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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/30/25 has been entered.
Response to Arguments
With regards to the claim objection “Claims 37-39 are objected to under 37 CFR 1.75 as being a substantial duplicate of claims 34-36.” The objection is withdrawn in view of the cancellation of the respective claims.
With regards to the 112b rejections of Claim 30-31, 35-36, 38-39 based on the varied phrasing of “optimal”, “instant” and “wake” the rejections are withdrawn due to the amendments.
With regards to the 101 rejection, Applicants first argue that the claims are directed to patent eligible subject matter. Examiner notes if this is meant to be an argument for Subject Matter Eligibility Test Step 1, then the argument is moot as Examiner is viewing the claims as directed to a machine under step 1. However, being considered as a machine does not in of itself render them eligible we move on to step 2A. To the extent this is a broad argument that the claims are inherently eligible Examiner disagrees. When viewing the claim elements as a whole, the claims are directed to the abstract idea(s) of mental process and/or mathematical concepts represented in the determining and detecting steps. Applicants seem to be arguing that the measuring of the data is part of what Examiner has indicated as the abstract idea. However, as discussed below the gathering of the data by the wearable and transferring of the data to a secondary processing device are extra solution activity, or phrased differently presolution data gathering. For the above reasons the Applicants arguments are not persuasive, the claims are directed to a mental concept and/or mathematical idea.
Applicants next argue that the claims integrate the elements into a practical application (seemingly step 2A prong 2) that go beyond applying abstract ideas on a generic computer. Applicants also generally argue that the use “specialized hardware”, specific parameters and specialized software to make a determination however, this is not persuasive. Applicants seem to enumerate on these hardware, parameters and software in more specific arguments discussed below. Examiner notes that to the extent Applicants arguments discussed below include arguments to advantages or other elements not disclosed by the specification, Applicants arguments are not evidence on the record see MPEP 2145(I). For example, non-exhaustively, Applicants mentioning of power savings, intrusiveness and computational efficiency. Examiner also notes Applicants claims recite a detection unit “with a computing system” and per the specification this is referring to a generic computing device see Applicants Pg Pub [0036] reciting “a computing device (such as a processor, an FPGA, or an ASIC) and a memory which may act as the means for implementing the method” and [0039] including “The separate detection unit may be a generic computing device or system, for example.” Thus per Applicants own recitation it is a generic computing device.
Applicants more specifically discuss the transmitting data wirelessly (presumably part of the “specialized hardware”) which is part of the pre-solution activity and is not an improvement in the additional elements to integrate a judicial exception into a practical application. Per Applicants specification [0039] including “Bluetooth, ZigBee, near field communication (NFC), or infrared protocols, for example.”, its disclosing this as transmitting data through generally known protocols. This is not disclosing some new more efficient protocol for example, its simply reciting known protocols which are are not an improvement in the art.
Applicants next argue that the “specific detection criteria”, which are the abstract idea - determine and detecting steps, are the improvement. Phrased different Applicants are arguing that the improvement is to the abstract itself which is not persuasive. Examiner notes even in arguendo if the recited limitations were beneficial, a claim for a useful or beneficial abstract idea is still an abstract idea. See Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, 1379 80 (Fed. Cir. 2015). To the extent “specialized sensor technology” is mentioned this is not persuasive. The sensors are not disclosed as being a new form of hr or temperature sensor or something similar.
Applicants next touch on claim 29 arguing it is renders a pratical application Examiner disagrees. The “estimate” step is part of the abstract idea and thus not an additional element and the “cause” an alarm is merely outputting a result and is a extrasolution activity which does not integrate the judicial exception into a practical application. As such this argument is not persuasive.
Applicants next argue the claim recites additional element sthat amount to significantly more than the judicial exception (seemingly step 2b). To the extent the arguments parallel those above please see the above. Again Examiner notes that to the extent Applicants arguments discussed below include arguments to advantages or other elements not disclosed by the specification, Applicants arguments are not evidence on the record see MPEP 2145(I). Applicants first argue the wearable sensor device and wireless transmission of data causes it to be significantly more but as discussed above this is merely extra solution data gathering. Examiner notes there is no recitation in the specification of a new more efficient or sensitive sensor; or a new transmission protocol etc. Again, Applicants argue it is a specialized computer but per their own spec this is contradicted see discussion earlier in the arguments for the similar argument presented under II or step 2a Prong 2. Finally, the “specific detection algorithm” is part of the abstract idea and not an additional element. For the above reasons these arguments are not persuasive.
Applicants next argue there are “factual errors”, Examiner disagrees. Applicants argument about “in the mind” or “using pen and paper”, Examiner notes that the arguments are based on reading in limitations and do not reflect the claims. Next mentioned is the pre-solution “data gathering”, the claims recite data gathering before the analysis/abstract idea and is extra solution activity in the form of presolution activity, furthermore Applicants argument appears to be that it’s the “selecting of the particular data” which is key but this is not persuasive see MPEP 2106.05(g). Next, Applicants again argue that the processor is specialized which is contradicted by their own specification see the discussion above. Next, Applicants appear to be arguing against the 101 Berkheimer discussion as if it is the a 102/103 rejection which is discussed later in the action. The elements in the Berkheimer discussion were provided in that section for use with regards to the enumerated additional elements in the analysis under step 2b, see MPEP 2106.05(d). For the above reasons Applicants arguments are not persuasive.
With regards to the 103 arguments, Applicant’s arguments are not persuasive. Applicants present several arguments. First applicants argue Chen does not recite heart rate variability or distal skin temperature variation. Examiner notes in the new claims Applicants claim specific values for variability. Examiner disagrees with Applicants arguments, when taking a broad interpretation of the terms the elements recited by the prior art fulfill the claim limitations.
Specifically, the Chen reference for example discloses in [0010] “calculate variations of the heart rate signals at adjacent times” and “compare the variations of the heart rate signals with a threshold for the variations of the heart rate signals at adjacent times one by one”. A heart rage signal over time with distinct respective “variations” at different times, this data is one way of representing the “variability” of the heart rate.
Applicants next argue that the Chen reference does not show the variability in the skin temperature. Examiner disagrees. The reference discloses taking a “a variation curve of the body temperature signals with respect to time” which is a series of data over time of the variation of temperature signals. Each point represents a variation of the temperature and the curve represents the different variations over time or when taken as a whole the variability of the measurements. Then when taking the variation curve compared to the threshold based on another variation curve you are comparing temperature variations to make the disclosed determination. Examiner notes as discussed further in the rejection the rejection of the element “distal skin temperature variability” is based on the combination of the references. Examiner responded to the argument which is seemingly focused on the variability portion of the element and Chen was relied on for. For the above reasons Examiner does not find Applicants arguments persuasive.
The remaining discussion of the additional reference relies on the discussion above and is not persuasive for the same reasons. While Examiner does not agree with Applicants arguments as discussed above, Examiner does acknowledge that Chen does not explicitly recite determining standard deviation, variance etc. as recited in the new claims 42-44 (for more on this see the rejection below).
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 22, 25-27, 29-32, 34-36, 40-44 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process and/or a mathematical concept without significantly more. The claim recites gathering data, deriving parameters, comparing parameters to limits and calculating a “wake up” time.
The limitations of “determining” parameters based on skin temperature and HR data such as temperature variability (TV) and HR variability (HRV); “detecting” sleep stages/cycles based on comparing the determined TV and HRV to thresholds; “providing”/determining quality of sleep information based on the sleep stages/cycles; “determining” ratios of durations (i.e. sleep quality information)/counts of sleep cycles/stages, durations and/or counts of sleep cycles/stages, reference points and determining an optimal wake up time based on the parameters, is/are a processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is nothing in the claim element precludes the step from practically being performed in the mind. For example, “determining” TV includes determining that the readings for temperature are changing between readings (other versions include applying known mathematical statistical concepts such as mean, variance, standard deviation equations for which are included in the rejections below), “determining” HRV values (time changes in intervals between R peaks, can also be done using the aforementioned known mathematical statistical concepts), comparing the TV and HRV to thresholds to determine sleep stages and the “reference point” (mathematical Boolean comparisons), tracking parameters (such as the counts and durations) of the stages during the course of an evening and calculating optimal wake up/bed times based on multiplication and addition (number of cycles times period of cycle plus the reference point as the starting time) the data in the context of the claims encompasses the user manually using pen a paper to perform such calculations/determinations. Furthermore, the additional claims do not claim anything beyond basic math concepts which can be performed mentally or using pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas; if it covers mathematical relationship (for example, correspondence between data), Mathematical formulas or equations, and/or Mathematical calculations it falls under the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements – of data gathering. The limitations wirelessly receiving data from measurement device with sensors is pre-solution activity of mere data gathering. The processor (i.e., “processor”, “controller”, “computing device”, “control unit”, “computer processor”, etc.) in computing steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of determining set parameters and calculate steps) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform detecting, determining, providing and estimating steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Additionally, well-known, routine and conventional activity is not enough to add significantly more than the abstract idea itself.
Per the Berkheimer requirement, the wrist wearable with temperature/HR sensing, wireless data transmission and processor/memory (at secondary element): (1) Bres see recitations below including [0041], [0043], [0045], [0067], [0075]; (2) US 20180055449 see [0003], [0037], [0056]-[0057], [0080], [0082], [0142]; (3) US 20130332286 see [0014]-[0016], [0018], [0038], [0042], [0045], [0059], [0069], [0099], [0233], Figs. 1-2; (4) US 20140276119 see [0122]-[0123], [0200]-[0205], Figs. 1-2.
Therefore, the claims considered in combination/as a whole is are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 22, 26-27, 32, 40 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen (Ruisi Chen, EP 3199197) hereinafter Chen in view of Breslow (Emily Breslow, US 20160374569) hereinafter Bres in further view of Benson (Ronald Benson et al., US 20150164409) hereinafter Ben.
Regarding claim 22, an interpretation of Chen discloses a detection system for monitoring sleep of a person data ([0010]-[0011], [0020]-[0021] see also [0033]-[0035], Figs. 1-2), wherein the detection system comprises a computer implemented detection unit with a computing device or system configured to automatically ([0010]-[0011], [0020]-[0021], [0035] see also [0033]-[0034], Figs. 1-2; recites processing by the system)
receive first measurement data and second measurement data ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), wherein the first measurement data represents at least one of temperature and temperature variability of the person ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), and the second measurement data represents at least one of heart rate and heart rate variability of the person ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), wherein variability represents dispersion of measurement values over time([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2; Examiner notes that variability and dispersion are synonyms if you have a variation curve over time where each value along the curve represents a temperature variation and the curve represents the dispersion/variability of the signal over time)
determine temperature variability of the person over time based on the first measurement data and determining heart rate variability of the person over time based on the second measurement data ([0010]-[0011], [0020]-[0021], [0040]; Examiner notes that the math equations for one way of calculating HR Variability (in time domain) is using Mean
(
μ
)
=
∑
X
N
, Variance
(
σ
2
)
=
∑
(
x
-
μ
)
2
N
and Standard Deviation
(
σ
)
=
∑
(
x
-
μ
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2
N
which are all generally known equations)
detect instances of sleep stage within sleep of the person based on the temperature variability over time and the heart rate variability over time ([0021], [0040], [0045], [0064]-[0065]), wherein the detecting of the instances of the sleep stages comprises both:
i) detecting that the person is in a Rapid Eye Movement (REM) sleep stage when the temperature variability is below a first temperature variability limit and the heart rate variability is above a first heart rate variability limit ([0021], [0040] including “compare the obtained temperature variation curve with the ideal temperature variation curve to be able to obtain information on which state and which stage the human body is in”, [0045], [0064]-[0065]; Per Applicants [0006] “The present disclosure describes a method for detecting stages of sleep of a person. During REM (Rapid Eye Movement) sleep stage and deep sleep stage of a person's sleep, the person's body temperature control effectively shuts off and distal skin temperature changes on the limbs may be within just about 0.2 degrees Celsius. During the other sleep stages the human's temperature control is active and the distal skin temperature changes are much larger.” This is discussing elements that Applicants are disclosing as inherent to the human body during sleep), and
ii) detecting that the person is in a deep sleep stage when the temperature variability is below a second temperature variability limit and the heart rate variability is below a second heart rate variability limit ([0021], [0040], [0043], [0064]-[0065]; Examiner notes Applicants [0015] “the first temperature variability limit is the same as the second temperature variability limit, and the first heart rate variability limit is the same as the second variability limit.” only requires a single threshold/limit for each respective variability parameter (heart rate and temperature). Reading the claims in view of the specification, the scope of the first and second limits (thresholds) can be same or different. Also, the “second” limits appear to lack criticality based on [0015] and [0020]).
While Chen discloses a measurement unit and processing unit; determining the body temperature, an interpretation of Chen may not explicitly disclose measurement unit and a separate detection unit with a computing device or system with a computer program product and a memory; the body temperature is distal skin temperature; the data is received wirelessly through a wireless communication unit from a measurement unit in the form of a wearable device comprising at least a distal skin temperature sensor and a heart rate sensor.
However, in the same field of endeavor (medical devices), Bres teaches measurement unit and a separate detection unit with a computing device or system with a computer program product and a memory ([0044]-[0045], [0058], [0204]-[0206], [0211]-[0212], Figs. 22-23 see also [0218]; wearable (aka measurement unit) transmits data to external computing system (aka detection unit) for processing); measuring the body temperature is measuring the distal skin temperature ([0067], [0073]-[0075], [0084], Fig. 6; The reference recites skin temperature from the wearable device on the wrist which is on a limb and “distal”, see applicants [0006]); the data is received wirelessly through a wireless communication unit from a measurement unit in the form of a wearable device comprising at least a distal skin temperature sensor and a heart rate sensor ([0041] including “Exemplary systems are wearable and enable real-time and continuous monitoring of heart rate . . . Exemplary systems also enable monitoring of one or more physiological parameters in addition to heart rate including, but not limited to, body temperature, heart rate variability”, [0044]-[0045], [0067], [0073]-[0075], [0077], [0084], [0211]-[0212], Fig. 6 see also [0218]). Bres also recites the determination/tracking of sleep states and transitions between states based on measured values including during sleep ([0003], [0041], [0248]-[0250])
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
An interpretation of Chen may not explicitly disclose provide information on quality of the sleep of the person based on the detected instances of the sleep stages.
However, in the same field of endeavor (medical devices), Ben teaches provide information on quality of the sleep of the person based on the detected instances of the sleep stages ([0320]-[0321] including “the processor may determine a metric which is based on the total amount of time spent in the REM sleep stage during a single sleeping period or session (e.g. during a single night) as compared with the total amount of time spent in other sleep stages and/or the total amount of time spent in the bed.”; Ben teaches calculating ratios of different stages of sleep of the person based on the basis of the detected stages of sleep which Applicants recite in their specification is “information on quality of the sleep of the person based on detected instances of the sleep stages”, [0322] see Applicants [0021], [0028]; Examiner notes that “provide” does not recite to a user, UI, output or display etc. thus if that is what Applicants meant to recite that is not currently claimed).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen in view of Bres to include further analysis of calculating ratios of different sleep stages, including comparing deep sleep to other stages of sleep as it can be used to determine an efficiency score which provides a quantitate measure of quality and/or efficiency of your sleep ([0313], [0321]).
Regarding claim 26, an interpretation of Chen in view of Bres in further view of Ben discloses the above in claim 22.
An interpretation of Chen may not explicitly disclose a wireless communication unit for relaying the first and second measurement data to the detection unit.
However, in the same field of endeavor (medical devices), Bres teaches a wireless communication unit ([0079], [0204]-[0205], [0212]-[0213], Figs. 6, 22) for relaying the first and second measurement data to the detection unit ([0079], [0204]-[0205], [0212]-[0213], Figs. 6, 22).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include wearable device with the associated sensors and communication capability as recited by Bres as it provides a comfortable and compact way of continuously gathering data of a user ([0041], [0061]).
Regarding claim 27, an interpretation of Chen in view of Bres in further view of Ben discloses the above in claim 26.
An interpretation of Chen may not explicitly disclose wherein the detection unit is a handheld communication device or is a cloud computing system configured to receive the first data and the second data from the measurement unit.
However, in the same field of endeavor (medical devices), Bres teaches wherein the detection unit is a handheld communication device or is a cloud computing system ([0045], [0204]-[0205] see also [0218]-[0220]; Bres discloses gathering data by the wearable and transferring it to a computing device including a handheld device or cloud system for processing) configured to receive the first data and the second data from the measurement unit ([0045], [0204]-[0205] see also [0218]-[0220], [0283]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include processing on a handheld communication device or a cloud system and transferring data to such a device as recited by Bres because a handheld communication device or a cloud system for processing are obvious to try as they are “Obvious to try”, Bres recites a finite list of computing devices ([0204]-[0205]) which predictable can process the data with a reasonable chance of success.
Regarding claim 32, an interpretation of Chen discloses a computer-implemented method for monitoring of sleep of a person, wherein the method comprises ([0010]-[0011], [0020]-[0021] see also [0033]-[0035], Figs. 1-2)
receiving first measurement data and second measurement data ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), wherein the first measurement data represents at least one of temperature and temperature variability of the person ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), and the second measurement data represents at least one of heart rate and heart rate variability of the person ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), wherein variability represents dispersion of measurement values over time([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2; Examiner notes that variability and dispersion are synonyms if you have a variation curve over time where each value along the curve represents a temperature variation and the curve represents the dispersion/variability of the signal over time),
determining temperature variability of the person over time based on the first measurement data and determining heart rate variability of the person over time based on the second measurement data ([0010]-[0011], [0020]-[0021], [0040]; Examiner notes that the math equations for one way of calculating HR Variability (in time domain) is using Mean
(
μ
)
=
∑
X
N
, Variance
(
σ
2
)
=
∑
(
x
-
μ
)
2
N
and Standard Deviation
(
σ
)
=
∑
(
x
-
μ
)
2
N
which are all generally known equations)
detecting instances of sleep stage within sleep of the person based on the temperature variability over time and the heart rate variability over time ([0021], [0040], [0045], [0064]-[0065]), wherein the detecting of the instances of the sleep stages comprises both:
i) detecting that the person is in a Rapid Eye Movement (REM) sleep stage when the temperature variability is below a first temperature variability limit and the heart rate variability is above a first heart rate variability limit ([0021], [0040], [0045], [0064]-[0065]; Per Applicants [0006] “The present disclosure describes a method for detecting stages of sleep of a person. During REM (Rapid Eye Movement) sleep stage and deep sleep stage of a person's sleep, the person's body temperature control effectively shuts off and distal skin temperature changes on the limbs may be within just about 0.2 degrees Celsius. During the other sleep stages the human's temperature control is active and the distal skin temperature changes are much larger.” This is discussing elements that Applicants are disclosing as inherent to the human body during sleep), and
ii) detecting that the person is in a deep sleep stage when the temperature variability is below a second temperature variability limit and the heart rate variability is below a second heart rate variability limit ([0021], [0040], [0043], [0064]-[0065]; Examiner notes Applicants [0015] “the first temperature variability limit is the same as the second temperature variability limit, and the first heart rate variability limit is the same as the second variability limit.” only requires a single threshold/limit for each respective variability parameter (heart rate and temperature). Reading the claims in view of the specification, the scope of the first and second limits (thresholds) can be same or different. Also, the “second” limits appear to lack criticality based on [0015] and [0020]).
While Chen discloses a measurement unit and processing unit; determining the body temperature, an interpretation of Chen may not explicitly disclose measurement unit and a separate detection unit with a computing device or system with a computer program product and a memory; the body temperature is distal skin temperature; the data is received wirelessly through a wireless communication unit from a measurement unit in the form of a wearable device comprising at least a distal skin temperature sensor and a heart rate sensor.
However, in the same field of endeavor (medical devices), Bres teaches measurement unit and a separate detection unit with a computing device or system with a computer program product and a memory ([0044]-[0045], [0058], [0204]-[0206], [0211]-[0212], Figs. 22-23 see also [0218]; wearable (aka measurement unit) transmits data to external computing system (aka detection unit) for processing); measuring the body temperature is measuring the distal skin temperature ([0067], [0073]-[0075], [0084], Fig. 6; The reference recites skin temperature from the wearable device on the wrist which is on a limb and “distal”, see applicants [0006]); the data is received wirelessly through a wireless communication unit from a measurement unit in the form of a wearable device comprising at least a distal skin temperature sensor and a heart rate sensor ([0041] including “Exemplary systems are wearable and enable real-time and continuous monitoring of heart rate . . . Exemplary systems also enable monitoring of one or more physiological parameters in addition to heart rate including, but not limited to, body temperature, heart rate variability”, [0044]-[0045], [0067], [0073]-[0075], [0077], [0084], [0211]-[0212], Fig. 6 see also [0218]). Bres also recites the determination/tracking of sleep states and transitions between states based on measured values including during sleep ([0003], [0041], [0248]-[0250])
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
An interpretation of Chen may not explicitly disclose providing information on quality of the sleep of the person based on the detected instances of the sleep stages.
However, in the same field of endeavor (medical devices), Ben teaches providing information on quality of the sleep of the person based on the detected instances of the sleep stages ([0320]-[0321] including “the processor may determine a metric which is based on the total amount of time spent in the REM sleep stage during a single sleeping period or session (e.g. during a single night) as compared with the total amount of time spent in other sleep stages and/or the total amount of time spent in the bed.”; Ben teaches calculating ratios of different stages of sleep of the person based on the basis of the detected stages of sleep which Applicants recite in their specification is “information on quality of the sleep of the person based on detected instances of the sleep stages”, [0322] see Applicants [0021], [0028]; Examiner notes that “provide” does not recite to a user, UI, output or display etc. thus if that is what Applicants meant to recite that is not currently claimed)
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen in view of Bres to include further analysis of calculating ratios of different sleep stages, including comparing deep sleep to other stages of sleep as it can be used to determine an efficiency score which provides a quantitate measure of quality and/or efficiency of your sleep ([0313], [0321]).
Regarding Claim 40, an interpretation of Chen may not explicitly disclose wherein the separate detection unit is a handheld communication device.
However, in the same field of endeavor (medical diagnostic systems), Bres teaches wherein the separate detection unit is a handheld communication device ([0205]-[0206], [0211] including “the computing device 2200 may be any computer system, such as . . . handheld computer, tablet computer (e.g., the iPad® tablet computer), mobile computing or communication device (e.g., the iPhone® communication device) . . . ”).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
Claim Rejections - 35 USC § 103
Claim(s) 25, 34-35 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of Bres in further view of Ben in further view of Ronnholm (Valter Ronnholm, US 20050190065) hereinafter Ronn.
Regarding claim 25, an interpretation of Chen in view of Bres in further view of Ben discloses the above in claim 22 and Chen further recites sounding an alarm for determined desired wake up time ([0056], [0071], Figs. 4-6).
An interpretation of Chen may not explicitly disclose to estimate an optimal time instant for a wake-up based on the detected instances of sleep stages, and cause an alarm to be raised based on the estimated optimal time instant.
However, in the same field of endeavor (medical devices), Ronn teaches to estimate an optimal time instant for a wake-up based on the detected instances of sleep stages, and cause an alarm to be raised based on the estimated optimal time instant ([0044], [0053], [0056], [0066], fig. 4 see also [0033], [0049], [0051], [0057]-[0058]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages as recited by Chen in view of Bres in further view of Ben to include further analysis of using the sleep cycle to determine an ideal time to wake up as recited by Ronn in order to sleep a sufficient amount of cycles to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Regarding claim 34, an interpretation of Chen in view of Bres in further view of Ben discloses the above in claim 32 and Chen further recites sounding an alarm for determined desired wake up time ([0056], [0071], Figs. 4-6).
An interpretation of Chen may not explicitly disclose to estimating an optimal time instant for a wake-up based on the detected instances of sleep stages, and causing an alarm to be raised based on the estimated optimal time instant.
However, in the same field of endeavor (medical devices), Ronn teaches to estimating an optimal instant for a wake-up based on the detected instances of sleep stages, and causing an alarm to be raised based on the estimated optimal instant ([0044], [0053], [0056], [0066], fig. 4 see also [0033], [0049], [0051], [0057]-[0058]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages as recited by Chen in view of Bres in further view of Ben to include further analysis of using the sleep cycle to determine an ideal time to wake up as recited by Ronn in order to sleep a sufficient amount of cycles to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Regarding claim 35, an interpretation of Chen in view of Bres in further view of Ben in further view of Ronn discloses the above in claim 34.
An interpretation of Chen may not explicitly disclose determining a length of a sleep cycle of the person based on the detected sleep stages.
However, in the same field of endeavor (medical devices), Bres teaches determining a length of a sleep cycle of the person based on the detected sleep stages ([0253], [0262], Fig. 16B; in 16b for example see sum of time in zones);
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to include determining length of a sleep cycle and using the disclosed parameters for determining recovery and sleep scores as recited by Bres in order to achieve the proper amount of sleep for homeostasis and be beneficial for the users health ([0252], [0262]-[0263]). Furthermore it is also, combining prior art elements according to known methods to yield predictable results, combining the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen with the determination of the parameters recited for determining of sleep quality and sufficiency in Bres would lead to the predictable result of using those parameters in order to determine desired sleep lengths and wake up times.
An interpretation of Chen may not explicitly disclose estimating an optimal instant based on the length of the sleep cycle and the fixed reference point so that the person will have slept a desired number of sleep cycles at the determined optimal instant.
However, in the same field of endeavor (medical devices), Ronn teaches estimating an optimal instant based on the length of the sleep cycle and the fixed reference point so that the person will have slept a desired number of sleep cycles at the determined optimal instant ([0044], [0053] including “The key factor is the number of complete sleep cycles we enjoy. . . on the average, after a multiple of 90 minutes—for example, after 4½ hours, 6 hours, 7½ hours, or 9 hours. . . . Once the user knows the length of a typical sleep cycle, then, where possible, the user can plan his or her waking accordingly.”, [0056], [0066], fig. 4 see also [0049], [0051], [0057]-[0058]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages, the length of a sleep cycle as recited by Chen in view of Bres to include further analysis of using the sleep cycle to determine an ideal time to wake up as recited by Ronn in order to sleep a sufficient amount of cycles to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Claim Rejections - 35 USC § 103
Claim(s) 29-30, 41 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of Bres in further view of Ronn.
Regarding claim 29, an interpretation of Chen discloses a detection system for monitoring sleep of a person data ([0010]-[0011], [0020]-[0021] see also [0033]-[0035], Figs. 1-2), wherein the detection system comprises a computer implemented detection unit with a computing device or system configured to automatically ([0010]-[0011], [0020]-[0021], [0035] see also [0033]-[0034], Figs. 1-2; recites processing by the system),
receive first measurement data and second measurement data ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), wherein the first measurement data represents at least one of temperature and temperature variability of the person ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2), and the second measurement data represents at least one of heart rate and heart rate variability of the person ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2),
determine temperature variability of the person over time based on the first measurement data and determining heart rate variability of the person over time based on the second measurement data ([0010]-[0011], [0020]-[0021], [0040]; Examiner notes that the math equations for one way of calculating HR Variability (in time domain) is using Mean
(
μ
)
=
∑
X
N
, Variance
(
σ
2
)
=
∑
(
x
-
μ
)
2
N
and Standard Deviation
(
σ
)
=
∑
(
x
-
μ
)
2
N
which are all generally known equations),
detect instances of sleep stage within sleep of the person based on the temperature variability over time and the heart rate variability over time ([0021], [0040], [0045], [0064]-[0065]),
and causing an alarm to be raised based on the determined wake-up time ([0056], [0071], Figs. 4-6;).
While Chen discloses a measurement unit and processing unit; determining the body temperature, an interpretation of Chen may not explicitly disclose measurement unit and a separate detection unit with a computing device or system with a computer program product and a memory; the body temperature is distal skin temperature; the data is received wirelessly through a wireless communication unit from a measurement unit in the form of a wearable device comprising at least a distal skin temperature sensor and a heart rate sensor.
However, in the same field of endeavor (medical devices), Bres teaches measurement unit and a separate detection unit with a computing device or system with a computer program product and a memory ([0044]-[0045], [0058], [0204]-[0206], [0211]-[0212], Figs. 22-23 see also [0218]; wearable (aka measurement unit) transmits data to external computing system (aka detection unit) for processing); measuring the body temperature is measuring the distal skin temperature ([0067], [0073]-[0075], [0084], Fig. 6; The reference recites skin temperature from the wearable device on the wrist which is on a limb and “distal”, see applicants [0006]); the data is received wirelessly through a wireless communication unit from a measurement unit in the form of a wearable device comprising at least a distal skin temperature sensor and a heart rate sensor ([0041] including “Exemplary systems are wearable and enable real-time and continuous monitoring of heart rate . . . Exemplary systems also enable monitoring of one or more physiological parameters in addition to heart rate including, but not limited to, body temperature, heart rate variability”, [0044]-[0045], [0067], [0073]-[0075], [0077], [0084], [0211]-[0212], Fig. 6 see also [0218]). Bres also recites the determination/tracking of sleep states and transitions between states based on measured values including during sleep ([0003], [0041], [0248]-[0250])
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
An interpretation of Chen may not explicitly disclose to estimate an optimal instant for a wake-up based on the detected instances of sleep stages, and cause an alarm to be raised based on the estimated optimal instant.
However, in the same field of endeavor (medical devices), Ronn teaches to estimate an optimal instant for a wake-up based on the detected instances of sleep stages, and cause an alarm to be raised based on the estimated optimal instant ([0044], [0053], [0056], [0066], fig. 4 see also [0033], [0049], [0051], [0057]-[0058]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages as recited by Chen in further view of Bres to include further analysis of using the sleep cycle to determine an ideal time to wake up as recited by Ronn in order to sleep a sufficient amount of cycles to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Regarding claim 30, an interpretation of Chen in view of Bres in further view of Ronn discloses the above in claim 29 including estimating the optimal time instant (see the rejection of claim 29).
An interpretation of Chen may not explicitly disclose determining a length of a sleep cycle of the person based on the detected sleep stages.
However, in the same field of endeavor (medical devices), Bres teaches determining a length of a sleep cycle of the person based on the detected sleep stages ([0253], [0262], Fig. 16B; in 16b for example see sum of time in zones);
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to include determining length of a sleep cycle and using the disclosed parameters for determining recovery and sleep scores as recited by Bres in order to achieve the proper amount of sleep for homeostasis and be beneficial for the users health ([0252], [0262]-[0263]). Furthermore it is also, combining prior art elements according to known methods to yield predictable results, combining the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen with the determination of the parameters recited for determining of sleep quality and sufficiency in Bres would lead to the predictable result of using those parameters in order to determine desired sleep lengths and wake up times.
An interpretation of Chen may not explicitly disclose estimating a optimal instant based on the length of the sleep cycle and the fixed reference point so that the person will have slept a desired number of sleep cycles at the determined optimal instant.
However, in the same field of endeavor (medical devices), Ronn teaches estimating a optimal instant based on the length of the sleep cycle and the fixed reference point so that the person will have slept a desired number of sleep cycles at the determined optimal instant ([0044], [0053] including “The key factor is the number of complete sleep cycles we enjoy. . . on the average, after a multiple of 90 minutes—for example, after 4½ hours, 6 hours, 7½ hours, or 9 hours. . . . Once the user knows the length of a typical sleep cycle, then, where possible, the user can plan his or her waking accordingly.”, [0056], [0066], fig. 4 see also [0049], [0051], [0057]-[0058]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages, the length of a sleep cycle as recited by Chen in view of Bres to include further analysis of using the sleep cycle to determine an ideal time to wake up as recited by Ronn in order to sleep a sufficient amount of cycles to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Regarding Claim 41, an interpretation of Chen may not explicitly disclose wherein the separate detection unit is a handheld communication device.
However, in the same field of endeavor (medical diagnostic systems), Bres teaches wherein the separate detection unit is a handheld communication device ([0205]-[0206], [0211] including “the computing device 2200 may be any computer system, such as . . . handheld computer, tablet computer (e.g., the iPad® tablet computer), mobile computing or communication device (e.g., the iPhone® communication device) . . . ”).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
Claim Rejections - 35 USC § 103
Claim(s) 31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of Bres in further view of Ronn in further view of Nogueira (Adriano Nogueira et al., US 20180206776) hereinafter Nog.
Regarding claim 31, an interpretation of Chen in view of Bres in further view of Ronn discloses the above in claim 30.
An interpretation of Chen may not explicitly disclose gather measurement data for a plurality of days.
However, in the same field of endeavor (medical devices), Bres teaches gathering measurement data for a plurality of days ([0067], [0073]-[0075], [0187], Fig. 18b see also [0045], [0140])).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include wearable device with the associated sensors and communication capability for gathering data over days as recited by Bres as it provides a comfortable and compact way of continuously gathering data of a user ([0041], [0061]).
An interpretation of Chen may not explicitly disclose determine a fixed reference point within a circadian rhythm of the person based on the gathered data.
However, in the same field of endeavor (medical devices), Nog teaches detecting a temperature change pattern in the temperature data, said temperature change pattern indicating a fixed reference point within a circadian rhythm of the person ([0062] including “For example, a pattern displayed by the skin temperature monitoring may serve as a biomarker of circadian rhythm (block 702.2A). Skin temperature usually decreases minutes before sleep and increases since the beginning of sleep. In this manner, these parameters serve to estimate circadian periods.”, Fig. 7);
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen in view of Bres in further view of Ronn to include the use of changes in temperature within a timeframe as recited by Nog in order to accurately determine the time in which a person falls asleep when there are not precisely delimited regions of substantial motionlessness ([0062]). Furthermore, it is merely the combining prior art elements according to known methods to yield predictable results and/or the simple substitution of one known element for another to obtain predictable results, the known element/method being the disclosed approach using skin temperature and time to determine sleep onset as recited by Nog in combination/substitution with the recitation of sleep stage determination of sleep onset recite in Chen.
An interpretation of Chen may not explicitly disclose wherein the estimating of the optimal instant is performed based on the length of the sleep cycle and the fixed reference point (estimate of the circadian rhythm).
However, in the same field of endeavor (medical devices), Ronn teaches determining an optimal wake-up instant based on the length of the sleep cycle and the fixed reference point so that the person will have slept a desired number of sleep cycles at the determined wake-up instant ([0044], [0053] including “The key factor is the number of complete sleep cycles we enjoy. . . on the average, after a multiple of 90 minutes—for example, after 4½ hours, 6 hours, 7½ hours, or 9 hours. . . . Once the user knows the length of a typical sleep cycle, then, where possible, the user can plan his or her waking accordingly.”, [0056], [0066], fig. 4 see also [0049], [0051], [0057]-[0058]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages, the length of a sleep cycle, sleep onset, points in the circadian rhythm as recited by Chen in view of Bres in further view of Nog to include further analysis of using the sleep cycle to determine an ideal time to wake up as recited by Ronn in order to sleep a sufficient amount of cycles to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Claim Rejections - 35 USC § 103
Claim(s) 36 is/are rejected under 35 U.S.C. 103 as being over Chen in view of Bres in further view of Ben in further view of Ronn in further view of Nog.
Regarding claim 36, an interpretation of Chen in view of Bres in further view of Ben in further view of Ronn discloses the above in claim 35.
An interpretation of Chen may not explicitly disclose gathering measurement data for a plurality of days.
However, in the same field of endeavor (medical devices), Bres teaches gathering measurement data for a plurality of days ([0067], [0073]-[0075], [0187], Fig. 18b see also [0045], [0140]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include wearable device with the associated sensors and communication capability for gathering data over days as recited by Bres as it provides a comfortable and compact way of continuously gathering data of a user ([0041], [0061]).
An interpretation of Chen may not explicitly disclose determining a fixed reference point within a circadian rhythm of the person based on the gathered data.
However, in the same field of endeavor (medical devices), Nog teaches detecting a temperature change pattern in the temperature data, said temperature change pattern indicating a fixed reference point within a circadian rhythm of the person ([0062] including “For example, a pattern displayed by the skin temperature monitoring may serve as a biomarker of circadian rhythm (block 702.2A). Skin temperature usually decreases minutes before sleep and increases since the beginning of sleep. In this manner, these parameters serve to estimate circadian periods.”, Fig. 7);
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen in view of Bres in further view of Ben in further view of Ronn to include the use of changes in temperature within a timeframe as recited by Nog in order to accurately determine the time in which a person falls asleep when there are not precisely delimited regions of substantial motionlessness ([0062]). Furthermore, it is merely the combining prior art elements according to known methods to yield predictable results and/or the simple substitution of one known element for another to obtain predictable results, the known element/method being the disclosed approach using skin temperature and time to determine sleep onset as recited by Nog in combination/substitution with the recitation of sleep stage determination of sleep onset recite in Chen.
An interpretation of Chen may not explicitly disclose wherein the estimating of the optimal instant is performed based on the length of the sleep cycle and the fixed reference point (estimate of the circadian rhythm).
However, in the same field of endeavor (medical devices), Ronn teaches determining a wake-up instant based on the length of the sleep cycle and the fixed reference point so that the person will have slept a desired number of sleep cycles at the determined wake-up instant ([0044], [0053] including “The key factor is the number of complete sleep cycles we enjoy. . . on the average, after a multiple of 90 minutes—for example, after 4½ hours, 6 hours, 7½ hours, or 9 hours. . . . Once the user knows the length of a typical sleep cycle, then, where possible, the user can plan his or her waking accordingly.”, [0056], [0066], fig. 4 see also [0049], [0051], [0057]-[0058]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages, the length of a sleep cycle and sleep onset as recited by Chen in view of Bres in further view of Ben in further view of Nog to include further analysis of using the sleep cycle to determine an ideal time to wake up as recited by Ronn in order to sleep a sufficient amount of cycles to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Claim Rejections - 35 USC § 103
Claim(s) 42, 44 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of Bres in further view of Ben in further view of David Lane et al,. Introduction to Statistics. Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Rice University. 2003. https://open.umn.edu/opentextbooks/textbooks/459. viewed on 11/11/2025 (hereinafter Lane)
Regarding Claim 42, an interpretation of Chen discloses heart rate variation and a variation curve of the temperature values ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2; As discussed for temperature each point of the “variation curve of the body temperature signals” represents a variation of the temperature and the curve represents the different variations over time or when taken as a whole the variability of the measurements; likewise for the variation of the heart rate. Thus the temperature and heart rate data is present and as discussed previously, Examiner notes that Mean
(
μ
)
=
∑
X
N
, Variance
(
σ
2
)
=
∑
(
x
-
μ
)
2
N
and Standard Deviation
(
σ
)
=
∑
(
x
-
μ
)
2
N
are generally known equations).
While Chen discloses determining the body temperature, an interpretation of Chen may not explicitly disclose the body temperature is distal skin temperature.
However, in the same field of endeavor (medical devices), Bres teaches measuring the body temperature is measuring the distal skin temperature ([0067], [0073]-[0075], [0084], Fig. 6; The reference recites skin temperature from the wearable device on the wrist which is on a limb and “distal”, see applicants [0006]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
While Chen in view of Bres discloses the determining the variability of the heart rate and the temperature it may not explicitly disclose wherein the heart rate variability and the distal skin temperature variability are measured or disclosed as one of variance, standard deviation, and interquartile range (IQR) of the measurements.
However, in the same field of endeavor (data analysis), Lane teaches different measures of variability including variance, standard deviation, and interquartile range (IQR) of the measurements (Measures of Variability Section Pgs 144-150; The reference discloses these measures of variability and discusses how “Variability refers to how “spread out” a group of scores is.” Including sample calculations of such values using the aforementioned equations).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the graphical display of the variability as disclosed by Chen to provide one of numerical values representative of the variability as disclosed by Lane because it is merely simple substitution of one known element (graphical representation of variability in the data set) for another (the numerical representation of variability in the data) to obtain predictable result of numerical measure of variability for output.
Regarding Claim 44, an interpretation of Chen discloses heart rate variation and a variation curve of the temperature values ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2; As discussed for temperature each point of the “variation curve of the body temperature signals” represents a variation of the temperature and the curve represents the different variations over time or when taken as a whole the variability of the measurements; likewise for the variation of the heart rate. Thus the temperature and heart rate data is present and as discussed previously, Examiner notes that Mean
(
μ
)
=
∑
X
N
, Variance
(
σ
2
)
=
∑
(
x
-
μ
)
2
N
and Standard Deviation
(
σ
)
=
∑
(
x
-
μ
)
2
N
are generally known equations).
While Chen discloses determining the body temperature, an interpretation of Chen may not explicitly disclose the body temperature is distal skin temperature.
However, in the same field of endeavor (medical devices), Bres teaches measuring the body temperature is measuring the distal skin temperature ([0067], [0073]-[0075], [0084], Fig. 6; The reference recites skin temperature from the wearable device on the wrist which is on a limb and “distal”, see applicants [0006]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
While Chen in view of Bres discloses the determining the variability of the heart rate and the temperature it may not explicitly disclose wherein the heart rate variability and the distal skin temperature variability are measured or disclosed as one of variance, standard deviation, and interquartile range (IQR) of the measurements.
However, in the same field of endeavor (data analysis), Lane teaches different measures of variability including variance, standard deviation, and interquartile range (IQR) of the measurements (Measures of Variability Section Pgs 144-150; The reference discloses these measures of variability and discusses how “Variability refers to how “spread out” a group of scores is.” Including sample calculations of such values using the aforementioned equations).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the graphical display of the variability as disclosed by Chen to provide one of numerical values representative of the variability as disclosed by Lane because it is merely simple substitution of one known element (graphical representation of variability in the data set) for another (the numerical representation of variability in the data) to obtain predictable result of numerical measure of variability for output.
Claim Rejections - 35 USC § 103
Claim(s) 43 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of Bres in further view of Ronn in further view of Lane
Regarding Claim 43, an interpretation of Chen discloses heart rate variation and a variation curve of the temperature values ([0010]-[0011], [0020]-[0021] including “variation curve of the body temperature signals with respect to time . . . at least one variation of the heart rate” see also [0033]-[0034], Figs. 1-2; As discussed for temperature each point of the “variation curve of the body temperature signals” represents a variation of the temperature and the curve represents the different variations over time or when taken as a whole the variability of the measurements; likewise for the variation of the heart rate. Thus the temperature and heart rate data is present and as discussed previously, Examiner notes that Mean
(
μ
)
=
∑
X
N
, Variance
(
σ
2
)
=
∑
(
x
-
μ
)
2
N
and Standard Deviation
(
σ
)
=
∑
(
x
-
μ
)
2
N
are generally known equations).
While Chen discloses determining the body temperature, an interpretation of Chen may not explicitly disclose the body temperature is distal skin temperature.
However, in the same field of endeavor (medical devices), Bres teaches measuring the body temperature is measuring the distal skin temperature ([0067], [0073]-[0075], [0084], Fig. 6; The reference recites skin temperature from the wearable device on the wrist which is on a limb and “distal”, see applicants [0006]).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the unit’s gathering data and providing analysis including changes in temperature and heart rate variation to determine sleep stages as recited by Chen to further include a wearable device with the associated sensors (including a distal temperature sensor) wirelessly transferring data to a secondary device for processing as recited by Bres because it is merely combining prior art elements according to known methods to yield predictable results; combining the elements data gathering and analysis from Chen with the known process of providing data from a wearable to secondary device to yield the predictable result of the secondary device performing analysis on the transmitted data.
While Chen in view of Bres discloses the determining the variability of the heart rate and the temperature it may not explicitly disclose wherein the heart rate variability and the distal skin temperature variability are measured or disclosed as one of variance, standard deviation, and interquartile range (IQR) of the measurements.
However, in the same field of endeavor (data analysis), Lane teaches different measures of variability including variance, standard deviation, and interquartile range (IQR) of the measurements (Measures of Variability Section Pgs 144-150; The reference discloses these measures of variability and discusses how “Variability refers to how “spread out” a group of scores is.” Including sample calculations of such values using the aforementioned equations).
It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the graphical display of the variability as disclosed by Chen to provide one of numerical values representative of the variability as disclosed by Lane because it is merely simple substitution of one known element (graphical representation of variability in the data set) for another (the numerical representation of variability in the data) to obtain predictable result of numerical measure of variability for output.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 22, 25-27, 29-32, 34-36, 40-44 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-6 of U.S. Patent No. 11219408 (‘408) in view of Chen in further view of Bres and Ronn. The ‘408 patent Claims disclose receiving temperature data, determining temperature variability meeting threshold criteria to determine optimal times for wake up and sounding an alarm at the optimal time (see claim 2). The use of the temperature and heart variability for sleep states are shown in Chen, the Bres reference discloses the determination of the length of the sleep cycle as wells as the transfer of data from the measurement unit to a separate detection unit for processing, Ben discloses the determination of quality of sleep, Ronn reference provides the teaching of timing of the bed time or wake up time based on the multiple of cycles, and the Lane reference discloses variability measures. See the rejection above in claims 22, 32 and 39 for further discussion. It would have been prima facie obvious to one of skill in the art before the effective filing date of the claimed invention to have modified the units gathering data including changes in temperature and heart rate variation and providing analysis based on the data including the determination of sleep stages as recited by Chen; the wearable with distal temperature and HR sensing and analysis for length of a sleep cycle as recited by Bres; the reference time based on temperature pattern of ‘408 with analysis of using the sleep cycle to determine an ideal time to wake up or go to sleep with notifications/alerts to that end as recited by Ronn because the combination of elements uses parameters in order determine a sufficient amount of cycles of sleep to be rested ([0053]) and wake up at an ideal stage of sleep to feel more pleasant waking up in a more “natural manner” ([0002]-[0004], [0014]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20170238868 – to Kenyon et al. see [0063].
PT 104115 – see second or third paragraph under background section - “Classically, measurements of body temperature and melatonin secretion are used to determine the mammalian circadian cycle. The measurement of melatonin is difficult to implement since it is necessary to be performed in a laboratory or clinical setting. The most widely used method of indirect measurement for estimating the melatonin production cycle, and in turn the sleep cycle, is the measurement of body temperature, which is much easier to measure compared to the evasive method referred to above.”
Burgess (Helen Burgess et al., “The Relationship Between Slow-wave Activity, Body Temperature, and Cardiac Activity During Nighttime Sleep”, SLEEP, Vol. 24, No. 3, 2001, https://academic.oup.com/sleep/article/24/3/343/2750031?login=true, viewed on 3/14/23) – discloses distal temperature and HR changes throughout the night including during REM.
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/James Moss/Examiner, Art Unit 3792