DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Objections Claim s 1 and 7-8 are objected to because of the following informalities: Claim 1, line 6: “a vital sign” should read --the vital sign-- Claim 7, line 9: “a vital sign” should read --the vital sign-- Claim 8, lines 8-9: “a vital sign” should read --the vital sign-- Appropriate correction is required. 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 1-12 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. Claims 1- 12 are directed to a system and method for obtaining vital signs in a subject , which is an abstract idea. Claims 1-12 do not include additional elements that integrate the exception into a practical application or that are sufficient to amount to significantly more than the judicial exception for the reasons provided below which are in line with the 2014 Interim Guidance on Patent Subject Matter Eligibility (Federal Register, Vol. 79, No. 241, p 74618, December 16, 2014), the July 2015 Update on Subject Matter Eligibility (Federal Register, Vol. 80, No. 146, p. 45429, July 30, 2015), the May 2016 Subject Matter Eligibility Update (Federal Register, Vol. 81, No. 88, p. 27381, May 6, 2016), and the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 4, page 50, January 7, 2019). The analysis of claim 1 is as follows: Step 1: Claim 1 is drawn to a machine . Step 2A: Prong One: Claim 1 recites an abstract idea. In particular, claim 1 recites the following limitations: [A1] “ receiv [ ing ] a first detection signal corresponding to a vital sign of a subject ” ; [B1] “ output [ t ing] a probability that the first detection signal is classified into each of a plurality of classes” [C1] “output [ t ing] data corresponding to a vital sign associated with the first detection signal, the probability that the first detection signal is classified into one of the plurality of classes being equal to or greater than a threshold” This element of claim 1 are drawn to an abstract idea since (1) they involve mathematical concepts in the form of mathematical concepts in the form of mathematical relationships, mathematical formulas or equations, and/or mathematical calculations in [ B 1] and [ C 1]; and/or (2) they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper. Step 2A- Prong Two: Claim 1 does not include additional elements that integrate the mental process into a practical application. The “ first sensor ” limitation do es not integrate the exception into a practical application since they are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). The “inference model” does not integrate the exception into a practical application since it is merely applying a generic, conventional machine learning algorithm to a new environment or dataset without providing a specific, tangible improvement to the underlying technology itself. (see Recentive Analytics, Inc. v. Fox Corp. , Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025)). The “ process or ” does not integrate the exception into a practical application since it is merely an instruction to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f). As a whole, the additional elements merely serve to gather and feed information to the abstract idea and to output a result based on the abstract idea, while generically implementing it on conventionally used tools. There is no practical application because the abstract idea is not applied, relied on, or used in a meaningful way. No improvement to the technology is evident, and the detected signal of the vital sign is not outputted and classified in any way such that a practical benefit is realized. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application. Step 2B: Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “ first sensor ” does not qualify as significantly more because this limitation is merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well-known elements. In particular, the sensor is nothing more than a bed sensor sensing a patient's vital signs . Such sensors are composed of conventional detecting components known by one of skill in the art such as evidenced by: U.S. Patent Application Publication No. 20160314673 ( Eyring ) discloses a bed sensor to track vital signs which includes conventional and well-known motion sensors such as microphone, video sensor, sleep sensor, biometric sensors, heart rate sensors, pulse sensors, bed sensor, audio sensor, motion sensor, light sensor, some combination thereof, and the like . (Paragraph [003 8 ] Eyring ). The “ process or ” does not qualify as significantly more because this limitation is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l , 110 USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l , 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic , 890 F.3d 1016 (Fed. Circ. 2018)). The “inference model” does not does not qualify as significantly more because it is merely applying a generic, conventional machine learning algorithm to a new environment or dataset without providing a specific, tangible improvement to the underlying technology itself. (see Recentive Analytics, Inc. v. Fox Corp. , Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025)). In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. Thus, independent claim 1 fails to recite patent-eligible subject matter under 35 U.S.C. 101. Claims 2- 6 depend from claim 1, recite the same abstract idea as claim 1, and fail to cure the deficiencies of the independent claim by merely reciting additional abstract ideas or further limitations on the abstract idea already recited. However, with respect to claim 6 , the claim recites limitations beyond the abstract idea, but the limitations of claim 6 are merely adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well-known elements or simply displaying the results of the algorithm that uses conventional, routine, and well-known elements. In particular, the second sensor is nothing more than a bed sensor sensing a patient's vital signs . Such sensors are composed of conventional detecting components known by one of skill in the art such as evidenced by ( Eyring ) (as provided above with respect to the rejection of claim 1). As such, the limitations of claim 6 do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). The analysis of claim 7 is as follows: Step 1: Claim 7 is drawn computer for obtaining vital signs . Step 2A: Prong One: Claim 7 recites an abstract idea. In particular, claim 11 recites the following limitations: [A1] “ receiv [ ing ] a detection signal corresponding to a vital sign of a subject” ; [B1] “output [ t ing] a probability that the detection signal is classified into each of a plurality of classes” [C1] “output [ t ing] data corresponding to a vital sign associated with the detection signal, the probability that the first detection signal is classified into one of the plurality of classes being equal to or greater than a threshold” This element of claim 1 are drawn to an abstract idea since (1) they involve mathematical concepts in the form of mathematical concepts in the form of mathematical relationships, mathematical formulas or equations, and/or mathematical calculations in [ B 1] and [ C 1]; and/or (2) they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper. Step 2A- Prong Two: Claim 7 does not include additional elements that integrate the mental process into a practical application. The “ first sensor ” limitation do es not integrate the exception into a practical application since they are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). The “ process or” does not integrate the exception into a practical application since it is merely an instruction to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f). The “inference model” does not integrate the exception into a practical application since it is merely applying a generic, conventional machine learning algorithm to a new environment or dataset without providing a specific, tangible improvement to the underlying technology itself. (see Recentive Analytics, Inc. v. Fox Corp. , Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025) ) . As a whole, the additional elements merely serve to gather and feed information to the abstract idea and to output a result based on the abstract idea, while generically implementing it on conventionally used tools. There is no practical application because the abstract idea is not applied, relied on, or used in a meaningful way. No improvement to the technology is evident, and the detected signal of the vital sign is not outputted and classified in any way such that a practical benefit is realized. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application. Step 2B: Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “ first sensor ” does not qualify as significantly more because this limitation is merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well-known elements. In particular, the sensor is nothing more than a bed sensor sensing a patient's vital signs . Such sensors are composed of conventional detecting components known by one of skill in the art such as evidenced by: U.S. Patent Application Publication No. 20160314673 ( Eyring ) discloses a bed sensor to track vital signs which includes conventional and well-known motion sensors such as microphone, video sensor, sleep sensor, biometric sensors, heart rate sensors, pulse sensors, bed sensor, audio sensor, motion sensor, light sensor, some combination thereof, and the like . (Paragraph [003 8 ] Eyring ). The “ process or ” does not qualify as significantly more because this limitation is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l , 110 USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l , 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic , 890 F.3d 1016 (Fed. Circ. 2018)). The “inference model” does not does not qualify as significantly more because it is merely applying a generic, conventional machine learning algorithm to a new environment or dataset without providing a specific, tangible improvement to the underlying technology itself. (see Recentive Analytics, Inc. v. Fox Corp. , Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025)). In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. Thus, independent claim 1 fails to recite patent-eligible subject matter under 35 U.S.C. 101. Thus, independent claim 7 fails to recite patent-eligible subject matter under 35 U.S.C. 101. The analysis of claim 8 is as follows: Step 1: Claim 8 is drawn to a system for obtaining vital signs . Step 2A: Prong One: Claim 8 recites an abstract idea. In particular, claim 8 recites the following limitations: [A1] “ output[ting] a first detection signal corresponding to a vital sign of a subject” ; [B1] “ manag [ ing ] attribute information of the subject” [C1] output[ting] a probability that the first detection signal is classified into each of a plurality of classes [D1] “output [ t ing] data corresponding to a vital sign associated with the detection signal, the probability that the first detection signal is classified into one of the plurality of classes being equal to or greater than a threshold” [E1] “ stor [ ing ] the data in association with the attribute information” This element of claim 8 are drawn to an abstract idea since (1) they involve mathematical concepts in the form of mathematical concepts in the form of mathematical relationships, mathematical formulas or equations, and/or mathematical calculations in [ B 1] and [ C 1]; and/or (2) they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper. Step 2A- Prong Two: Claim 8 does not include additional elements that integrate the mental process into a practical application. The “ first sensor ” limitation do es not integrate the exception into a practical application since they are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). The “ process or” and “management device” do not integrate the exception into a practical application since it is merely an instruction to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f). The “inference model” does not integrate the exception into a practical application since it is merely applying a generic, conventional machine learning algorithm to a new environment or dataset without providing a specific, tangible improvement to the underlying technology itself. (see Recentive Analytics, Inc. v. Fox Corp. , Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025)). As a whole, the additional elements merely serve to gather and feed information to the abstract idea and to output a result based on the abstract idea, while generically implementing it on conventionally used tools. There is no practical application because the abstract idea is not applied, relied on, or used in a meaningful way. No improvement to the technology is evident, and the detected signal of the vital sign is not outputted and classified in any way such that a practical benefit is realized. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application. Step 2B: Claim 8 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “ first sensor ” does not qualify as significantly more because this limitation is merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well-known elements. In particular, the sensor is nothing more than a bed sensor sensing a patient's vital signs . Such sensors are composed of conventional detecting components known by one of skill in the art such as evidenced by: U.S. Patent Application Publication No. 20160314673 ( Eyring ) discloses a bed sensor to track vital signs which includes conventional and well-known motion sensors such as microphone, video sensor, sleep sensor, biometric sensors, heart rate sensors, pulse sensors, bed sensor, audio sensor, motion sensor, light sensor, some combination thereof, and the like . (Paragraph [003 8 ] Eyring ). The “ process or ” and “management device” do not qualify as significantly more because this limitation is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l , 110 USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l , 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic , 890 F.3d 1016 (Fed. Circ. 2018)). The “inference model” does not does not qualify as significantly more because it is merely applying a generic, conventional machine learning algorithm to a new environment or dataset without providing a specific, tangible improvement to the underlying technology itself. Recentive Analytics, Inc. v. Fox Corp. , Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025). In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. Thus, independent claim 8 fails to recite patent-eligible subject matter under 35 U.S.C. 101. Claims 9 - 12 depend from claim 1, recite the same abstract idea as claim 1, and fail to cure the deficiencies of the independent claim by merely reciting additional abstract ideas or further limitations on the abstract idea already recited. However, with respect to claim s 10- 11 , the claim s recite limitations beyond the abstract idea, but the limitations of claim 11 are merely adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well-known elements or simply displaying the results of the algorithm that uses conventional, routine, and well-known elements. In particular, the second sensor is nothing more than a bed sensor sensing a patient's vital signs . Such sensors are composed of conventional detecting components known by one of skill in the art such as evidenced by ( Eyring ) (as provided above with respect to the rejection of claim 8 ). As such, the limitations of claim s 10- 11 do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). 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. Claim s 1, 3-5, 7-8 and 12 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Armitstead (WO 2006066337 ). Regarding claim 1, Armitstead teaches a vital sign obtaining device comprising: an interface configured to receive, from a first sensor, a first detection signal corresponding to a vital sign of a subject, the first sensor configured to obtain the vital sign (Paragraph [0016] respiratory pressure sensor system and provides recordings of respiratory pressure during sleep ); an inference model ( Paragraph [0023] machine learning) configured to output a probability that the first detection signal is classified into each of a plurality of classes ( See Paragraphs [0021]-[0023]) ; and a processor configured to output data corresponding to a vital sign associated with the first detection signal, (Paragraph s [00 37 ] respiratory, signal is processed either onboard by the recording device or using a computer ), the probability that the first detection signal is classified into one of the plurality of classes being equal to or greater than a threshold (Paragraph [0017] detection of such events may be determined from the duration of one or more regions of hyperpnoea when the duration of the hyperpnoea exceeds a threshold, or a statistic, of the duration of regions of hyperpnoea exceeds a threshold ). Regarding claim 3, Armitstead teaches wherein one of the plurality of classes is associated with an elapsed time from obtaining of the vital sign. (Paragraph [0039] epoch length). Regarding claim 4, Armitstead teaches wherein the vital sign includes respiration information. (Paragraph [0020]). Regarding claim 5, Armitstead teaches wherein the data includes an index for evaluating a disease sign of the subject . (Paragraph [0010] apnea- hypopnoea index ). Regarding claim 7, Armitstead teaches a non-transitory computer readable storage medium storing a computer program, the computer program comprising instructions which, when executed by a processor (Paragraphs [0016], [0037] computer) mounted on a vital sign obtaining device, cause the vital sign obtaining device to: receive, from a sensor, a detection signal corresponding to a vital sign of a subject, the sensor configured to obtain the vital sign (Paragraph [0016] respiratory pressure sensor system and provides recordings of respiratory pressure during sleep ) ; input the detection signal to an inference model, (Paragraph [0023] machine learning) the inference model being configured to output a probability that the detection signal is classified into each of a plurality of classes (See Paragraphs [0021]-[0023]) ; and output data corresponding to a vital sign associated with the detection signal , (Paragraph [0021]), the probability that the detection signal is classified into one of the plurality of classes being equal to or greater than a threshold, the probability being output from the inference model. (Paragraph [0017] detection of such events may be determined from the duration of one or more regions of hyperpnoea when the duration of the hyperpnoea exceeds a threshold, or a statistic, of the duration of regions of hyperpnoea exceeds a threshold ). Regarding claim 8, Armitstead teaches a vital sign obtaining system comprising: a first sensor configured to output a first detection signal corresponding to a vital sign of a subject (Paragraph [0016] respiratory pressure sensor system and provides recordings of respiratory pressure during sleep ) ; a management device configured to manage attribute information of the subject (Paragraph [0010] computer) ; an inference model (Paragraph [0023] machine learning) configured to output a probability that the first detection signal is classified into each of a plurality of classes (See Paragraphs [0021]-[0023]) ; and a processor configured to output, to the management device, data corresponding to a vital sign associated with the first detection signal, (Paragraphs [0037] respiratory, signal is processed either onboard by the recording device or using a computer ) the probability that the first detection signal is classified into one of the plurality of classes being equal to or greater than a threshold, (Paragraph [0017] detection of such events may be determined from the duration of one or more regions of hyperpnoea when the duration of the hyperpnoea exceeds a threshold, or a statistic, of the duration of regions of hyperpnoea exceeds a threshold ), wherein the management device is configured to store the data in association with the attribute information (Paragraph [0037] memory). Regarding claim 12, Armitstead teaches wherein the management device is configured to give, to the data, an index for evaluating a disease sign of the subject. (Paragraph [0010] apnea- hypopnoea index ). 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 2 i s rejected under 35 U.S.C. 103 as being unpatentable over Armitstead in view of Heneghan (US 20180064388). Regarding claim 2, Armitstead does not teach “w herein one of the plurality of classes is associated with an artifact superimposed on the vital sign ”. Heneghan, in a related field of endeavor, teaches a system for estimating sleep states of a user based on sensor data comprising a classifier w herein one of the plurality of classes is associated with an artifact superimposed on the vital sign . (Paragraph [0162] a sleep stage classifier may be trained by having a set of labeled data available, labels for epochs as being Wake, Light, Deep or REM , e.g., there may be different labels or additional labels, such as artefact and/or off-wrist labels) . As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Armitstead to teach “ w herein one of the plurality of classes is associated with an artifact superimposed on the vital sign ”. Doing so may maximize classification accuracy. (Paragraph [0162]). Claim 9 i s rejected under 35 U.S.C. 103 as being unpatentable over Armitstead in view of Kaplan (US 20160071393 ). Regarding claim 9 , Armitstead does not teach “ wherein the first sensor has an operation period longer than a non-operation period ”. Kaplan, in a related field of endeavor, teaches alertness monitoring device wherein the first sensor has an operation period longer than a non-operation period . (Paragraph [0080] continuous monitoring of various sleep risk variables implies operation period is longer than a non-operation period ). As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Armitstead to teach “ wherein the first sensor has an operation period longer than a non-operation period ”. Doing so enables generat ion of dynamic risk levels for user fatigue . (Paragraph [0081]). Claim s 6 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Armitstead in view of Schuijers ( WO 2017178308 ). Regarding claim 6, Armitstead does not teach wherein the interface is configured “ to receive, from a second sensor, a second detection signal corresponding to at least one of a level of consciousness of the subject or a resting state of the subject, and wherein the processor is configured to determine whether to output the data, based on the second detection signal”. Schuijers , in a related field of endeavor, teaches a sleeping signal conditional device (Fig. 1, 100) configured to receive, from a second sensor ( 220 ) , a second detection signal (120) corresponding to at least one of a level of consciousness of the subject or a resting state of the subject (i.e. sleep) , and wherein the processor is configured to determine whether to output the data, based on the second detection signal. (Pa ge 8, lines 24-33, In practice (not shown), in addition to providing the first sleep signal output 170, typically similar sleep output signals would be generated based on the conditioned signals from the second and further sensors using corresponding processing circuitry ) . As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Armitstead to teach “ wherein the interface is configured to receive, from a second sensor, a second detection signal corresponding to at least one of a level of consciousness of the subject or a resting state of the subject, and wherein the processor is configured to determine whether to output the data, based on the second detection signal” as taught by Schuijers . Doing so provides a conditioned output sleep signal based on the evaluation criteria of the system. (Page 8, lines 24-33). Regarding claim 10, Armitstead does not teach “a second sensor configured to output a second detection signal corresponding to at least one of a level of consciousness of the subject or a resting state of the subject, wherein the processing device is configured to determine whether to output the data to the management device, based on the second detection signal”. Schuijers teaches a second sensor ( 220 ), a second detection signal (120) corresponding to at least one of a level of consciousness of the subject or a resting state of the subject, ( i.e., sleep ), and wherein the processing device is configured to determine whether to output the data to the management device, based on the second detection signal . ( Page 8, lines 24-33, In practice (not shown), in addition to providing the first sleep signal output 170, typically similar sleep output signals would be generated based on the conditioned signals from the second and further sensors using corresponding processing circuitry ) . As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Armitstead to teach “ a second sensor configured to output a second detection signal corresponding to at least one of a level of consciousness of the subject or a resting state of the subject, wherein the processing device is configured to determine whether to output the data to the management device, based on the second detection signal” as taught by Schuijers . Doing so provides a conditioned output sleep signal based on the evaluation criteria of the system. (Page 8, lines 24-33). Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Armitstead in view of Schuijers , further in view of Ten Kate (EP 3398513). Regarding claim 11, Ten Kate as modified by Schuijers , as discussed above, teaches a second sensor configured to output a second detection signal corresponding to at least one of a level of consciousness of the subject or a resting state of the subject (Page 8, lines 24-33 of Schuijers ), but does not teach wherein the management device is configured “to determine whether to store the data, based on the second detection signal”. Ten Kate, in a related field of endeavor, teaches a sleep monitoring system, (Fig. 5; Abstract), comprising a second sensor ( 110, 114) wherein the management device (116) is configured to determine whether to store the data, based on the second detection signal, based on the second detection signal . (Fig. 5, at block 514, the apparatus may store a second indication that signifies a transition of the subject into a second state based on one or more signals received from the second sensor.) As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Armitstead as modified by Schuijers to teach wherein the management device is configured “to determine whether to store the data, based on the second detection signal” as taught by Ten Kate. Doing so enables removal of spurious events from monitoring of any activities of a subject and ascertains periods of sleep of a subject more accurately . (Paragraphs [0013], [0060]). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT Om A. Patel whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)272-6331 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT Monday - Friday 8 a.m. - 5 p.m. . 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Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /OM PATEL/ Examiner, Art Unit 3791 /JENNIFER ROBERTSON/ Supervisory Patent Examiner, Art Unit 3791