DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 8/19/2025 has been entered.
Acknowledgements
The present application is being examined under the pre-AIA first to invent provisions.
Claims 1, 4-7, 10-18, 23-26, 28 are pending; claims 4-7, 10-18 are withdrawn.
This action is Non-Final.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 26 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 26 recites the limitation "wherein the comparison identifies". There is insufficient antecedent basis for this limitation in the claim.
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 pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under pre-AIA 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims under pre-AIA 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of pre-AIA 35 U.S.C. 103(c) and potential pre-AIA 35 U.S.C. 102(e), (f) or (g) prior art under pre-AIA 35 U.S.C. 103(a).
Claims 1, 23-26 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Mault et al. (Mault, US 2003/0208113) in view of Venon et al. (Venon, US 2009/0259493) and Landis et al. (Landis, US 2013/0318439).
Regarding claim 1, Mault teaches a machine-executed method of continuous analyte monitoring for a host to facilitate management of the host's blood glucose level (see at least Figures 1-2, 7a-b, 10-11), the method comprising:
receiving, at a continuous analyte monitoring (CAM) software application executing on a hand-held computing device (see at least [0073] meets continuous sensor, [0014] software receiving glucose data), input from a scheduling software application executing on the hand-held computing device, the input including data about a plurality of past events and data about a future event, the data about the past events and the future event each including a timing and duration of physical activity performed by the host (scheduling software is interpreted as software related to information about any other feature other than glucose that is logged and provided as feedback, such as activity log 308 and future exercise data, which can include information stored with respect to date/time: see at least [0197]-[0198], [0075] “Physical activity monitor 14 may comprise a body mounted accelerometer, and can transmit data to the PDA correlated with the physical activity level of the person. Monitor 14 may used to determine the effect of physical activity on glycemic response. For example, after consuming a meal of known nutrition content, the person may engage in a repetitive physical activity and the effect of this on the blood glucose response can be determined.” [0015], [0018], [0021] “The software program may provide interactive feedback to modify a future meal, exercise, or administration of medication so as to prevent excursions of blood glucose from a predetermined range.” [0023] “The glycemic response model for the person is used to predict blood glucose levels over a period of time. If exercise is planned, the planned exercise can be entered into the PDA, which can suggest times for the exercise based on blood glucose levels. The effect of physical activity on glycemic response can be determined, enabling the PDA to suggest limits on the planned exercise, additional snacks (for example fruit juice, candy) which it might be advisable to consume, or any other adjustments so as to avoid the onset of hypoglycemia.”, [0028] “Calorie management functionality can comprise diet logging, diet control (such as menu suggestions), activity logging, and activity control (such as exercise program generation)”, [0031] “optimum times for medication, exercise, etc”, [0038], [0070], [0117], [0118] ‘The software program, working from previously entered blood glucose levels, and any previous diet log information, calculates a projected curve of blood glucose levels from the food items recorded. This curve is shown on the display of the PDA, or using the display capabilities of any device in communication with the PDA. If the projected curve goes outside a predetermined healthy range, actions can be recommended to the person, these include…performing exercise (an optimum time, duration, nature, and intensity of exercise may be recommended), cancellation of exercise,… so as to maintain blood glucose levels within a healthy range.” [0142]);
determining, by the CAM application, a correlation between the plurality of past events and the host's historical analyte concentration levels (see at least [0039] “The algorithm may further correlate the blood glucose response of the person with a physical activity level of the person.” [0075] “Physical activity monitor 14 may comprise a body mounted accelerometer, and can transmit data to the PDA correlated with the physical activity level of the person. Monitor 14 may used to determine the effect of physical activity on glycemic response. For example, after consuming a meal of known nutrition content, the person may engage in a repetitive physical activity and the effect of this on the blood glucose response can be determined.”);
receiving, at the CAM application, a current analyte concentration data of the host obtained via a continuous analyte monitor (see at least Figures 7A-B, 11, receiving current data [0156], especially from a continuous glucose sensor type including those known in the art [0073], [0095], [0203]-[0204]);
optimizing, by the CAM application, the future event by adjusting one or more of the timing and duration of the future event based on the determined correlation and the current analyte concentration data of the host (see at least [0075] “Physical activity monitor 14 may comprise a body mounted accelerometer, and can transmit data to the PDA correlated with the physical activity level of the person. Monitor 14 may used to determine the effect of physical activity on glycemic response. For example, after consuming a meal of known nutrition content, the person may engage in a repetitive physical activity and the effect of this on the blood glucose response can be determined.”, [0118] ‘The software program, working from previously entered blood glucose levels, and any previous diet log information, calculates a projected curve of blood glucose levels from the food items recorded. This curve is shown on the display of the PDA, or using the display capabilities of any device in communication with the PDA. If the projected curve goes outside a predetermined healthy range, actions can be recommended to the person, these include…performing exercise (an optimum time, duration, nature, and intensity of exercise may be recommended), cancellation of exercise,… so as to maintain blood glucose levels within a healthy range.”);
scheduling, by the CAM software application executing on the hand-held computing device, the optimized future event (see at least [0139] “cancellation or rescheduling of fitness programs” [0021] “The software program may provide interactive feedback to modify a future meal, exercise, or administration of medication so as to prevent excursions of blood glucose from a predetermined range.” [0118] ‘The software program, working from previously entered blood glucose levels, and any previous diet log information, calculates a projected curve of blood glucose levels from the food items recorded. This curve is shown on the display of the PDA, or using the display capabilities of any device in communication with the PDA. If the projected curve goes outside a predetermined healthy range, actions can be recommended to the person, these include…performing exercise (an optimum time, duration, nature, and intensity of exercise may be recommended), cancellation of exercise,… so as to maintain blood glucose levels within a healthy range.”, Figure 14-16); and
generating, by the CAM software application executing on the hand-held computing device, an output indicative of the optimized future event (see entire document, especially [0031], [0071], [0080], [0111], [0112], [0118], [0132]-[0144], [0175], Figure 14-16).
However, the limitations of the CAM software application and the scheduling software application being separate software applications executing on the hand-held computing device are not directly taught.
Venon teaches a related system for managing user personal data on a hand-held device, including monitoring chronic health conditions such as diabetes (see entire document, especially abstract, [0016]), and wherein the health monitoring program interacts with separate programs including storing/stored information in a calendar-type program and integrates the separate programs to leverage existing programs in managing/monitoring health status, which one combined, reasonably teaches the claimed features that the CAM software application and the scheduling software application being separate software applications executing on the hand-held computing device (see at least abstract “The health tracking software receives and stores various health related information for the user. The health tracking software program communicates with at least the contact management program and calendar program on the mobile device to integrate the function of these programs with the health tracking software.”; “[0060] As shown in FIG. 2, the MHB is stored in memory of a mobile device 12 and leverages a mobile device's 12 existing phone 14, email 16, contact management and address book 18, calendar 20 and task applications 22 so a user may conveniently manage related tasks and workflow directly on the mobile device 12, for example, but not limited to: [0061] Call/Map/Search a care provider, a pharmacy, a member, etc. [0062] Send health related information to a care provider, a pharmacy, etc. by Email/Fax/Instant Messaging [0063] Send prescriptions (Rx) to pharmacy [0064] Schedule a doctor visit as a calendar item [0065] Set up `fill/refill medication`, `take medication` or `record next log` reminders. [0066] Set up recurring monitoring or caring events, such as, but not limited to taking medications, monitoring a chronic health condition (e.g., diabetes, asthma, etc. . . . )”; [0220]-[0230], [0254], [0261], [0276], [0350] “`Record Next Log` Reminder function . . . MHB will automatically set up a reminder entry in the mobile device's calendar management program using the information of a log, such as, but not limited to, member name, log type, next recording date/time. A corresponding reminder may also appear in this member's To-Do Reminder List. Any updates to the log's next recording date/time after the reminder is first set up, will be automatically trickled down to the calendar reminder entry by MHB.”. [0441], [0453], [0498]. Claim 8 “The health tracking system of claim 1 wherein the health tracking software program integrates information between the health tracking software program and at least the contact management program and the calendar program of the mobile device”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine prior art elements according to known methods to yield predictable results of using separate health software with existing calendar software of hand-held devices in order to integrate date/time/appointment/logged information between programs with known software architecture to leverage programs already commonly used on handheld devices for the management and monitoring of chronic diseases such as diabetes.
While Mault teaches the past data stored includes information about exercise, the past data including a timing and duration of physical activity performed by the host is not directly suggested.
Landis teaches a related system for monitoring analyte information along with lifestyle information, which includes time and duration of exercise to be logged (see at least [0057], [0060], [0077] “with light exercise "E" at 640 AM for 30 minutes”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine prior art elements according to known methods to yield predictable results of logging past exercise times and durations in order to track analyte readings effects from such activities. Such inclusion would suggest to one of ordinary skill in the art to use such activity information of date and time as activity information to correlate with blood analyte data in order to adjust or recommend future durations and time for exercise as already suggested by Mault.
Regarding claim 23, the limitations are met by Mault in view of Venon and Landis, where the combination teaches wherein the CAM software application executing on the hand-held computing device schedules the determined event on the second software application (see Mault document, especially [0118], [0132]-[0144], Figure 14-16; see Venon document, especially abstract, [0016], [0060]-[0066], [0498]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine prior art elements according to known methods to yield predictable results of using separate health software with existing calendar software of hand-held devices in order to integrate date/time/appointment/logged information between programs with known software architecture to leverage programs already commonly used on handheld devices for the management and monitoring of chronic diseases.
Regarding claim 24, Mault teaches a hand-held computing device (see at least Figures 1-2, 7a-b, 10-11, [0042], [0117]), comprising:
at least one memory including executable instructions; and at least one processor in data communication with the memory and configured to execute the instructions to cause the hand-held computing device (see Figures 1-2, 7a-b, 10-11 , [0042], [0117]) to:
receive, at a continuous analyte monitoring (CAM) software application executing on a hand-held computing device (see at least [0073] meets continuous sensor, [0014] software receiving glucose data), input from a scheduling software application executing on the hand-held computing device, the input including data about a plurality of past events and data about a future event, the data about the past events and the future event each including a timing and duration of physical activity performed by the host (scheduling software is interpreted as software related to information about any other feature other than glucose that is logged and provided as feedback, such as activity log 308 and future exercise data, which can include information stored with respect to date/time: see at least [0197]-[0198], [0075] “Physical activity monitor 14 may comprise a body mounted accelerometer, and can transmit data to the PDA correlated with the physical activity level of the person. Monitor 14 may used to determine the effect of physical activity on glycemic response. For example, after consuming a meal of known nutrition content, the person may engage in a repetitive physical activity and the effect of this on the blood glucose response can be determined.” [0015], [0018], [0021] “The software program may provide interactive feedback to modify a future meal, exercise, or administration of medication so as to prevent excursions of blood glucose from a predetermined range.” [0023] “The glycemic response model for the person is used to predict blood glucose levels over a period of time. If exercise is planned, the planned exercise can be entered into the PDA, which can suggest times for the exercise based on blood glucose levels. The effect of physical activity on glycemic response can be determined, enabling the PDA to suggest limits on the planned exercise, additional snacks (for example fruit juice, candy) which it might be advisable to consume, or any other adjustments so as to avoid the onset of hypoglycemia.”, [0028] “Calorie management functionality can comprise diet logging, diet control (such as menu suggestions), activity logging, and activity control (such as exercise program generation)”, [0031] “optimum times for medication, exercise, etc”, [0038], [0070], [0117], [0118] ‘The software program, working from previously entered blood glucose levels, and any previous diet log information, calculates a projected curve of blood glucose levels from the food items recorded. This curve is shown on the display of the PDA, or using the display capabilities of any device in communication with the PDA. If the projected curve goes outside a predetermined healthy range, actions can be recommended to the person, these include…performing exercise (an optimum time, duration, nature, and intensity of exercise may be recommended), cancellation of exercise,… so as to maintain blood glucose levels within a healthy range.” [0142]);
determine, by the CAM application, a correlation between the plurality of past events and the host's historical analyte concentration levels (see at least [0039] “The algorithm may further correlate the blood glucose response of the person with a physical activity level of the person.” [0075] “Physical activity monitor 14 may comprise a body mounted accelerometer, and can transmit data to the PDA correlated with the physical activity level of the person. Monitor 14 may used to determine the effect of physical activity on glycemic response. For example, after consuming a meal of known nutrition content, the person may engage in a repetitive physical activity and the effect of this on the blood glucose response can be determined.”);
receive, at the CAM application, a current analyte concentration data of the host obtained via a continuous analyte monitor (see at least Figures 7A-B, 11, receiving current data [0156], especially from a continuous glucose sensor type including those known in the art [0073], [0095], [0203]-[0204]);
optimize, by the CAM application, the future event by adjusting one or more of the timing and duration of the future event based on the determined correlation and the current analyte concentration data of the host (see at least [0075] “Physical activity monitor 14 may comprise a body mounted accelerometer, and can transmit data to the PDA correlated with the physical activity level of the person. Monitor 14 may used to determine the effect of physical activity on glycemic response. For example, after consuming a meal of known nutrition content, the person may engage in a repetitive physical activity and the effect of this on the blood glucose response can be determined.”, [0118] ‘The software program, working from previously entered blood glucose levels, and any previous diet log information, calculates a projected curve of blood glucose levels from the food items recorded. This curve is shown on the display of the PDA, or using the display capabilities of any device in communication with the PDA. If the projected curve goes outside a predetermined healthy range, actions can be recommended to the person, these include…performing exercise (an optimum time, duration, nature, and intensity of exercise may be recommended), cancellation of exercise,… so as to maintain blood glucose levels within a healthy range.”);
schedule, by the CAM software application executing on the hand-held computing device, the optimized future event (see at least [0139] “cancellation or rescheduling of fitness programs” [0021] “The software program may provide interactive feedback to modify a future meal, exercise, or administration of medication so as to prevent excursions of blood glucose from a predetermined range.” [0118] ‘The software program, working from previously entered blood glucose levels, and any previous diet log information, calculates a projected curve of blood glucose levels from the food items recorded. This curve is shown on the display of the PDA, or using the display capabilities of any device in communication with the PDA. If the projected curve goes outside a predetermined healthy range, actions can be recommended to the person, these include…performing exercise (an optimum time, duration, nature, and intensity of exercise may be recommended), cancellation of exercise,… so as to maintain blood glucose levels within a healthy range.”, Figure 14-16; and
generate, by the CAM software application executing on the hand-held computing device, an output indicative of the optimized future event (see entire document, especially [0031], [0071], [0080], [0111], [0112], [0118], [0132]-[0144], [0175], Figure 14-16).
However, the limitations of the CAM software application and the scheduling software application being separate software applications executing on the hand-held computing device are not directly taught.
Venon teaches a related system for managing user personal data on a hand-held device, including monitoring chronic health conditions such as diabetes (see entire document, especially abstract, [0016]), and wherein the health monitoring program interacts with separate programs including storing/stored information in a calendar-type program and integrates the separate programs to leverage existing programs in managing/monitoring health status, which one combined, reasonably teaches the claimed features that the CAM software application and the scheduling software application being separate software applications executing on the hand-held computing device (see at least abstract “The health tracking software receives and stores various health related information for the user. The health tracking software program communicates with at least the contact management program and calendar program on the mobile device to integrate the function of these programs with the health tracking software.”; “[0060] As shown in FIG. 2, the MHB is stored in memory of a mobile device 12 and leverages a mobile device's 12 existing phone 14, email 16, contact management and address book 18, calendar 20 and task applications 22 so a user may conveniently manage related tasks and workflow directly on the mobile device 12, for example, but not limited to: [0061] Call/Map/Search a care provider, a pharmacy, a member, etc. [0062] Send health related information to a care provider, a pharmacy, etc. by Email/Fax/Instant Messaging [0063] Send prescriptions (Rx) to pharmacy [0064] Schedule a doctor visit as a calendar item [0065] Set up `fill/refill medication`, `take medication` or `record next log` reminders. [0066] Set up recurring monitoring or caring events, such as, but not limited to taking medications, monitoring a chronic health condition (e.g., diabetes, asthma, etc. . . . )”; [0220]-[0230], [0254], [0261], [0276], [0350] “`Record Next Log` Reminder function . . . MHB will automatically set up a reminder entry in the mobile device's calendar management program using the information of a log, such as, but not limited to, member name, log type, next recording date/time. A corresponding reminder may also appear in this member's To-Do Reminder List. Any updates to the log's next recording date/time after the reminder is first set up, will be automatically trickled down to the calendar reminder entry by MHB.”. [0441], [0453], [0498]. Claim 8 “The health tracking system of claim 1 wherein the health tracking software program integrates information between the health tracking software program and at least the contact management program and the calendar program of the mobile device”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine prior art elements according to known methods to yield predictable results of using separate health software with existing calendar software of hand-held devices in order to integrate date/time/appointment/logged information between programs with known software architecture to leverage programs already commonly used on handheld devices for the management and monitoring of chronic diseases such as diabetes.
While Mault teaches the past data stored includes information about exercise, the past data including a timing and duration of physical activity performed by the host is not directly suggested.
Landis teaches a related system for monitoring analyte information along with lifestyle information, which includes time and duration of exercise to be logged (see at least [0057], [0060], [0077] “with light exercise "E" at 640 AM for 30 minutes”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine prior art elements according to known methods to yield predictable results of logging past exercise times and durations in order to track analyte readings effects from such activities. Such inclusion would suggest to one of ordinary skill in the art to use such activity information of date and time as activity information to correlate with blood analyte data in order to adjust or recommend future durations and time for exercise as already suggested by Mault.
Regarding claim 25, the limitations are met by Mault in view of Venon and Landis, where the combination teaches wherein: the scheduling software application includes a calendar of the host on the hand-held computing device, and scheduling the optimized future event includes adding the optimized future event to the calendar of the host (see Mault document, especially [0118], [0132]-[0144], Figure 14-16; see Venon document, especially abstract, [0016], [0060]-[0066], [0498]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine prior art elements according to known methods to yield predictable results of using separate health software with existing calendar software of hand-held devices in order to integrate information between programs with known software architecture to leverage programs already commonly used on handheld devices for the management and monitoring of chronic disease.
Regarding claim 26, the limitations are met by Mault in view of Venon and Landis, where Mault teaches wherein the comparison identifies one or more patterns between (i) the correlation between the plurality of past events and the host's historical analyte concentration levels during the plurality of past events and (ii) data from other users (see at least [0075] “Physical activity monitor 14 may comprise a body mounted accelerometer, and can transmit data to the PDA correlated with the physical activity level of the person. Monitor 14 may used to determine the effect of physical activity on glycemic response. For example, after consuming a meal of known nutrition content, the person may engage in a repetitive physical activity and the effect of this on the blood glucose response can be determined.”, [0118] ‘The software program, working from previously entered blood glucose levels, and any previous diet log information, calculates a projected curve of blood glucose levels from the food items recorded. This curve is shown on the display of the PDA, or using the display capabilities of any device in communication with the PDA. If the projected curve goes outside a predetermined healthy range, actions can be recommended to the person, these include…performing exercise (an optimum time, duration, nature, and intensity of exercise may be recommended), cancellation of exercise,… so as to maintain blood glucose levels within a healthy range.”).
Allowable Subject Matter
Claim 28 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: The art of record including Mault and Mensinger (US 2009/0240193) teach using GPS systems with glucose management devices, where such can be used to determine nearby food locations (Mault), or locations associated with information transfer such as an exercise location (Mensinger), but the art of record fails to teach or suggest the claimed features of further comprising: receiving, via a global positioning system (GPS) receiver of the hand-held computing device, a current location of the host, wherein optimizing the future event is further based on the current location of the host in view of the required structures and features of claim 1 when considered as a whole.
Response to Arguments
The examiner acknowledges applicant’s submission of amendments to the claims filed 8/19/2025, and IDS filed 9/18/2025.
Applicant’s arguments regarding the rejections of the claims under 35 U.S.C. 112 have been fully considered and are persuasive in view of the amendments to the claims and corresponding arguments; the rejections are withdrawn.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL R BLOCH whose telephone number is (571)270-3252. The examiner can normally be reached M-F 11-8 EST.
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/MICHAEL R BLOCH/Primary Examiner, Art Unit 3791