Figure 2 box 200 relates to physiological parameters and other factors, including vascular activity and body movement of the pregnant person, which are used for determining and predicting the date of giving birth with the electronic system according to the invention, particularly by using the first and the second sensor system 101, 102; Page 18 Lines 21-25).
Regarding Claim 32, Bilic discloses wherein determining the predicted delivery date includes identifying an inflection point in the history of the heart rate metric and calculating the predicted delivery date to occur a predetermined number of days after the inflection point (As seen in Figure 3, determination of the date of delivery can be calculated as the date of onset of a decrease in heart rate in the third trimester plus 5.5 weeks +/- 0.5 weeks; Page 21 Lines 1-3).
Regarding Claim 33, Bilic discloses wherein the history of the heart rate metric includes a history of heart rate variability for the user during the pregnancy (the heart rate of the pregnant person wearing the wearable device 1 is measured using the wearable device 1. Specifically, in the state of the device 1 being worn, e.g. on the wrist, the processor 13 of the wearable device 1 reads or receives from the first sensor system 101 the current heart rate of the pregnant person. The processor 13 stores the heart rate (value) in the data storage 12 together with a time stamp, including the current time and date; Page 18 Line 30 – Page 19 Line 2).
Regarding Claim 34, Bilic discloses wherein each of a number of heart rate variability values in the history of heart rate variability is calculated based on an aggregation of individual heart rate variability measurements acquired during a period of sleep by the user (The measurements of the first and the second sensor system 101, 102 are performed periodically, for example the first sensor system 101 uses the optical sensors to measure the heart 20 rate and heart rate variability every couple of milliseconds. In an embodiment, the periodic measurements are limited to specific time intervals, e.g. during night time, when the pregnant person sleeps, such that the heart rate is measured during sleeр phases only; Page 19 Lines 17-23).
Regarding Claim 38, Bilic discloses wherein the history of the heart rate metric includes a history of resting heart rate measurements for the user during the pregnancy (This allows the electronic system to detect phases of rest of the pregnant person, such that sleep phases can be detected. During sleep phases the heart rate can be detected and shows less inter-day variability, as the person is at rest; Page 9 Lines 27-29; the sleep phases of the pregnant person are determined by evaluating a heart rate variability and/or sensor signals indicative of a resting state pregnant person, such as acceleration. This embodiment allows distinguishing active phases and resting phases of the pregnant person such as to obtain more reliable measurements; Page 13 Line 27 – Page 14 Line 2; In step S5, the heart rate variability and the acceleration are used (by the processor 13 of the wearable device and/or by the processor(s) 30, 40 of the computer system 3 and/or the mobile communication device 4) to detect sleep phases with a resting pulse. Detecting sleep phases with resting pulse allows detecting the heart rate each night in the same state of activity of the pregnant person…the processor(s) 13, 30, 40 determine changes of the heart rate, i.e. changes in the duration of the interval between individual heart beats, respectively, that occur during the detected sleep phases with resting pulse; Page 20 Lines 12-27).
Regarding Claim 39, Bilic discloses wherein calculating the history of the heart rate metric includes calculating a weekly sequence of seven day moving medians for the heart rate metric based on the heart rate data (The filtered set of heart rates might comprise an average, a cumulant and/or a statistical set of heart rates, such as a specific percentile of the heart rate distribution, which is for example calculated for each day, and/or for each week; Page 7 Lines 22-24).
Regarding Claim 40, Bilic discloses wherein the heart rate metric includes at least one of a heart rate variability for the user and a resting heart rate for the user (This allows the electronic system to detect phases of rest of the pregnant person, such that sleep phases can be detected. During sleep phases the heart rate can be detected and shows less inter-day variability, as the person is at rest; Page 9 Lines 27-29; the sleep phases of the pregnant person are determined by evaluating a heart rate variability and/or sensor signals indicative of a resting state pregnant person, such as acceleration. This embodiment allows distinguishing active phases and resting phases of the pregnant person such as to obtain more reliable measurements; Page 13 Line 27 – Page 14 Line 2; In step S5, the heart rate variability and the acceleration are used (by the processor 13 of the wearable device and/or by the processor(s) 30, 40 of the computer system 3 and/or the mobile communication device 4) to detect sleep phases with a resting pulse. Detecting sleep phases with resting pulse allows detecting the heart rate each night in the same state of activity of the pregnant person…the processor(s) 13, 30, 40 determine changes of the heart rate, i.e. changes in the duration of the interval between individual heart beats, respectively, that occur during the detected sleep phases with resting pulse; Page 20 Lines 12-27).
Regarding Claim 41, Bilic discloses wherein determining the predicted delivery date includes locating an inflection point in the heart rate metric from a first timewise decreasing value to a second timewise increasing value (As seen in Figure 3, determination of the date of delivery can be calculated as the date of onset of a decrease in heart rate in the third trimester plus 5.5 weeks +/- 0.5 weeks…after conception the heart rate increases to a local maximum around week 5-6 followed by a short period of a decrease. Starting from week 10, the heart rates in all groups increase approximately until week 30 after conception. Depending on the date of childbirth a period 50 of decreasing heart rates indicated by the boxed region follows to the maximum heart rate around week 30; Page 21 Lines 1-17).
Regarding Claim 42, Bilic discloses wherein determining the predicted delivery date includes calculating the predicted delivery date at a predetermined number of days after the inflection point (As can been seen in all groups after conception the heart rate increases to a local maximum around week 5-6 followed by a short period of a decrease. Starting from week 10, the heart rates in all groups increase approximately until week 30 after conception. Depending on the date of childbirth a period 50 of decreasing heart rates indicated by the boxed region follows to the maximum heart rate around week 30. Obviously it is possible to differentiate between the decrease around week 10 and 30, simply by providing an approximate date of conception. The electronic system and method is configured such that the onset of said period is detected and a prediction of the date of childbirth becomes possible…a probability (confidence information) for each possible week of delivery can be given such that the pregnant person is able to put the determined date of childbirth in perspective. The electronic system and the method according to the invention allows for a novel, reliable and non-invasive way of predicting the date of childbirth; Page 21 Line 1 – Page 22 Line 14).
Regarding Claim 44, Bilic discloses comprising transmitting a notification to a user device of the user identifying the predicted delivery date (the predicted date of childbirth or a symbol being indicative of the date of childbirth or its approach is displayed to the pregnant person, e.g. on a mobile device such as a mobile phone; Page 14 Lines 12-14).
Regarding Claim 45, Bilic discloses comprising calculating a plurality of heart rate variability measurements (The measurements of the first and the second sensor system 101, 102 are performed periodically, for example the first sensor system 101 uses the optical sensors to measure the heart rate and heart rate variability every couple of milliseconds; Page 19 Lines 17-20).
Regarding Claim 46, Bilic discloses wherein calculating the history of the heart rate metric includes identifying a number of periods of sleep for the user during the pregnancy based on data from the wearable monitor, each of the number of periods of sleep associated with a calendar day (In step S5, the heart rate variability and the acceleration are used (by the processor 13 of the wearable device and/or by the processor(s) 30, 40 of the computer system 3 and/or the mobile communication device 4) to detect sleep phases with a resting pulse. Detecting sleep phases with resting pulse allows detecting the heart rate each night in the same state of activity of the pregnant person. The sleep phases are detected, for example, by combining the measurements of the heart rate variability and acceleration as described by Renevey et al. cited above. In a simplified embodiment, the sleep phase is determined without using the measured acceleration and the second sensor system at all, for example based on a user-defined sleep interval, e.g. between 3:00 am and 4:00 am; Page 20 Lines 12-21).
Regarding Claim 47, Bilic discloses comprising during each of the number of periods of sleep for the user, calculating a plurality of heart rate variability measurements over a plurality of intervals (In step S5, the heart rate variability and the acceleration are used (by the processor 13 of the wearable device and/or by the processor(s) 30, 40 of the computer system 3 and/or the mobile communication device 4) to detect sleep phases with a resting pulse. Detecting sleep phases with resting pulse allows detecting the heart rate each night in the same state of activity of the pregnant person. The sleep phases are detected, for example, by combining the measurements of the heart rate variability and acceleration as described by Renevey et al. cited above. In a simplified embodiment, the sleep phase is determined without using the measured acceleration and the second sensor system at all, for example based on a user-defined sleep interval, e.g. between 3:00 am and 4:00 am; Page 20 Lines 12-21).
Regarding Claim 48, Bilic discloses comprising aggregating the plurality of heart rate variability measurements into a plurality of weekly multi-day medians for heart rate variability for each of a plurality of consecutive weeks (The filtered set of heart rates might comprise an average, a cumulant and/or a statistical set of heart rates, such as a specific percentile of the heart rate distribution, which is for example calculated for each day, and/or for each week; Page 7 Lines 22-24).
Regarding Claim 49, Bilic discloses wherein determining the predicted delivery date includes identifying an inflection point in the plurality of heart rate variability measurements at a day of a week where the weekly multi-day medians (The filtered set of heart rates might comprise an average, a cumulant and/or a statistical set of heart rates, such as a specific percentile of the heart rate distribution, which is for example calculated for each day, and/or for each week; Page 7 Lines 22-24) for the plurality of heart rate variability measurements change from a timewise decreasing value to a timewise increasing value (As seen in Figure 3, determination of the date of delivery can be calculated as the date of onset of a decrease in heart rate in the third trimester plus 5.5 weeks +/- 0.5 weeks…As can been seen in all groups after conception the heart rate increases to a local maximum around week 5-6 followed by a short period of a decrease. Starting from week 10, the heart rates in all groups increase approximately until week 30 after conception. Depending on the date of childbirth a period 50 of decreasing heart rates indicated by the boxed region follows to the maximum heart rate around week 30; Page 21 Lines 1-17).
Claim Rejections - 35 USC § 103
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 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.
Claims 35-37 and 50-51 are rejected under 35 U.S.C. 103 as being unpatentable over Bilic et al in view of Capodilupo et al (U.S. Publication No. 2019/0110755).
Regarding Claim 35, Bilic fails to disclose wherein each of a number of heart rate variability values in the history of heart rate variability is calculated as a weighted sum of the individual heart rate variability measurements.
In a similar technical field, Capodilupo teaches applied data quality metrics for physiological measurements (Abstract), wherein each of a number of heart rate variability values in the history of heart rate variability is calculated as a weighted sum of the individual heart rate variability measurements (The recovery score is customized and adapted for the unique physiological properties of the user and takes into account, for example, the user's heart rate variability (HRV)…the recovery score is a weighted combination of the user's heart rate variability (HRV), resting heart rate, sleep quality indicated by a sleep score, and recent strain (indicated, in one example, by the intensity score of the user)…by considering sleep and HRV alone or in combination; [0096]; the quality of heart rate data may be evaluated prior to selecting a particular moment or window of heart rate data for calculating heart rate variability, and the method 600 may include using this quality data to select suitable values for calculating a recovery score. For example, the method 600 may include calculating the heart rate variability for a window of predetermined duration within the slow wave sleep period having the highest quality of heart rate data according to the data quality metric; [0120]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the teachings of Capodilupo into the invention of Bilic in order to ensure that the highest quality of heart rate data is used to provide an accurate and consistent basis for further calculations (Capodilupo [0120]).
Regarding Claim 36, Bilic fails to disclose wherein the weighted sum weights heart rate variability measurements more heavily toward an end of the period of sleep.
In a similar technical field, Capodilupo teaches applied data quality metrics for physiological measurements (Abstract), wherein the weighted sum weights heart rate variability measurements more heavily toward an end of the period of sleep (As shown in step 612, the method 600 may include calculating a heart rate variability of the user at a moment in a last phase of sleep preceding the waking event based upon the heart rate data…an average heart rate variability or similar metric may be determined for any number of discrete measurements within a window around the time of interest; [0117-0118]; As shown in step 618, the method 600 may include evaluating a quality of heart rate data using a data quality metric for a slow wave sleep period, e.g., the slow wave sleep period occurring most recently before the waking event. As noted above, the quality of heart rate measurements may vary over time for a variety of reasons. Thus the quality of heart rate data may be evaluated prior to selecting a particular moment or window of heart rate data for calculating heart rate variability, and the method 600 may include using this quality data to select suitable values for calculating a recovery score. For example, the method 600 may include calculating the heart rate variability for a window of predetermined duration within the slow wave sleep period having the highest quality of heart rate data according to the data quality metric; [0120]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the teachings of Capodilupo into the invention of Bilic because the use of a heart rate variability measurement from the last phase of sleep provides an accurate and consistent basis for evaluating the user (Capodilupo [0120]).
Regarding Claim 37, Bilic fails to disclose wherein the weighted sum weights heart rate variability measurements more heavily according to a likelihood of occurring during a period of slow wave sleep.
In a similar technical field, Capodilupo teaches applied data quality metrics for physiological measurements (Abstract), wherein the weighted sum weights heart rate variability measurements more heavily according to a likelihood of occurring during a period of slow wave sleep (As shown in step 612, the method 600 may include calculating a heart rate variability of the user at a moment in a last phase of sleep preceding the waking event based upon the heart rate data…an average heart rate variability or similar metric may be determined for any number of discrete measurements within a window around the time of interest; [0117-0118]; As shown in step 618, the method 600 may include evaluating a quality of heart rate data using a data quality metric for a slow wave sleep period, e.g., the slow wave sleep period occurring most recently before the waking event. As noted above, the quality of heart rate measurements may vary over time for a variety of reasons. Thus the quality of heart rate data may be evaluated prior to selecting a particular moment or window of heart rate data for calculating heart rate variability, and the method 600 may include using this quality data to select suitable values for calculating a recovery score. For example, the method 600 may include calculating the heart rate variability for a window of predetermined duration within the slow wave sleep period having the highest quality of heart rate data according to the data quality metric; [0120]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the teachings of Capodilupo into the invention of Bilic because the use of a heart rate variability measurement from the slow wave sleep provides an accurate and consistent basis for evaluating the user (Capodilupo [0120]).
Regarding Claim 50, Bilic fails to disclose wherein aggregating the plurality of heart rate variability measurements into the heart rate variability includes calculating a weighted sum of the plurality of heart rate variability measurements.
In a similar technical field, Capodilupo teaches applied data quality metrics for physiological measurements (Abstract), wherein aggregating the plurality of heart rate variability measurements into the heart rate variability includes calculating a weighted sum of the plurality of heart rate variability measurements (The recovery score is customized and adapted for the unique physiological properties of the user and takes into account, for example, the user's heart rate variability (HRV)…the recovery score is a weighted combination of the user's heart rate variability (HRV), resting heart rate, sleep quality indicated by a sleep score, and recent strain (indicated, in one example, by the intensity score of the user)…by considering sleep and HRV alone or in combination; [0096]; the quality of heart rate data may be evaluated prior to selecting a particular moment or window of heart rate data for calculating heart rate variability, and the method 600 may include using this quality data to select suitable values for calculating a recovery score. For example, the method 600 may include calculating the heart rate variability for a window of predetermined duration within the slow wave sleep period having the highest quality of heart rate data according to the data quality metric; [0120]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the teachings of Capodilupo into the invention of Bilic in order to ensure that the highest quality of heart rate data is used to provide an accurate and consistent basis for further calculations (Capodilupo [0120]).
Regarding Claim 51, Bilic fails to disclose wherein the weighted sum weights the plurality of heart rate variability measurements more heavily toward an end of each sleep period.
In a similar technical field, Capodilupo teaches applied data quality metrics for physiological measurements (Abstract), wherein the weighted sum weights the plurality of heart rate variability measurements more heavily toward an end of each sleep period (As shown in step 612, the method 600 may include calculating a heart rate variability of the user at a moment in a last phase of sleep preceding the waking event based upon the heart rate data…an average heart rate variability or similar metric may be determined for any number of discrete measurements within a window around the time of interest; [0117-0118]; As shown in step 618, the method 600 may include evaluating a quality of heart rate data using a data quality metric for a slow wave sleep period, e.g., the slow wave sleep period occurring most recently before the waking event. As noted above, the quality of heart rate measurements may vary over time for a variety of reasons. Thus the quality of heart rate data may be evaluated prior to selecting a particular moment or window of heart rate data for calculating heart rate variability, and the method 600 may include using this quality data to select suitable values for calculating a recovery score. For example, the method 600 may include calculating the heart rate variability for a window of predetermined duration within the slow wave sleep period having the highest quality of heart rate data according to the data quality metric; [0120]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the teachings of Capodilupo into the invention of Bilic because the use of a heart rate variability measurement from the last phase of sleep provides an accurate and consistent basis for evaluating the user (Capodilupo [0120]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHANEL J YOON whose telephone number is (571) 272-2695. The examiner can normally be reached on Monday-Friday 9:00AM-5:00PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexander Valvis can be reached on 571-272-4233. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/CHANEL J YOON/Examiner, Art Unit 3791 /ALEX M VALVIS/Supervisory Patent Examiner, Art Unit 3791