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 .
Response to Amendment
This Office Action is responsive to the amendment filed on 11/05/2025. As directed by the amendment: Claims 1-18 have been amended, and claims 19-20 have been added. Thus, claims 1-20 are presently under consideration in this application.
Response to Arguments
Applicant's arguments, see pages 9-10, filed 11/05/2025, regarding 35 U.S.C. 112(b) and objections have been fully considered but they are persuasive. Amendments obviate the rejection of record. Therefore, the rejection and objection have been withdrawn.
Applicant's arguments, see page 10, filed 11/05/2025, regarding 35 U.S.C. 112(a) have been fully considered but they are not persuasive. The amendments do not obviate the rejection of record. The instant specification is unknown what is used within those feature values to make the determination of the fatigue level, and how they are used to determine what is normal versus outside then normal range for fatigue level. For example, what physical capacity would produce a sever, medium, and low fatigue level. Further, the instant specification fails to detail the way in which each of the machine learning models is used in their distinctive manner. It is further unknown what is inputted and outputted to the machine learning model to obtain the fatigue level. Therefore, the rejection is maintained.
Applicant's arguments, see pages 10-13, filed 11/05/2025, regarding 35 U.S.C. 101 have been fully considered but they are not persuasive.
Applicant argues on page 11 that “Applicant respectfully submits that a human mind is physically incapable of receiving acceleration data from a terminal device, where the acceleration data is from three-axis acceleration sensor sampling at a constant rate. To the extent that the Office attempts to maintain the rejection Applicant respectfully requests that the Office explain how a human mind is physically capable of the recited claim language. Applicant notes that the Examples in the USPTO 101 guidelines focus on whether the features of the claim can be practically performed in the human mind, e.g. Example 37, claims 1 and 2; Example 38, claim 1; and Example 39.”
Examiner disagrees. The comparing of an acceleration data with a first and second predetermined rule 1 and 2 can be performed by the human mind by analyzing the data, and the calculation of an integral value, via integration, is a basic calculation that can be done on pen and paper. The calculating of feature values based on biological data and estimation of fatigue level are extracting features from a signal, that a human can do, and the estimation of fatigue level can also be determined by a human. The examples provided by Applicant are not the same field of endeavor, and therefore not pertinent to the instant claims.
Applicant then argues on page 11 that “the amended claim further at least integrates the asserted judicial exception into a practical application by including a specific type of acceleration sensor. This particular machine is used for capturing the acceleration data that is used as the basis for all operations in the claim language. MPEP 2106.04(d) states "in Step 2A Prong Two, examiners should ensure that they give weight to all additional elements, whether or not they are conventional, when evaluating whether a judicial exception has been integrated into a practical application. Additional elements that represent well-understood, routine, conventional activity may integrate a recited judicial exception into a practical application." (Emphasis added).”
Examiner disagrees because the use of accelerometers are well-understood, routine, and conventional, as shown in for determining sleep and awake state.
Applicant argues on pages 11-12 that “In addition, non-limiting examples in the specification explain that biological data
depends on the state of the autonomous nerve system as well as the fatigue level, and that
biological data also fluctuates depending on the state of activity of the person, in addition to the
fatigue level and the state of the autonomous nerve system. (USPTO's publication of the current
application at paragraph 0005). The non-limiting aspects of the specification further explain that
with prior art approaches, accurately estimate the fatigue level from the biological data is
difficult due to the multiple factors that contribute to the biological data. In order to accurately estimate the fatigue level in the claim language, a determination is made regarding whether the subject is in a sleeping state in order to isolate and exclude data that causes the fatigue level to fluctuate, such as the autonomous nerve system.”
Applicant is asserting the abstract idea itself as the improvement. However, the abstract idea cannot be an “additional element” that shows integration into a practical application. The order of calculations and the particular calculations claimed do not make the abstract idea any less abstract. The claims are currently structured as simply using a generic computer to implement the abstract idea (mental process), which is not enough to show a practical application.
Applicant then argues on page 11 that “The claims language clearly recites
integration with physical sensor hardware. This is not a generic computer implementation. The
claims recite specific interactions with terminal devices and three-axis acceleration sensors to
obtain acceleration data and biological data, specific processing of that acceleration data using
predetermined rules to identify particular physiological states (sleeping VS. awake), and
extraction of biological data only during specific activity states identified through this technical
process involving physical sensor measurements.”
Examiner disagrees since the processing of data on a microcontroller unit is merely performing this process on a generic computer structure. The transmitting of signals is simply a generic computer function performed by a generic computer structure, wherein implementing the abstract idea with a generic computer is not enough to show integration into a practical application or significantly more than the abstract idea itself. The transmission of data to and from the sensor systems is merely data gathering, which is insignificant extra-solution activity.
Applicant argues on pages 11-12 that “The claim language improves the functioning of biological monitoring systems by
providing a technical solution to the problem of obtaining reliable biological data for fatigue
estimation. The fatigue level is estimated using only the biological data obtained when the
subject is in a specific activity state. As mentioned above, the biological data that is used does
not include any component that causes the fatigue level to fluctuate, which improves the
accuracy of the output. Thus, the recited claim language provides an improvement in a technical
field other than computers.”
Applicant is asserting the abstract idea itself as the improvement. However, the abstract idea cannot be an “additional element” that shows integration into a practical application. The order of calculations and the particular calculations claimed do not make the abstract idea any less abstract. The claims are currently structured as simply using a generic computer to implement the abstract idea (mental process), which is not enough to show a practical application.
Therefore, the rejection of record is maintained.
Applicant’s arguments, see pages 13-15, filed 11/05/2025, with respect to the rejection(s) of the claim(s) under 35 U.S.C. 102 and 103 have been fully considered and are persuasive. The amendments to the claims obviate the rejection of record. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Huang et al. (US 20220039677)(Hereinafter Huang) in view of Thein et al. (WO 2016108751 A1)(Hereinafter Thein).
Claim Rejections - 35 USC § 112
Claims 6, 12, and 18 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.
Similarly, original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection IV.
When examining computer-implemented functional claims, examiners should determine whether the specification discloses the computer and the algorithm (e.g., 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 possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as "a finite sequence of steps for solving a logical or mathematical problem or performing a task." Microsoft Computer Dictionary (5th ed., 2002). Applicant may “express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure." Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340 (Fed. Cir. 2008) (internal citation omitted).It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015).
Claims 6, 12, and 18 fail to sufficiently describe the usage of the machine learning model in enough detail for one skilled in the art to understand how the inventor intended the function to be performed to show possession of the claimed invention. The mere statement and recitation of the equation “estimate the fatigue level of the subject by inputting the calculated feature value into a trained machine learning model” of claims 6, 12, 18 and [0051]-[0054] and the usage of models such as linear regression, logistic regression, a support vector machine, a decision tree, a regression tree, and a neural network in [0055] of PG PUB (US 20230397890) of the instant specification provides insufficient detail to the type of data that is used to train the model for determining the fatigue level. Simply reciting the “training data can be obtained from answers to a questionnaire, physical capacity (jump height, maximum speed, range of motion of joints, etc.)” in [0053] of the instant specification is unknown what is used within those feature values to make the determination of the fatigue level, and how they are used to determine what is normal versus outside then normal range for fatigue level. For example, what physical capacity would produce a sever, medium, and low fatigue level. Further, the instant specification fails to detail the way in which each of the machine learning models is used in their distinctive manner. It is further unknown what is inputted and outputted to the machine learning model to obtain the fatigue level. Therefore, claims 6, 12, and 18 do not provide sufficient detail for one to replicate and understand the intended function to show possession of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 112, 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(s), at the time the application was filed, had possession of the claimed invention. This is a new matter rejection.
Claims 1, 7, and 13 has been amended to include the limitation, "determine whether a subject is in a sleeping state based on a comparison between changes in the first acceleration data and a first predetermined rule". The limitation does not have support in the instant specification nor in the parent application.
The specification provides support for ratio th1 complying with reference rule 1 ([0099]), specifically, the ratio is determined from this calculation th1 (=ACC.sub.j/ACC.sub.j-1) ([0098]). However, the specification does not provide support for the comparison of rule 1 with changes in first acceleration data. Applicant has not indicated where the disclosure provides adequate written description support for the instant claim limitation, "determine whether a subject is in a sleeping state based on a comparison between changes in the first acceleration data and a first predetermined rule”. Therefore, the new claim limitations introduce new matter.
Claims 1-20 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.
Similarly, original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection IV.
Merely recite a description of the problem to be solved while claiming all solutions to it, leaving the industry to “complete an unfinished invention.” See Ariad, 598 F.3d at 1353
Disclosure of function alone is little more than a wish possession. See MPEP 2163(II)(A)(3)(a).
The written description requirement is not satisfied by merely outlining the goals or results one hopes to achieve with the invention. See MPEP 2163(II)(A)(3)(a).
Claims 1, 7, and 13 fail to sufficiently describe the reference/predetermined rule 1, reference/predetermined rule 2, first comparison, and second comparison to have sufficient written description. The mere statement and recitation of the analyzing of the reference/predetermined rule 1, reference/predetermined rule 2, first comparison, and second comparison in claims 1, 7, and 13, and in [0097]-[0104] of the instant specification fails to disclose what are the reference/predetermined rule 1 and reference/predetermined rule 2 are and how they are determined. Furthermore, the instant specification provides insufficient detail as to what the comparisons are, and if the comparison is between a threshold, a criterion, a value, and what does this reference/predetermined rule 1 and reference/predetermined rule 2 represent. Therefore, claims 1-20 do not provide sufficient detail for one to have sufficient written description.
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 1-20 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 1 recites the limitation "the acceleration data" in line 10. There is insufficient antecedent basis for this limitation in the claim. It is unclear if the claim should recite the first or second acceleration data.
Claim 7 recites the limitation "the acceleration data" in line 10. There is insufficient antecedent basis for this limitation in the claim. It is unclear if the claim should recite the first or second acceleration data.
Claim 13 recites the limitation "the acceleration data" in line 10. There is insufficient antecedent basis for this limitation in the claim. It is unclear if the claim should recite the first or second acceleration data.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Each of independent claims 1, 7, and 13 recites a step calculating a feature value of the biological data, based on the extracted biological data obtained when the subject is in a specific activity state… estimating a fatigue level indicating a level of fatigue of the subject, based on the calculated feature value, which is a mental process. This judicial exception is not integrated into a practical application because the generically recited computer elements (ie. a memory and processor), determining values, and estimating fatigue level do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations are to receiving data, processing data, and estimating fatigue level, which are all well-understood, routine, and conventional computer functions. See MPEP § 2106.05(d).
MPEP 2106(III) outlines steps for determining whether a claim is directed to statutory subject
matter. The stepwise analysis for the instant claim is provided here.
Step 1 – Statutory categories
Claim 1 is directed to a system (i.e. machine) and thus meets the step 1 requirements.
Claim 7 is directed to a method and thus meets the step 1 requirements.
Claim 13 is directed to a tangible non-transitory computer-readable medium (i.e. a product), and
thus, meets the step 1 requirements.
Step 2A – Prong 1 – Judicial exception (j.e.)
Regarding claims 1, 7, and 13, the following step is an abstract idea:
“determine whether a subject is in a sleeping state based on a comparison between changes in the first acceleration data and a first predetermined rule… calculate an integral value of the acceleration data during a sleeping time duration in which the subject is in the sleeping state; determine whether the subject is changing from the sleeping state to an awake state based on a second comparison between the integral value and a second predetermined rule…calculating a feature value of the biological data, based on the extracted biological data obtained when the subject is in the specific activity state… estimating a fatigue level indicating a level of fatigue of the subject, based on the calculated feature value”, which is a mental process when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(II), the mental process grouping includes observations, evaluations, judgements, and opinions. In this case, a human could calculate a feature value from extracted RRI via power spectral density and estimating fatigue level from the calculations of the feature values .
Step 2A – Prong 2 – additional elements to integrate j.e. into a practical application
Regarding claims 1, 7, and 13, the abstract idea is not integrated into a practical application.
The following claim elements do not add any meaningful limitation to the abstract idea:
- “terminal device”, “a memory”, and “a processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the machine learning model of claims 6, 12, and 18 are by definition automating the human thinking process with a computer.
- “3-axis accelerometer sensor” are data gathering structures for the insignificant extra-solution activity of data gathering [MPEP 2106.05(b)];
- “biological data”, “first and second acceleration data”, “changes”, “first and second predetermined rule”, “first and second comparison”, “awake/sleeping state”, “integral value”, “activity state”, “feature value” and “fatigue level” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
Step 2B – significantly more/inventive concept
The following claim elements do not add any meaningful limitation to the abstract idea:
- “a memory”, and “a processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the machine learning model of claims 6, 12, and 18 are by definition automating the human thinking process with a computer.
- “biological data”, “activity state”, “feature value” and “fatigue level” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
The additional elements of claims 1, 7, and 13, when considered separately and in combination, do not add significantly more (ie. an inventive concept) to the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, the memory and processor, along with their associated functions, are recited at a high level of generality and simply amount to implementing the abstract idea on a computer. The ECG sensor are claimed very generically and are used only to gather the data they are designed for. These are well-understood, routine and conventional structure since the diagnostic art in Zhao et al (US 20170258356) teaches the use of ECG/EKG sensors to collect ECG signals ([0006]).
Dependent claims 2-6, 8-12 and 14-20 do not integrate the abstract idea into a practical application and do not add significantly more to the abstract idea of claim 1 and 10. The dependent claim limitations are directed to processing of data and mental processes (claims 2-6, 8-12, and 14-18), extra-solution activity (claim 20 of transferring data.) and a mathematical concept (claim 19) which are insignificant extra-solution activity and do not amount to more than what is well-understood, routine, and conventional.
In summary, claims 1-20 are directed to an abstract idea without significantly more and, therefore, are patent ineligible.
Claim Interpretation
Regarding claim 7, the phrases “determining whether a subject is in a sleeping state based on a comparison between changes in the first acceleration data and a first predetermined rule; receiving, in response to a determination that the subject is in the sleeping state, second acceleration data from the terminal device; determining whether the subject is changing from the sleeping state to an awake state based on a second comparison between the integral value and a second predetermined rule;” are conditional limitations.
“The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met.” “The broadest reasonable interpretation of a system (or apparatus or product) claim having structure that performs a function, which only needs to occur if a condition precedent is met, requires structure for performing the function should the condition occur.” Note the phrase, “whether a subject is in a sleeping state based on a comparison… in response to a determination that the subject is in the sleeping state… whether the subject is changing from the sleeping state to an awake state” in claim 7 is conditional language, that is, if a condition precedent in a method claim is not met, the conditional steps recited in the claim are not required to be performed. The conditions of the threshold may or may not reach that range required. As such, the broadest reasonable interpretation of such a method claim does not include the conditional step along with the steps proceeding the conditional step. See MPEP 2111.04(II).
Examiner notes that the only limitation not affected by the conditional language is “receiving first acceleration data from a terminal device, wherein the first acceleration data is from a three-axis acceleration sensor sampling at a constant rate;” and will be examined as such.
Claim Rejections - 35 USC § 102
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.
Claim(s) 7-10 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Thein et al. (WO 2016108751 A1)(Hereinafter Thein).
Regarding claim 7, Thein teaches receive first acceleration data from a terminal device, wherein the first acceleration data is from a three-axis acceleration sensor sampling at a constant rate (Page 6 lines 20-22 “three stages of wake during sleep, REM sleep, and NREM sleep are calculated simultaneously by using motion data, e.g. an acceleration signal measured by an accelerometer (ACC) sensor or a gyroscope, and physiological signal data” Page 12 lines 14-15 “Fig. 10, acceleration magnitude data is collected from the wrist- worn 3-axis accelerometer at 20 samples per second [constant sampling rate] for the whole sleep duration (step 1002).” Page 14 lines 3-6 “a wearable device 1601 [terminal device] according to an example embodiment, for obtaining physiological measurements from a user and removing artifacts in the physiological measurements. The device 1601 includes a first signal sensing module 1602, such as an accelerometer”). As noted in the claim interpretation, the rest of the claim does not occur as the fatigue level is determined during sleep, which the sleep state is determined based on a condition that is required to be satisfied.
See Ex parte Schulhauser, Appeal 2013-007847 (PTAB April 28, 2016) for an analysis of contingent claim limitations in the context of both method claims and system claims. In Schulhauser, both method claims and system claims recited the same contingent step. When analyzing the claimed method as a whole, the PTAB determined that giving the claim its broadest reasonable interpretation, “[i]f the condition for performing a contingent step is not satisfied, the performance recited by the step need not be carried out in order for the claimed method to be performed” (quotation omitted). Schulhauser at 10. When analyzing the claimed system as a whole, the PTAB determined that “[t]he broadest reasonable interpretation of a system claim having structure that performs a function, which only needs to occur if a condition precedent is met, still requires structure for performing the function should the condition occur.” Schulhauser at 14. Therefore "[t]he Examiner did not need to present evidence of the obviousness of the [ ] method steps of claim 1 that are not required to be performed under a broadest reasonable interpretation of the claim (e.g., instances in which the electrocardiac signal data is not within the threshold electrocardiac criteria such that the condition precedent for the determining step and the remaining steps of claim 1 has not been met);" however to render the claimed system obvious, the prior art must teach the structure that performs the function of the contingent step along with the other recited claim limitations. Schulhauser at 9, 14. See MPEP 2111.04.
Regarding claim 8, Thein teaches detecting an activity state of the subject,
wherein, in the biological data extraction, the biological data obtained when the subject is in a specific activity state is extracted, from the obtained biological data, based on a result of detection by the activity state detection (As noted in the claim interpretation, the rest of the claim does not occur as the fatigue level is determined during sleep, which the sleep state is determined based on a condition that is required to be satisfied.).
Regarding claim 9, Thein teaches wherein, in the activity state detection, when it is detected that an activity state of the subject has changed from asleep to awake (),
in the biological data extraction, biological data corresponding to a set time period immediately before a wake-up time of the subject is extracted, as the biological data obtained when the subject is in a specific activity state (See Ex parte Schulhauser, Appeal 2013-007847 (PTAB April 28, 2016) for an analysis of contingent claim limitations in the context of both method claims and system claims. In Schulhauser, both method claims and system claims recited the same contingent step. When analyzing the claimed method as a whole, the PTAB determined that giving the claim its broadest reasonable interpretation, “[i]f the condition for performing a contingent step is not satisfied, the performance recited by the step need not be carried out in order for the claimed method to be performed” (quotation omitted). Schulhauser at 10. When analyzing the claimed system as a whole, the PTAB determined that “[t]he broadest reasonable interpretation of a system claim having structure that performs a function, which only needs to occur if a condition precedent is met, still requires structure for performing the function should the condition occur.” Schulhauser at 14. Therefore "[t]he Examiner did not need to present evidence of the obviousness of the [ ] method steps of claim 1 that are not required to be performed under a broadest reasonable interpretation of the claim (e.g., instances in which the electrocardiac signal data is not within the threshold electrocardiac criteria such that the condition precedent for the determining step and the remaining steps of claim 1 has not been met);" however to render the claimed system obvious, the prior art must teach the structure that performs the function of the contingent step along with the other recited claim limitations. Schulhauser at 9, 14. See MPEP 2111.04.
“The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met.” “The broadest reasonable interpretation of a system (or apparatus or product) claim having structure that performs a function, which only needs to occur if a condition precedent is met, requires structure for performing the function should the condition occur.” Note the phrase, “when it is detected that an activity state of the subject has changed from asleep to awake” in claim 9 are conditional language, that is, if a condition precedent in a method claim is not met, the conditional steps recited in the claim are not required to be performed. The conditions of the changing of activity state from asleep to awake may not occur. As such, the broadest reasonable interpretation of such a method claim does not include the conditional step along with the steps proceeding the conditional step. See MPEP 2111.04(II).).
Regarding claim 10, Thein teaches wherein, in the activity state detection, when it is detected that the activity state has switched from REM sleep to non-REM sleep, or the activity state has switched from non-REM sleep to REM sleep (),
in the biological data extraction, extracting the biological data corresponding to a set time period immediately before and after a time when the activity state switched, as the biological data obtained when the subject is in a specific activity state (See Ex parte Schulhauser, Appeal 2013-007847 (PTAB April 28, 2016) for an analysis of contingent claim limitations in the context of both method claims and system claims. In Schulhauser, both method claims and system claims recited the same contingent step. When analyzing the claimed method as a whole, the PTAB determined that giving the claim its broadest reasonable interpretation, “[i]f the condition for performing a contingent step is not satisfied, the performance recited by the step need not be carried out in order for the claimed method to be performed” (quotation omitted). Schulhauser at 10. When analyzing the claimed system as a whole, the PTAB determined that “[t]he broadest reasonable interpretation of a system claim having structure that performs a function, which only needs to occur if a condition precedent is met, still requires structure for performing the function should the condition occur.” Schulhauser at 14. Therefore "[t]he Examiner did not need to present evidence of the obviousness of the [ ] method steps of claim 1 that are not required to be performed under a broadest reasonable interpretation of the claim (e.g., instances in which the electrocardiac signal data is not within the threshold electrocardiac criteria such that the condition precedent for the determining step and the remaining steps of claim 1 has not been met);" however to render the claimed system obvious, the prior art must teach the structure that performs the function of the contingent step along with the other recited claim limitations. Schulhauser at 9, 14. See MPEP 2111.04.
“The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met.” “The broadest reasonable interpretation of a system (or apparatus or product) claim having structure that performs a function, which only needs to occur if a condition precedent is met, requires structure for performing the function should the condition occur.” Note the phrase, “when it is detected that the activity state has switched from REM sleep to non-REM sleep, or the activity state has switched from non-REM sleep to REM sleep” in claim 10 are conditional language, that is, if a condition precedent in a method claim is not met, the conditional steps recited in the claim are not required to be performed. The conditions of the activity state switching from REM to NREM or REM to NREM may not occur. As such, the broadest reasonable interpretation of such a method claim does not include the conditional step along with the steps proceeding the conditional step. See MPEP 2111.04(II).).
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) 1-2, 6, 13-14, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (US 20220039677)(Hereinafter Huang) in view of Thein et al. (WO 2016108751 A1)(Hereinafter Thein).
Regarding claims 1 and 13, Huang teaches A fatigue level estimation method/apparatus ([0095] “The wearable device 1110 may include a processor 1111, a memory 1112, a communication module 1113, an input/output module 1114, and at least one sensor 1115 coupled with each other. The memory 1112 may be a non-transitory computer-readable medium.” [0093] “From FIGS. 8-10, subjects with high BFI (e.g., high fatigue level) may have poor sleep quality at night and insufficient daytime rest. The sleep quality of subjects with lower BFI (e.g., lower fatigue level) may be generally better at night, and the resting frequency at daytime varies.”) comprising:
at least one memory storing instructions ([0095] “The wearable device 1110 may include a processor 1111, a memory 1112, a communication module 1113, an input/output module 1114, and at least one sensor 1115 coupled with each other. The memory 1112 may be a non-transitory computer-readable medium.”); and
at least one processor configured to execute the instructions to/A non-transitory computer-readable recording medium on which a program is recorded, the program comprising instructions that cause a computer to carry out ([0095] “The wearable device 1110 may include a processor 1111, a memory 1112, a communication module 1113, an input/output module 1114, and at least one sensor 1115 coupled with each other. The memory 1112 may be a non-transitory computer-readable medium.”):
extracting biological data obtained when a subject is in a specific activity state during the sleeping state (Fig. 2 (201));
calculating a feature value of the biological data, based on the extracted biological data obtained when the subject is in the specific activity state (Fig. 2(205) where the feature value is LF and HF ratio, as seen in Fig. 4(401).); and
estimating a fatigue level indicating a level of fatigue of the subject, based on the calculated feature value (See ratio of LF/HF of Fig. 4(401) used to determine FI (fatigue index) in Fig. 4(409). [0093] “From FIGS. 8-10, subjects with high BFI (e.g., high fatigue level) may have poor sleep quality at night and insufficient daytime rest. The sleep quality of subjects with lower BFI (e.g., lower fatigue level) may be generally better at night, and the resting frequency at daytime varies.”).
However, Shimokawa does not teach receive first acceleration data from a terminal device, wherein the first acceleration data is from a three-axis acceleration sensor sampling at a constant rate, determine whether a subject is in a sleeping state based on a comparison between changes in the first acceleration data and a first predetermined rule, receive, in response to a determination that the subject is in the sleeping state, second acceleration data from the terminal device, calculate an integral value of the acceleration data during a sleeping time duration in which the subject is in the sleeping state, and determine whether the subject is changing from the sleeping state to an awake state based on a second comparison between the integral value and a second predetermined rule. Thein, in the same field of endeavor, teaches a sleep monitoring device for monitoring sleep at different phases (Abstract), and further teaches receive first acceleration data from a terminal device, wherein the first acceleration data is from a three-axis acceleration sensor sampling at a constant rate (Page 6 lines 20-22 “three stages of wake during sleep, REM sleep, and NREM sleep are calculated simultaneously by using motion data, e.g. an acceleration signal measured by an accelerometer (ACC) sensor or a gyroscope, and physiological signal data” Page 12 lines 14-15 “Fig. 10, acceleration magnitude data is collected from the wrist- worn 3-axis accelerometer at 20 samples per second [constant sampling rate] for the whole sleep duration (step 1002).” Page 14 lines 3-6 “a wearable device 1601 [terminal device] according to an example embodiment, for obtaining physiological measurements from a user and removing artifacts in the physiological measurements. The device 1601 includes a first signal sensing module 1602, such as an accelerometer”);
determine whether a subject is in a sleeping state based on a comparison between changes in the first acceleration data and a first predetermined rule (Page 3 lines 26-28 “a processor for detecting the time-to-sleep from the motion data based on a first time-above-threshold (TAT) threshold and a first proportional integration device (PIM) threshold” See Fig. 13 where time-to-sleep occurs.);
receive, in response to a determination that the subject is in the sleeping state, second acceleration data from the terminal device (See Fig. 13 where following the time-to-sleep determination, additional determinations are made at different time windows.);
calculate an integral value of the acceleration data during a sleeping time duration in which the subject is in the sleeping state (Page 10 lines 27-29 “PIM (Proportional Integration Method) integrates the acceleration magnitude signal and calculates the area under the curve using the equation shown in Fig. 9b) in the example embodiment.”);
determine whether the subject is changing from the sleeping state to an awake state based on a second comparison between the integral value and a second predetermined rule (Page 16 lines 18-21 “Detecting the wake periods during sleep from the motion data may comprise dividing the motion data into time windows; determining TAT and PIM scores for each time window, and identifying windows in which the TAT and PIM scores exceed the second TAT threshold and the second PIM threshold.” PIM score greater than second PIM threshold.) to measure sleep stages accurately and effectively with power consumption efficiency, thus reducing battery spent for the wearable device (Page 6 lines 13-15). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Huang, with the receive first acceleration data from a terminal device, wherein the first acceleration data is from a three-axis acceleration sensor sampling at a constant rate, determine whether a subject is in a sleeping state based on a comparison between changes in the first acceleration data and a first predetermined rule, receive, in response to a determination that the subject is in the sleeping state, second acceleration data from the terminal device, calculate an integral value of the acceleration data during a sleeping time duration in which the subject is in the sleeping state, and determine whether the subject is changing from the sleeping state to an awake state based on a second comparison between the integral value and a second predetermined rule of Thein, because such a modification would allow to measure sleep stages accurately and effectively with power consumption efficiency, thus reducing battery spent for the wearable device.
Regarding claim 2 and 14, Huang teaches detecting an activity state of the subject,
wherein, in the biological data extraction, the biological data obtained when the subject is in a specific activity state is extracted, from the obtained biological data, based on a result of detection by the activity state detection ([0029] “The LF/HF ratios from HRV data may be collected from a device with photoplethysmography (PPG) sensors or from a device with ECG sensors.” [0027] “HF power may increase during a fatigue state, whereas LF power may increase during waking state. In non-rapid-eye-movement (non-REM) states, the LF/HF ratio may gradually decrease as sleep deepens. The LH/HF ratio may reflect sleep activity. LF/HF may differentiate between non-REM and REM states. Sleep quality at night and rest frequency during daytime may potentially correspond to fatigue status. A higher fatigue level may cause higher rest frequency during the daytime, affecting sleep quality at night.”).
Regarding claims 6 and 18, Huang teaches estimate the fatigue level of the subject by inputting the calculated feature value into a trained machine learning model ([0067] “Weighting factors α.sub.A, β.sub.A, γ.sub.A, α.sub.B, β.sub.B, γB, α.sub.C, β.sub.C, γ.sub.C may be employed to amplify or reduce the components of the corresponding HRV parameters. The weighting factors may depend on their correlation with FI and their respective value range contributed to FI. When fitting Formula (8) into a multiple linear regression model, the shifting factors ε.sub.A, ε.sub.B, ε.sub.C may correspond to the intercept of the model and may be based on the available dataset.” See equation 11.).
Claim(s) 5 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (US 20220039677)(Hereinafter Huang) in view of Thein et al. (WO 2016108751 A1)(Hereinafter Thein) and Shimokawa et al. (US 20180064387)(Hereinafter Shimokawa).
Regarding claims 5 and 17, claim 1 is anticipated over Huang and Thein. Hunag in view of Thein do not teach wherein, when the biological data is data indicating a heartbeat interval, in the feature value calculation, a feature value indicating a change in a pulse interval for each pulse is calculated. Shimokawa, in the same field of endeavor, teaches determining fatigue during the day using heart rate and sleepiness (Abstract), and further teaches wherein, when the biological data is data indicating a heartbeat interval, in the feature value calculation, a feature value indicating a change in a pulse interval for each pulse is calculated ([0073] “In order to estimate a balance of autonomic nerve from the heartbeat fluctuation, high-frequency fluctuation component (HF component) corresponding to breathing variation and low-frequency component corresponding to Mayer wave which is blood pressure variation [change in a pulse interval for each pulse] are extracted from time-series data about the heartbeat fluctuation, and both sizes are compared.”) to increase accuracy calculation of the fatigue level ([0108]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Hunag in view of Thein, with the biological data is data indicating a heartbeat interval, in the feature value calculation, a feature value indicating a change in a pulse interval for each pulse is calculated of Shimokawa, because such a modification would allow to increase accuracy calculation of the fatigue level.
Claim(s) 11-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Thein et al. (WO 2016108751 A1)(Hereinafter Thein) in view of Shimokawa et al. (US 20180064387)(Hereinafter Shimokawa).
Regarding claim 11, claim 1 is anticipated over Huang and Thein. Hunag in view of Thein do not teach wherein, when the biological data is data indicating a heartbeat interval, in the feature value calculation, a feature value indicating a change in a pulse interval for each pulse is calculated. Shimokawa, in the same field of endeavor, teaches determining fatigue during the day using heart rate and sleepiness (Abstract), and further teaches wherein, when the biological data is data indicating a heartbeat interval, in the feature value calculation, a feature value indicating a change in a pulse interval for each pulse is calculated ([0073] “In order to estimate a balance of autonomic nerve from the heartbeat fluctuation, high-frequency fluctuation component (HF component) corresponding to breathing variation and low-frequency component corresponding to Mayer wave which is blood pressure variation [change in a pulse interval for each pulse] are extracted from time-series data about the heartbeat fluctuation, and both sizes are compared.”) to increase accuracy calculation of the fatigue level ([0108]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Thein, with the biological data is data indicating a heartbeat interval, in the feature value calculation, a feature value indicating a change in a pulse interval for each pulse is calculated of Shimokawa, because such a modification would allow to increase accuracy calculation of the fatigue level.
Regarding claim 12, claim 1 is anticipated over Huang and Thein. Hunag in view of Thein do not teach estimate the fatigue level of the subject by inputting the calculated feature value into a trained machine learning model. Shimokawa, in the same field of endeavor, teaches determining fatigue during the day using heart rate and sleepiness (Abstract), and further teaches estimate the fatigue level of the subject by inputting the calculated feature value into a trained machine learning model ([0115] “In the above classification, “the subject is not tired at all” is indicated as a level 0, “the subject is a bit tired” is indicated as a level 1, “the subject is tired” is indicated as a level 2, “the subject is pretty tired” is indicated as a level 3, and “the subject is very tired” is indicated as a level 4. The sleepiness baseline heart rate is corrected according to the fatigue level as shown in FIG. 10. In a case of an example of FIG. 10, when the fatigue level is 4, 10 is added to the read sleepiness baseline heart rate. The added value becomes the correction sleepiness baseline heart rate. The added correction value is one example. Thus, it is possible to change the correction value by setting appropriately.” Examiner notes that classification is a machine learning model that uses the feature values and fatigue level.) to increase accuracy calculation of the fatigue level ([0108]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Hunag in view of Thein, with the estimate the fatigue level of the subject by inputting the calculated feature value into a trained machine learning model of Shimokawa, because such a modification would allow to increase accuracy calculation of the fatigue level.
Claim(s) 3-4, 15-16, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (US 20220039677)(Hereinafter Huang) in view of Thein et al. (WO 2016108751 A1)(Hereinafter Thein) and Akselrod et al. (US 20060235315)(Hereinafter Akselrod).
Regarding claims 4 and 16, claim 1 is anticipated over Huang and Thein. Hunag in view of Thein do not teach detecting between NREM and REM sleep and extracting biological data corresponding at a set time before and after activity state switch. Akselrod, in the same field of endeavor, teaches using cardiac RR intervals for analysis of different states via power spectrum analysis (Abstract and [0054]), and further teaches wherein, in the activity state detection, when it is detected that the activity state has switched from REM sleep to non-REM sleep, or the activity state has switched from non-REM sleep to REM sleep ([0100] “a REM determinator, for using the Poincare plot to determine the REM sleep and the NREM sleep of the sleeping subject.”),
in the biological data extraction, extracting the biological data corresponding to a set time period immediately before and after a time when the activity state switched, as the biological data obtained when the subject is in a specific activity state ([0100] “being measured over a plurality of epochs, the apparatus comprising: an R-R extractor, for extracting a series of cardiac R-R intervals from the signals; a plotter, for constructing a Poincare plot of the series of cardiac R-R intervals”) to determine the sleep stages of the sleeping subject ([0103]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Hunag in view of Thein, with the detecting between NREM and REM sleep and extracting biological data corresponding at a set time before and after activity state switch of Akselrod, because such a modification would allow to determine the sleep stages of the sleeping subject.
Regarding claims 3 and 15, claim 1 is anticipated over Huang and Thein. Hunag in view of Thein do not teach detecting the change from sleep to wake and extracting biological data corresponding at a set time before wake up. Akselrod, in the same field of endeavor, teaches using cardiac RR intervals for analysis of different states via power spectrum analysis (Abstract and [0054]), and further teaches wherein, in the activity state detection, when it is detected that an activity state of the subject has changed from asleep to awake ([0103] “a SWS determinator for using the time-frequency decomposition to determine at least one SWS period and at least one NSWS period; a SO determinator for determining at least one SO period onset period from the at least one NSWS period; a non-sleep determinator for determining plurality of non-sleep periods from the at least one NSWS period;”),
in the biological data extraction, biological data corresponding to a set time period immediately before a wake-up time of the subject is extracted, as the biological data obtained when the subject is in a specific activity state ([0103] “determining sleep stages from signals of electrical activity recorded of a chest of a sleeping subject, the signals being measured over a plurality of epochs, the apparatus comprising: a R-R extractor for extracting a series of cardiac R-R intervals from the signals; a decomposer, for obtaining a time-frequency decomposition from the series of cardiac R-R intervals;”) to determine the sleep stages of the sleeping subject ([0103]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Hunag in view of Thein, with the detecting the change from sleep to wake and extracting biological data corresponding at a set time before wake up of Akselrod, because such a modification would allow to determine the sleep stages of the sleeping subject.
Regarding claim 19, claim 1 is anticipated over Huang and Thein. Hunag in view of Thein do not teach interpolation on R-R Interval (RRI) data, wherein the RRI data indicates the heartbeat interval, resampling the RRI data at a specified frequency, and performing a Fast Fourier Transform (FFT) on the resampled RRI data to obtain a power spectral density. Akselrod, in the same field of endeavor, teaches using cardiac RR intervals for analysis of different states via power spectrum analysis (Abstract and [0054]), and further teaches wherein the biological data comprises at least one of electrocardiographic signals or pulse waveforms, and the at least one processor is further configured to execute the instructions to:
calculate the feature value to indicate a change in a heartbeat interval based on the biological data by performing:
interpolation on R-R Interval (RRI) data, wherein the RRI data indicates the heartbeat interval (Fig. 8 [0362] “Prior to the step of extracting the RRI series, an optional step of interpolation of the input signals may be performed, so as to compensate missing heart beats of the sleeping subject.”);
resampling the RRI data at a specified frequency ([0503] “The inflection points, used to determine the RWD function (see FIG. 7) were found by upsampling the recorded signal by a factor of 100, taking its first derivative and searching for local maxima and minima of the first derivative in the vicinity of each R-wave peak (since most of power of the QRS signal is contained at frequencies up to 150 Hz, a sample rate of 1000 Hz should be enough to permit full reconstruction and resampling the signal).”); and
performing a Fast Fourier Transform (FFT) on the resampled RRI data to obtain a power spectral density ([0364] “a power spectrum is obtained from the RRI series, preferably by a discrete transform. Either a steady state of a time-dependent discrete transform may be used. Examples of discrete transforms which may be used include, but are not limited to, Fourier transform”) to determine the sleep stages of the sleeping subject ([0103]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Hunag in view of Thein, with the interpolation on R-R Interval (RRI) data, wherein the RRI data indicates the heartbeat interval, resampling the RRI data at a specified frequency, and performing a Fast Fourier Transform (FFT) on the resampled RRI data to obtain a power spectral density of Akselrod, because such a modification would allow to determine the sleep stages of the sleeping subject.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (US 20220039677)(Hereinafter Huang) in view of Thein et al. (WO 2016108751 A1)(Hereinafter Thein) and Mihara et al. (US 20190171282)(Hereinafter Mihara).
Regarding claim 20, claim 1 is anticipated over Huang and Thein. Hunag in view of Thein do not teach output the estimated fatigue level simultaneously to the terminal device and to a third-party terminal device. Mihara, in the same field of endeavor, teaches determining fatigue from a terminal device (Abstract and [0033]), and further teaches output the estimated fatigue level simultaneously to the terminal device and to a third-party terminal device ([0057] “The information on the fatigue may be output by audio through the audio output device 24 instead of the display in the display device 22. In this case, the display in the display device 22 and the output through the audio output device 24 may be simultaneously performed.”) to display information to a user ([0103]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Hunag in view of Thein, with the output the estimated fatigue level simultaneously to the terminal device and to a third-party terminal device of Mihara, because such a modification would allow to display information to a user.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 MOUSSA M HADDAD whose telephone number is (571)272-6341. The examiner can normally be reached M-TH 8:00-6:00.
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/MOUSSA HADDAD/Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/Supervisory Patent Examiner, Art Unit 3796