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 .
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.
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1-20 of this application are patentably indistinct from claims 1-20 of Application No. 18/636,210. Pursuant to 37 CFR 1.78(f), when two or more applications filed by the same applicant or assignee contain patentably indistinct claims, elimination of such claims from all but one application may be required in the absence of good and sufficient reason for their retention during pendency in more than one application. Applicant is required to either cancel the patentably indistinct claims from all but one application or maintain a clear line of demarcation between the applications. See MPEP § 822.
Claims 1-3 are provisionally rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 1-3 of copending Application No. 18/636,210 (reference application). This is a provisional statutory double patenting rejection since the claims directed to the same invention have not in fact been patented.
Claims 4-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 4-20 of copending Application No. 18/636,210 in view of Shen et al. (US Pre-Grant Publication 2022/0125354).
Copending Application No. teaches classifying a host as unhealthy/metabolically unfit, but does not teach classifying a host as healthy.
Shen et al. teaches determining an individual’s physical fitness ([0059], [0068]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified copending Application No. 18/636,210 to incorporate the teachings of Shen et al. to also classify a host as being healthy/an athlete. Doing so would allow for the establishment of appropriate training interventions based on fitness level, as recognized by Shen [0063].
This is a provisional nonstatutory double patenting rejection.
18/636,224 (this application)
18/636,210 (copending reference application)
Claim 1: A monitoring system, comprising: a continuous analyte sensor configured to generate a first set of analyte measurements associated with analyte levels of a host; and a sensor electronics module coupled to the continuous analyte sensor and configured to receive and process the first set of analyte measurements.
Claim 1: A monitoring system, comprising: a continuous analyte sensor configured to generate a first set of analyte measurements associated with analyte levels of a host; and a sensor electronics module coupled to the continuous analyte sensor and configured to receive and process the first set of analyte measurements.
Claim 2: The monitoring system of claim 1, wherein the continuous analyte sensor comprises: a substrate, a working electrode disposed on the substrate, a reference electrode disposed on the substrate, wherein the first set of analyte measurements generated by the continuous analyte sensor correspond to an electromotive force at least in part based on a potential difference generated between the working electrode and the reference electrode.
Claim 2: The monitoring system of claim 1, wherein the continuous analyte sensor comprises: a substrate, a working electrode disposed on the substrate, a reference electrode disposed on the substrate, wherein the first set of analyte measurements generated by the continuous analyte sensor correspond to an electromotive force at least in part based on a potential difference generated between the working electrode and the reference electrode.
Claim 3: The monitoring system of claim 1, wherein: the continuous analyte sensor comprises a continuous lactate sensor, and the first set of analyte measurements include lactate measurements.
Claim 3: The monitoring system of claim 1, wherein: the continuous analyte sensor comprises a continuous lactate sensor, and the first set of analyte measurements include lactate measurements.
Claim 4: The monitoring system of claim 3, further comprising: one or more memories comprising executable instructions; one or more processors in data communication with the one or more memories and configured to execute the executable instructions to: classify a host as an athlete or a healthy host based on the first set of analyte measurements obtained during a trial exercise session or input received from the host; and optimize an exercise session for the host based on the classification of the host.
Claim 4: The monitoring system of claim 3, further comprising: one or more memories comprising executable instructions; one or more processors in data communication with the one or more memories and configured to execute the executable instructions to: classify a host as a metabolically unfit host based on the first set of analyte measurements obtained during a trial exercise session or input received from the host; and optimize an exercise session for the host based on the classification of the host.
Claim 5: The monitoring system of claim 4, wherein the classifying the host as an athlete or a healthy host based on the first set of analyte measurements comprises detecting a starting lactate level of 1.5 millimolar and a lactate threshold in the first set of analyte measurements during the trial exercise session.
Claim 5: The monitoring system of claim 4, wherein the classifying the host as a metabolically unfit host based on the first set of analyte measurements comprises detecting a starting lactate level of 3 millimolar and a lactate trough in the first set of analyte measurements during the trial exercise session.
Claim 6: The monitoring system of claim 5, the classifying the host as an athlete or a healthy host based on the first set of analyte measurements comprises correlating the lactate threshold of the first set of analyte measurements with an exercise parameter to classify the host as the athlete or the healthy host.
Claim 6: The monitoring system of claim 5, wherein the classifying the host as a metabolically unfit host based on the first set of analyte measurements comprises correlating the lactate trough of the first set of analyte measurements with an exercise parameter to classify the host as the metabolically unfit host.
Claim 7: The monitoring system of claim 4, wherein the classifying the host as an athlete or a healthy host is further based on non-analyte data obtained from a non-analyte sensor during the trial exercise session, wherein the non-analyte data includes accelerometer data, heart rate data, heart rate variability data, oxygen saturation data, blood pressure data, or body temperature data.
Claim 7: The monitoring system of claim 4, wherein the classifying the host as a metabolically unfit host is further based on non-analyte data obtained from a non-analyte sensor during the trial exercise session, wherein the non-analyte data includes accelerometer data, heart rate data, heart rate variability data, oxygen saturation data, blood pressure data, or body temperature data.
Claim 8: The monitoring system of claim 4, wherein the input received from the host include self classification information, health goals of the host, exercise goals of the host, or historical exercise data of the host.
Claim 8: The monitoring system of claim 4, wherein the input received from the host include self classification information, health goals of the host, exercise goals of the host, or historical exercise data of the host.
Claim 9: The monitoring system of claim 4, wherein optimizing the exercise session for the host comprises: determining exercise parameters for the exercise session based on the classification of the host or the first set of analyte measurements obtained during the trial exercise session; and transmitting an electronic signal to an exercise machine to cause the exercise machine to operate based on the determined exercise parameters.
Claim 9: The monitoring system of claim 4, wherein optimizing the exercise session for the host comprises: determining exercise parameters for the exercise session based on the classification of the host or the first set of analyte measurements obtained during the trial exercise session; and transmitting an electronic signal to an exercise machine to cause the exercise machine to operate based on the determined exercise parameters.
Claim 10: The monitoring system of claim 9, wherein optimizing the exercise session further comprises: monitoring a second set of analyte measurements of the host during the exercise session; determining the second set of analyte measurements is within a defined range for the exercise session; determining to maintain the exercise parameters for a specified duration of time; and causing the exercise machine to continue to operate based on the exercise parameters for a specified duration of time
Claim 10: The monitoring system of claim 9, wherein optimizing the exercise session further comprises: monitoring a second set of analyte measurements of the host during the exercise session; determining the second set of analyte measurements is within a defined range for the exercise session; determining to maintain the exercise parameters for a specified duration of time; and causing the exercise machine to continue to operate based on the determined exercise parameters for a specified duration of time.
Claim 11: The monitoring system of claim 4, wherein optimizing the exercise session further comprises: providing feedback to the host on an effectiveness of the exercise session.
Claim 11: The monitoring system of claim 4, wherein optimizing the exercise session further comprises: providing feedback to the host on an effectiveness of the exercise session.
Claim 12: The monitoring system of claim 11, wherein the effectiveness of the exercise session is determined based on a caloric burn and an overall energy expenditure following the exercise session.
Claim 12: The monitoring system of claim 11, wherein the effectiveness of the exercise session is determined based on a caloric burn and an overall energy expenditure following the exercise session.
Claim 13: The monitoring system of claim 10, wherein the one or more processors are further configured to: optimize a future exercise session based on the second set of analyte measurements and non-analyte data of the host during the exercise session.
Claim 13: The monitoring system of claim 10, wherein the one or more processors are further configured to: optimize a future exercise session based on the second set of analyte measurements and non-analyte data of the host during the exercise session.
Claim 14: The monitoring system of claim 4, wherein optimizing an exercise session for the host comprises: determining exercise parameters for an exercise session based on the classification of the host or the first set of analyte measurements obtained during the trial exercise session; and instructing the host to exercise according to the determined exercise parameters.
Claim 14: The monitoring system of claim 4, wherein optimizing the exercise session for the host comprises: determining exercise parameters for the exercise session based on the classification of the host or the first set of analyte measurements obtained during the trial exercise session; and instructing the host to exercise according to the determined exercise parameters.
Claim 15: The monitoring system of claim 14, wherein instructing the host to exercise according to the determined exercise parameters comprises the host manually adjusting a current exercise parameter to reach the determined exercise parameters.
Claim 15: The monitoring system of claim 14, wherein instructing the host to exercise according to the determined exercise parameters comprises the host manually adjusting a current exercise parameter on an exercise machine to reach the determined exercise parameters.
Claim 16: The monitoring system of claim 15, wherein exercise parameters comprise speed, incline, resistance, repetitions, or weight.
Claim 16: The monitoring system of claim 15, wherein exercise parameters comprise speed, incline, resistance, repetitions, or weight.
Claim 17: The monitoring system of claim 14, wherein optimizing the exercise session further comprises: monitoring a second set of analyte measurements of the host during the exercise session; determining the second set of analyte measurements is within a defined range for the exercise session; and instructing the host to maintain the exercise parameters for a specified duration of time.
Claim 17: The monitoring system of claim 14, wherein optimizing the exercise session further comprises: monitoring a second set of analyte measurements of the host during the exercise session; determining the second set of analyte measurements is within a defined range for the exercise session; and instructing the host to maintain the exercise parameters for a specified duration of time.
Claim 18: The monitoring system of claim 17, wherein optimizing the exercise session further comprises: providing feedback to the host on an effectiveness of the exercise session.
Claim 18: The monitoring system of claim 17, wherein optimizing the exercise session further comprises: providing feedback to the host on an effectiveness of the exercise session.
Claim 19: The monitoring system of claim 18, wherein the effectiveness of the exercise session is determined based on a caloric burn and an overall energy expenditure following the exercise session.
Claim 19: The monitoring system of claim 18, wherein the effectiveness of the exercise session is determined based on a caloric burn and an overall energy expenditure following the exercise session.
Claim 20: The monitoring system of claim 18, wherein the one or more processors are further configured to: optimize a future exercise session based on the effectiveness of the exercise session.
Claim 20: The monitoring system of claim 18, wherein the one or more processors are further configured to: optimize a future exercise session based on the second set of analyte measurements and non-analyte data of the host during the exercise session.
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 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Simpson et al. (US Pre-Grant Publication 2016/0324463), hereinafter ‘Simpson’.
Regarding claim 1, Simpson teaches a monitoring system (Figs. 45-47), comprising:
a continuous analyte sensor (continuous analyte sensor 700, Figs. 54-57) configured to generate a first set of analyte measurements associated with analyte levels of a host ([0038], analyte may be lactate measured by lactate sensor); and
a sensor electronics module ([0486], sensor electronics, unlabeled) coupled to the continuous analyte sensor and configured to receive and process the first set of analyte measurements ([0379], transmitter sends measured electrical analyte signal to device 518 that performs signal processing).
Regarding claim 3, Simpson teaches the system of claim 1, further comprising:
the continuous analyte sensor comprises a continuous lactate sensor ([0418], lactate sensor 656, Fig. 53) and the first set of analyte measurements include lactate measurements ([0532], measurement of lactate).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simpson et al. (US Pre-Grant Publication 2016/0324463) in view of Avula et al. (US Pre-Grant Publication 2022/0296867), hereinafter ‘Avula’.
Regarding claim 2, Simpson teaches the system of claim 1, further comprising:
wherein the continuous analyte sensor comprises:
a substrate ([0487], first layer 712, Figs. 54-57),
a working electrode disposed on the substrate ([0487], working electrode disposed on first layer 712, Figs. 54-57),
a reference electrode disposed on the substrate ([0489], third layer 714 has reference electrode, Figs. 55-57).
Simpson does not teach that the first set of analyte measurements is based on a potential difference between the working and reference electrodes.
Avula teaches an analyte sensor (Figs. 2A-2C), further comprising:
wherein the first set of analyte measurements generated by the continuous analyte sensor correspond to an electromotive force at least in part based on a potential difference generated between the working electrode and the reference electrode ([0177], working electrode 38 measures electronic current).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson to incorporate the teachings of Avula to include analyte measurements based on a potential difference between working/reference electrodes. Doing so would allow for an electrochemical reaction to provide information about the analyte concentration, as recognized by Avula [0177].
Claim(s) 4, 7-8, 11-12, 14-15, 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simpson et al. (US Pre-Grant Publication 2016/0324463) in view of Shen et al. (US Pre-Grant Publication 2022/0125354), hereinafter ‘Shen’.
Regarding claim 4, Simpson teaches the system of claim 3, further comprising:
one or more memories comprising executable instructions ([0186], computer readable memory);
one or more processors in data communication with the one or more memories ([0186], application/app 27 receives data and performs functions) and configured to execute the executable instructions to:
classify a host as an athlete or a healthy host based on input received from the host ([0009], different types of users can select programs); and
optimize an exercise session for the host based on the classification of the host ([0010], optimize sports/fitness training).
Simpson does not teach that the processors can classify the host as an athlete/healthy based on the analyte measurements.
Shen teaches a lactate sensing system (Fig. 2A), further comprising processors configured to:
classify a host as an athlete or a healthy host based on the first set of analyte measurements obtained during a trial exercise session ([0068], variance of lactate levels representative of physical fitness, Fig. 5).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson to incorporate the teachings of Shen to include host classification based on analyte measurements. Doing so would allow for the measurement of a host’s lactate clearance, which can be used to indicate physical fitness, as recognized by Shen [0068].
Regarding claim 7, Simpson and Shen teach the system according to claim 4. Simpson teaches the system further comprising:
wherein the classifying the host as an athlete or a healthy host is further based on non-analyte data obtained from a non-analyte sensor during the trial exercise session ([0039], monitoring other user data/activity data),
wherein the non-analyte data includes accelerometer data, heart rate data, heart rate variability data, oxygen saturation data, blood pressure data, or body temperature data ([0039], monitoring other user data/activity data from an accelerometer, heart rate monitor, or with the purpose of optimizing cardiovascular health) ([0185], body temperature).
Regarding claim 8, Simpson and Shen teach the system according to claim 4. Simpson teaches the system further comprising:
wherein the input received from the host (program selection 502, Fig. 45) include self-classification information, health goals of the host, exercise goals of the host, or historical exercise data of the host ([0370], program selection is associated with a goal) ([0394], previously determined lactate curves).
Regarding claim 11, Simpson and Shen teach the system according to claim 4. Simpson teaches the system further comprising:
wherein optimizing the exercise session further comprises: providing feedback to the host on an effectiveness of the exercise session ([0527], provide information about effectiveness of exercise).
Regarding claim 12, Simpson and Shen teach the system according to claim 11. Simpson teaches the system further comprising:
wherein the effectiveness of the exercise session is determined based on a caloric burn and an overall energy expenditure following the exercise session ([0418], calculate energy expenditure and caloric consumption/burn rate to help optimize exercise).
Regarding claim 14, Simpson and Shen teach the system according to claim 4. Simpson teaches the system further comprising:
wherein optimizing an exercise session for the host comprises:
determining exercise parameters for an exercise session based on the classification of the host ([0372], provide initial guidance to the user about how to achieve selected program, Fig. 45) or the first set of analyte measurements obtained during the trial exercise session ([0394], evaluate program lactate results to move user closer to goal);
and instructing the host to exercise according to the determined exercise parameters ([0372], provide initial guidance to the user about how to achieve selected program, Fig. 45).
Regarding claim 15, Simpson and Shen teach the system according to claim 14. Simpson teaches the system further comprising:
wherein instructing the host to exercise according to the determined exercise parameters comprises the host manually adjusting a current exercise parameter to reach the determined exercise parameters ([0419], user instructed to work out at an intensity, Fig. 52).
Regarding claim 17, Simpson and Shen teach the system according to claim 14. Simpson teaches the system further comprising:
wherein optimizing the exercise session further comprises:
monitoring a second set of analyte measurements of the host during the exercise session ([0383], lactate and other analytes monitored, Fig. 45) ([0013], glucose/other analytes monitored); and
determining the second set of analyte measurements is within a defined range for the exercise session ([0229], glucose threshold 92, 94, Fig. 6).
Simpson does not teach instructing the host to maintain the parameters for a specified period of time.
Shen teaches a lactate sensing system (Fig. 2A), further comprising:
instructing the host to maintain the exercise parameters for a specified duration of time ([0069], adjusting duration/timing of second exercise event).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson to incorporate the teachings of Shen to include instructing the host to maintain exercise parameters for a specified period of time. Doing so would allow for a specified training goal to be met, as recognized by Shen [0069].
Regarding claim 18, Simpson and Shen teach the system according to claim 17. Simpson teaches the system further comprising:
wherein optimizing the exercise session further comprises:
providing feedback to the host on an effectiveness of the exercise session ([0419], step 632, data evaluated against selected program, Fig. 52).
Regarding claim 19, Simpson and Shen teach the system according to claim 18. Simpson teaches the system further comprising:
wherein the effectiveness of the exercise session is determined based on a caloric burn and an overall energy expenditure following the exercise session ([0430-0431], energy expended, caloric consumption/burn rate).
Regarding claim 20, Simpson and Shen teach the system according to claim 18. Simpson teaches the system further comprising:
wherein the one or more processors are further configured to:
optimize a future exercise session based on the effectiveness of the exercise session ([0394], results evaluated and program modified to move user closer to goal).
Claim(s) 5-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simpson et al. (US Pre-Grant Publication 2016/0324463) in view of Shen et al. (US Pre-Grant Publication 2022/0125354), further in view of Atmaram et al. (US Pre-Grant Publication 2025/0302384), hereinafter ‘Atmaram’.
Regarding claim 5, Simpson and Shen teach the system according to claim 4. Simpson teaches the system further comprising:
wherein the classifying the host as an athlete or a healthy host based on the first set of analyte measurements comprises:
detecting a lactate threshold in the first set of analyte measurements during the trial exercise session (Fig. 49, lactate threshold).
Simpson and Shen do not teach detecting a starting lactate level of 1.5 millimolar to classify the host as an athlete/healthy.
Atmaram teaches a system for activity and exercise monitoring (Fig. 8), further comprising:
wherein the classifying the host as an athlete or a healthy host based on the first set of analyte measurements comprises:
detecting a starting lactate level of 1.5 millimolar ([0061], categorizing resting lactate levels 120, between 1.0-1.5 mmol 122, greater than or equal to 1.6 mmol 121).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson and Shen to incorporate the teachings of Atmaram to include classifying a host based on a starting lactate level of 1.5 millimolar. Doing so would allow for the selection of a testing protocol most appropriate for a person’s level of fitness, as determined by their starting lactate level, as recognized by Atmaram [0068].
Regarding claim 6, Simpson, Shen, and Atmaram teach the system according to claim 5. Shen teaches the system further comprising:
the classifying the host as an athlete or a healthy host based on the first set of analyte measurements comprises:
correlating the lactate threshold of the first set of analyte measurements with an exercise parameter to classify the host as the athlete or the healthy host ([0068], variance of lactate levels representative of physical fitness, Fig. 5).
Claim(s) 9-10, 13, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simpson et al. (US Pre-Grant Publication 2016/0324463) in view of Shen et al. (US Pre-Grant Publication 2022/0125354), further in view of Smith (US Pre-Grant Publication 2019/0192906), hereinafter ‘Smith’.
Regarding claim 9, Simpson and Shen teach the system according to claim 4. Simpson teaches the system further comprising:
wherein optimizing an exercise session for the host comprises:
determining exercise parameters for the exercise session based on the classification of the host ([0372], provide initial guidance to the user about how to achieve selected program, Fig. 45) or the first set of analyte measurements obtained during the trial exercise session ([0394], evaluate program lactate results to move user closer to goal).
Simpson and Shen do not teach transmitting a signal to cause an exercise machine to operate based on the parameters.
Smith teaches an adaptive training system (Fig. 8A), further comprising:
transmitting an electronic signal to an exercise machine to cause the exercise machine to operate based on the determined exercise parameters ([0086], step 806, automatically control functionality of workout machine, Fig. 8A).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson and Shen to incorporate the teachings of Smith to include causing an exercise machine to operate based on parameters. Doing so would allow for the automatic adjustment of the training program based on the user’s fitness, as recognized by Smith [0007].
Regarding claim 10, Simpson, Shen, and Smith teach the system according to claim 9. Simpson teaches the system further comprising:
monitoring a second set of analyte measurements of the host during the exercise session ([0383], lactate and other analytes monitored, Fig. 45) ([0013], glucose/other analytes monitored); and
determining the second set of analyte measurements is within a defined range for the exercise session ([0229], glucose threshold 92, 94, Fig. 6).
Simpson does not teach instructing the host to maintain the parameters for a specified period of time.
Shen teaches a lactate sensing system (Fig. 2A), further comprising:
determining to maintain the exercise parameters for a specified duration of time ([0069], adjusting duration/timing of second exercise event).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson to incorporate the teachings of Shen to include determining a period of time to maintain the exercise parameters for. Doing so would allow for a specified training goal to be met, as recognized by Shen [0069].
Simpson and Shen do not teach causing the exercise machine to continue operation for a period of time based on the exercise parameters.
Smith teaches an adaptive training system (Fig. 8A), further comprising:
causing the exercise machine to continue to operate based on the exercise parameters for a specified duration of time ([0086], step 806, automatically control functionality of workout machine, Fig. 8A).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson and Shen to incorporate the teachings of Smith to include causing an exercise machine to operate based on parameters. Doing so would allow for the automatic adjustment of the training program based on the user’s fitness, as recognized by Smith [0007].
Regarding claim 13, Simpson, Shen, and Smith teach the system according to claim 10. Simpson teaches the system further comprising:
wherein the one or more processors are further configured to:
optimize a future exercise session based on the second set of analyte measurements and non-analyte data of the host during the exercise session ([0392], inputs from glucose sensor, accelerometer).
Regarding claim 16, Simpson and Shen teach the system according to claim 15, but do not teach the limitations of claim 16. Smith teaches an adaptive training system (Fig. 8A), further comprising:
wherein exercise parameters comprise speed, incline, resistance, repetitions, or weight ([0020], speed, resistance, incline, weight, repetitions).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Simpson and Shen to incorporate the teachings of Smith to include various types of exercise parameters for exercise optimization. Doing so would allow for the measurement of power output and generation of a training program, as recognized by Smith [0013].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Huang (US Pre-Grant Publication 2015/0208970) teaches a system for lactate measurement and training adjustment.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELIZABETH L OKONAK whose telephone number is (571)272-1594. The examiner can normally be reached Monday-Friday 8-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benjamin Klein can be reached at (571) 270-5213. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/E.L.O./
Examiner, Art Unit 3792
/Benjamin J Klein/Supervisory Patent Examiner, Art Unit 3792