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 .
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.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2 and 5-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of Claim 19 follows.
STEP 1
Regarding Claim 19, the claim recites a method configured to obtain glucose measurements, identify glucose management feedback that correspond to glucose measurements, determine a highest ranking glucose feedback, and display determined glucose feedback. Thus, this claim is directed to a process, which is one of the statutory categories of invention.
STEP 2A, PRONG ONE
This claim is then analyzed to determine whether it is directed to any judicial exception. The steps of identifying multiple glucose management feedbacks, generating a quantitative improvement metric based on a magnitude of an improvement, ranking the multiple diabetes management feedbacks based on the respective quantitative improvement metric, and determining one of the multiple glucose feedbacks having a highest ranking set forth a judicial exception. These steps describe a concept performed in the human mind (including an observation, evaluation, judgment, opinion). Thus, this claim is drawn to a Mental Process, which is an Abstract Idea.
STEP 2A, PRONG TWO
Next, the claim as a whole is analyzed to determine whether the claim recites additional elements that integrate the judicial exception into a practical application. The claim fails to recite an additional element or a combination of additional elements to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limitation on the judicial exception. Claim 19 recites an additional step of causing the determined glucose feedback having the highest ranking to be displayed, which is merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). The step of displaying a glucose feedback with a highest ranking does not provide an improvement to the technological field, the method does not effect a particular treatment or effect a particular change based on the displayed glucose feedback, nor does the method use a particular machine to perform the Abstract Idea.
STEP 2B
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, is sufficient to ensure that the claim amounts to significantly more than the exception. Besides the Abstract Idea, Claim 19 recites obtaining glucose measurements from a glucose sensor of a continuous glucose level monitoring system, identifying glucose management feedback that correspond to glucose measurements, and determining a highest ranking glucose feedback . The obtaining, identifying, and determining steps are recited at a high level of generality such that they amount to insignificant pre-solution activity, e.g., mere data gathering step necessary to perform the Abstract Idea. When recited at this high level of generality, there is no meaningful limitation, such as a particular or unconventional step that distinguishes it from well-understood, routine, and conventional data gathering and comparing activity engaged in by medical professionals prior to Applicant's invention.
Consideration of the additional elements as a combination also adds no other meaningful limitations to the exception not already present when the elements are considered separately. Unlike the eligible claim in Diehr in which the elements limiting the exception are individually conventional, but taken together act in concert to improve a technical field, the claim here does not provide an improvement to the technical field. Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claim as a whole does not amount to significantly more than the exception itself. The claim is therefore drawn to non-statutory subject matter.
The same rationale applies to claim 1. It is noted that Claim 1 receives a similar streamline analysis as Claim 19 above due to Claim 19 being a more specific process of the same elements recited in Claim 1.
Regarding Claim 14, the device recited in the claim is a generic device comprising generic components configured to perform the abstract idea. The recited “device”, “display device”, “feedback generation system”, and “feedback presentation system” are generically claimed device elements configured to perform insignificant routine pre-solution data gathering activity. The recited “device”, “display device”, “feedback generation system”, and “feedback presentation system” are computers configured to perform the Abstract Idea. According to section 2106.05(f) of the MPEP, merely using a computer as a tool to perform an abstract idea does not integrate the Abstract Idea into a practical application.
The rest of the dependent claims fail to add something more to the abstract independent claims as they generally recite method steps pertaining to data gathering that can be performed by mentally comparing data to criteria that can be performed by using pen and paper. The obtaining of diabetes management measurements, identifying diabetes management feedbacks that correspond to diabetes management measurements, determining diabetes management feedbacks, and displaying the feedback recited in the independent claims maintain a high level of generality even when considered in combination with the dependent claims.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 5, 8-12, 14-16, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Gass et. al.’507 (U.S. Publication Number 20180286507 – previously cited) in view of Uchida et. al.’911 (U.S. Publication Number 20240127911).
Regarding Claim 1, Gass et. al.’507 discloses a method implemented in a diabetes management monitoring system (Paragraph [0026] – enhanced system for managing diabetes), the method comprising:
obtaining, from a sensor of the diabetes management monitoring system, diabetes management measurements measured for a use (Paragraph [0026] - Embodiments of the present invention include software applications and systems adapted to provide an enhanced system for managing diabetes. Using a portable, wireless device such as, for example, a smartphone, in communication with a blood glucose meter (BG meter or BGM), embodiments of the present invention include a software application (e.g., a DMS app) operable to receive blood glucose measurements and store the measurements in a DMS database for correlating the measurements with user activities and patterns);
identifying, based on the diabetes management measurements, multiple diabetes management feedbacks that correspond to the diabetes management measurements (Paragraph [0042] - Pattern Manager display interface 500B for presenting and managing detected patterns according to embodiments of the present invention);
determining one or more of the multiple diabetes management feedbacks having a highest ranking (Paragraph [0081] - The Rank parameter represents the priority level of a particular pattern. It is assigned to each pattern in the group (Type) and it is unique for that particular pattern within the Type (in some embodiments, no two patterns within the same Type have the same Rank)); and
causing the determined diabetes management feedback having the highest ranking to be displayed (Paragraph [0053] - If a certain pattern is detected, then the Pattern Manager module 1004 triggers notification of a new pattern. After acknowledging this notification, a series of UI messages (e.g., screen displays) referred to as IMB Pattern Maps, will be presented to the user one after another depending on the level of choices the user makes on each screen. IMB patterns can be divided into critical IMB patterns and non-critical IMB patterns).
Gass et. al.’507 fails to disclose for each of the multiple diabetes management feedbacks, generating a quantitative improvement metric based on a magnitude of an improvement in the diabetes management measurements and ranking the multiple diabetes management feedbacks based on the respective quantitative improvement metrics. Uchida et. al.’911 teaches providing a degree of improvement to different diabetes management feedbacks and graphically showcasing – ranking - these degrees of improvement to understand what actions contribute to various degrees of improvement (Paragraph [0003] - generate improvement degree display information graphically showing the degree of improvement in lifestyle…improvement degree display information are pieces of data that can be displayed on one sheet, the lifestyle question information includes only actions that contribute to improvement of blood sugar level, and the improvement degree display information indicates a degree of execution of an action that contributes to improvement of blood sugar level). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the rank parameter of Gass et. al.’507 to include assigning degrees of improvement and identifying patterns of improvement based on those degrees in order to better identify what contributions affect diabetes management within a user the most as seen in Uchida et. al.’911.
Regarding Claim 2, Gass et. al.’507 discloses the multiple diabetes management feedbacks correspond to different time periods of a day, and the determining includes ranking, for one time period of the day, the multiple diabetes management feedbacks that correspond to the one time period of the day (Paragraph [0025] - it is useful to identify numerous patterns related to blood glucose readings over time to help PWDs better manage their health. Examples of such patterns include critical low meter reading, critical high meter reading, test frequency low, test frequency fair, test frequency good, testing mostly same time, high for the time of day, low for the time of day, best time of day, fasting high, fasting low, pre-lunch high, pre-lunch low, pre-throughout high, pre-dinner low, post dinner high, post dinner low, running high, running low, day of week low, day of week high, etc….Embodiments of the present invention provide interface facilities and features to help the user manage, filter, and prioritize notices and reminders).
Regarding Claim 5, Gass et. al.’507 discloses the determining includes determining that a diabetes management feedback that was caused to be displayed within a threshold number of preceding days is not the highest ranking diabetes management feedback (Paragraph [0117] - In some embodiments, when a user selects an Archived pattern that is in either “Dismissed” (“Dismissed_Rem”, “Dismissed_Setup”) or “Timed-Out” status, the Pattern Manager may display a “Modified Pattern Interpretation” screen at process block 3504. The “Modified Pattern Interpretation” screen may, in addition to the information offered in a regular “Pattern Interpretation” screen, enable a user to (1) see the state of the pattern, and (2) select from the following options: (a) see records that contributed to this pattern being detected (starting from the first reading contributing to the pattern being detected and ending with the last reading related to the pattern before the pattern was dismissed or timed out), and (b) record a Note; Paragraph [0051] - In some embodiments, IMB pattern detection will generally look at 14 days of BGM data history. Note however that some of the patterns consider up to 21 days of history).
Regarding Claim 8, Gass et. al.’507 discloses the multiple diabetes management feedbacks include feedback identifying improvements in glucose measurements for a given time period over one or more previous days (Paragraph [0043] - FIG. 6A is a screenshot of an example display interface 600A for presenting details of a detected “improved” pattern; Figure 6A).
Regarding Claim 9, Gass et. al.’507 discloses the multiple diabetes management feedbacks include feedback identifying a time period of a day during which glucose measurements were within an optimal range (Paragraph [0050] - The following twenty-one patterns are described in detail below…best time of day; Paragraph [0062] - An example of an algorithm or method 1900 for recognizing a best time of day pattern is illustrated as a flowchart in FIG. 19…with the highest number of in-range readings (e.g., values between predefined parameters InRangeLowTarget and InRangeHighTarget)).
Regarding Claim 10, Gass et. al.’507 discloses the multiple diabetes management feedbacks include feedback identifying sustained positive patterns of glucose measurements by the user (Paragraph [0043] - FIG. 6A is a screenshot of an example display interface 600A for presenting details of a detected “improved” pattern; Figure 6A).
Regarding Claim 11, Gass et. al.’507 discloses the multiple diabetes management feedbacks include feedback identifying deviations in glucose measurements between time periods (Paragraph [0037] - The time field 302 is adapted to store data representative of a timestamp that indicates the time a blood glucose reading associated with the entry occurred; Paragraph [0043] - The display interfaces 600A, 600B include a summary area 602, a graph area 604, a status area 606, an explanation area 608, and a “further links” area 610; Paragraph [0052] - Each of the example IMB algorithms described herein are used to trigger a corresponding pattern based on the BG readings and time).
Regarding Claim 12, Gass et. al.’507 discloses the multiple diabetes management feedbacks include feedback identifying potential behavior modification that a user could take to engage in beneficial diabetes management behavior (Paragraph [0076] - following up with user's progress on managing patterns through notifications and reminders, providing informational, motivational and behavioral messages and recording user's notes about associated triggered patterns and BG Records (if applicable) related to the associated patterns).
Regarding Claim 14, Gass et. al.’507 discloses a device (Paragraph [0030] - A DMS device 104) comprising:
a display device (Paragraph [0031] - The processor 202 can be coupled to a display 208 that can include any number of output devices (e.g., such a display, an audio speaker, haptic devices, a vibrator, light emitting diodes (LEDs), a printer, audio output, USB and LAN ports, and the like). The display 208 can be used to communicate with the user to present reminders as well as for conventional output functions);
a feedback generation system, implemented at least in part in hardware, to obtain, from a sensor, diabetes management measurements measured for a user and to identify, based on the diabetes management measurements, multiple diabetes management feedbacks that correspond to the diabetes management measurements (Paragraph [0033] - The processor 202 can be coupled to input device 212 which can, for example, include any number of input devices (e.g., such as a touch screen, “soft” programmable buttons/keys, hardware buttons and switches, keyboard, optical and magnetic readers/scanners, cameras, sensors, transducers, accelerometer, microphones, audio input, USB and LAN ports, and the like); Paragraph [0042] – entire paragraph); and
a feedback presentation system, implemented at least in part in hardware, to determine one of the multiple diabetes management feedbacks having a highest ranking and cause the determined diabetes management feedback having the highest ranking to be displayed (Paragraph [0053] – entire paragraph; Paragraph [0081] – entire paragraph).
Gass et. al.’507 fails to disclose for each of the multiple diabetes management feedbacks, generating a quantitative improvement metric based on a magnitude of an improvement in the diabetes management measurements and ranking the multiple diabetes management feedbacks based on the respective quantitative improvement metrics. Uchida et. al.’911 teaches providing a degree of improvement to different diabetes management feedbacks and graphically showcasing - ranking - these degrees of improvement to understand what actions contribute to various degrees of improvement (Paragraph [0003] - generate improvement degree display information graphically showing the degree of improvement in lifestyle…improvement degree display information are pieces of data that can be displayed on one sheet, the lifestyle question information includes only actions that contribute to improvement of blood sugar level, and the improvement degree display information indicates a degree of execution of an action that contributes to improvement of blood sugar level). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the rank parameter of Gass et. al.’507 to include assigning degrees of improvement and identifying patterns of improvement based on those degrees in order to better identify what contributions affect diabetes management within a user the most as seen in Uchida et. al.’911.
Regarding Claim 15, Gass et. al.’507 discloses the multiple diabetes management feedbacks include feedback identifying improvements in glucose measurements for a given time period over one or more previous days (Paragraph [0043] - FIG. 6A is a screenshot of an example display interface 600A for presenting details of a detected “improved” pattern),
feedback identifying a time period of the day during which glucose measurements were within an optimal range (Paragraph [0050] - The following twenty-one patterns are described in detail below…best time of day; Paragraph [0062] - An example of an algorithm or method 1900 for recognizing a best time of day pattern is illustrated as a flowchart in FIG. 19…with the highest number of in-range readings (e.g., values between predefined parameters InRangeLowTarget and InRangeHighTarget)), and
feedback identifying a sustained positive pattern of glucose measurements by the user (Paragraph [0043] - FIG. 6A is a screenshot of an example display interface 600A for presenting details of a detected “improved” pattern; Figure 6A).
Regarding Claim 16, Gass et. al.’507 discloses the multiple diabetes management feedbacks include feedback identifying potential behavior modification that a user could take to engage in beneficial diabetes management behavior (Paragraph [0076] - following up with user's progress on managing patterns through notifications and reminders, providing informational, motivational and behavioral messages and recording user's notes about associated triggered patterns and BG Records (if applicable) related to the associated patterns).
Regarding Claim 18, Gass et. al.’507 discloses multiple diabetes management feedbacks include: feedback identifying improvements in glucose measurements for a given time period over one or more previous days (Paragraph [0043] - FIG. 6A is a screenshot of an example display interface 600A for presenting details of a detected “improved” pattern; Figure 6A); and
feedback identifying potential behavior modification that a user could take to engage in beneficial diabetes management behavior (Paragraph [0076] - following up with user's progress on managing patterns through notifications and reminders, providing informational, motivational and behavioral messages and recording user's notes about associated triggered patterns and BG Records (if applicable) related to the associated patterns).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Gass et. al.’507 (U.S. Publication Number 20180286507 – previously cited) in view of Uchida et. al.’911 (U.S. Publication Number 20240127911) as applied to Claim 1, and further in view of Rack-Gomer et. al.’823 (U.S. Publication Number 20150289823 – previously cited).
Regarding Claim 6, Gass et. al.’507 in view of Uchida et. al.’911 discloses the method outlined in Claim 1 above as well as the determining one or more of the multiple diabetes management feedbacks having the highest ranking (Paragraph [0053] - If a certain pattern is detected, then the Pattern Manager module 1004 triggers notification of a new pattern. After acknowledging this notification, a series of UI messages (e.g., screen displays) referred to as IMB Pattern Maps, will be presented to the user one after another depending on the level of choices the user makes on each screen) includes:
determining that a glucose level for a user was less than a threshold amount for at least a threshold amount of time during a time period of a day (Paragraph [0054] – entire paragraph; Figure 11); and
determining that feedback indicating the user was in a critically low glucose range during the time period is the highest ranking diabetes management feedback (Paragraph [0025] - Examples of such patterns include critical low meter reading; Paragraph [0027] - in response to the DMS application recognizing one or more patterns in the BGM data (e.g., a set of patterns that collectively indicate a particular status of condition), the DMS application can generate and present recommendations, reminders, and/or warnings to the user. In some embodiments, the reminders presented can be prioritized based upon user defined and/or medical priorities. Higher priority reminders can be presented ahead of, with more intensity than (e.g., with larger text, with brighter highlighting, with different colors, with sound, etc.), and/or more frequently than lower priority reminders).
Gass et. al.’507 fails to disclose determining that feedback indicating the user was in a hypoglycemic range during the time period. Rack-Gomer et. al.’823 teaches determining that feedback indicating the user was in a hypoglycemic range during a time period (Paragraph [0097] - a standard hypoglycemia threshold alert may be set at 70 mg/dL. If the user's glucose level is dropping quickly, such a low threshold alert may not be able to provide the user with enough time to prevent a very low glucose level; Paragraph [0146] - a low glucose level tends to move the value of the GUI again towards a greater value of urgency, that indicating a hypoglycemic state). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Gass et. al.’507 in view of Uchida et. al.’911 that identifies critical low meter readings to include labeling these critically low measurements as “hypoglycemic” as a way to incorporate known language in the art and grasp the criticality of the range as seen in Rack-Gomer et. al.’823.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Gass et. al.’507 (U.S. Publication Number 20180286507 – previously cited) in view of Uchida et. al.’911 (U.S. Publication Number 20240127911), further in view of Rack-Gomer et. al.’823 (U.S. Publication Number 20150289823 – previously cited) as applied to Claim 6 above, and further in view of Hayter et. al.’149 (U.S. Publication Number 20090055149 – previously cited).
Regarding Claim 7, Gass et. al.’507 in view of Uchida et. al.’911 and further in view of Rack-Gomer et. al.’823 discloses the method outlined in Claim 6 above, but fails to disclose the threshold amount comprises 70 mg/dL, and the threshold amount of time comprises 1 percent of the time period of the day. Rack-Gomer et. al.’823 teaches a threshold amount comprises 70mg/dL (Paragraph [0097] - a standard hypoglycemia threshold alert may be set at 70 mg/dL). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Gass et. al.’507 in view of Uchida et. al.’911 that identifies critical low meter reading to include the glucose measurement of 70mg/dL since it is a standard hypoglycemic threshold as seen in Rack-Gomer et. al.’823. Rack-Gomer et. al.’823 further teaches the criticality of readings at this level due to its danger to the user (Paragraph [0223] - Similarly, staying at a low glucose level (e.g., below 70 mg/dL) for two hours can be more dangerous than staying at the same low glucose level for only 20 minutes).
Hayter et. al.’149 teaches a threshold amount of time comprises one percent of the time period of the day (Paragraph [0105] - For example, when the 15 minute glucose data including the current glucose level as well as the past 14 minutes of glucose level data is to be displayed or output to the user, and the determined variance of the 15 data points exceeds a preset threshold level). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Gass et. al.’507 in view of Uchida et. al.’911 to include a threshold timeline based on the necessitated amount of time it takes to gather enough data to accurately depict trends as seen in Hayter et. al.’149. Hayter et. al.’149 also describes that this threshold can be changed based on necessitated trend retrieval (Paragraph [0097] - any other appropriate time intervals to attain an accurate estimation of the glucose trend information).
Claims 13 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Gass et. al.’507 (U.S. Publication Number 20180286507 – previously cited) in view of Uchida et. al.’911 (U.S. Publication Number 20240127911) as applied to Claims 1 and 14 above, and further in view of Hubbard et. al.’387 (WO Patent Publication 2010022387 – previously cited).
Regarding Claim 13, Gass et. al.’507 in view of Uchida et. al.’911 discloses the method outlined in Claim 1 above as well as multiple diabetes management feedbacks including feedback identifying a user’s need to record physical activity whenever no physical activity has been recorded (Paragraph [0027] - a reminder to record exercise is presented to the user in response to the user not recording any exercise for three days), but fails to disclose what a glucose level of the user would have been had a bout of physical activity not been engaged in by the user. Hubbard et. al.’387 teaches providing feedback that identifies a glucose level of a user if physical activity is not engaged in by the user (Page 7 lines 16-22 and Page 8 lines 1-2 – entire section). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Gass et. al.’507 in view of Uchida et. al.’911 to include a predictive glucose trend in order to best understand the affects physical activity has on a user’s glucose level in order to avoid unsafe behaviors or actions in the future as seen in Hubbard et. al.’387 (Page 8 lines 7-11 - By updating the glucose level prediction parameters each time with the different readings of the patient, the present invention is able to track and predict the glucose level at different times of the day and suggest certain recommendations if the level is not in the safe range or there is not any improvement noticed).
Regarding Claim 17, Gass et. al.’507 in view of Uchida et. al.’911 discloses the system outlined in Claim 14 above as well as multiple diabetes management feedbacks including feedback identifying a user’s need to record physical activity whenever no physical activity has been recorded (Paragraph [0027] - a reminder to record exercise is presented to the user in response to the user not recording any exercise for three days), but fails to disclose what a glucose level of the user would have been had a bout of physical activity not been engaged in by the user. Hubbard et. al.’387 teaches providing feedback that identifies a glucose level of a user if physical activity is not engaged in by the user (Page 7 lines 16-22 and Page 8 lines 1-2 – entire section). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the system of Gass et. al.’507 in view of Uchida et. al.’911 to include a predictive glucose trend in order to best understand the affects physical activity has on a user’s glucose level in order to avoid unsafe behaviors or actions in the future as seen in Hubbard et. al.’387 (Page 8 lines 7-11 - By updating the glucose level prediction parameters each time with the different readings of the patient, the present invention is able to track and predict the glucose level at different times of the day and suggest certain recommendations if the level is not in the safe range or there is not any improvement noticed).
Claims 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Gass et. al.’507 (U.S. Publication Number 20180286507 – previously cited) in view of Vaddiraju et. al.’938 (U.S. Publication Number 20180137938 – previously cited), and further in view of Uchida et. al.’911 (U.S. Publication Number 20240127911).
Regarding Claim 19, Gass et. al.’507 discloses a method implemented in a continuous glucose level monitoring system if set up to do so (Paragraph [0026] - enhanced system for managing diabetes; Paragraph [0131] - Devices that are in communication with each other need not be in continuous communication with each other, unless expressly specified otherwise), the method comprising:
obtaining, from a glucose sensor of the continuous glucose level monitoring system (Paragraph [0028] - The DMS 100 includes a BGM 102 that is adapted to couple to a DMS device 104 (e.g., a smart phone, tablet, smart watch, etc. operative to execute a DMS App 110) and/or a computer 106 operative to run a DMS program 112; Figure 1; Paragraph [0033] - The processor 202 can be coupled to input device 212 which can, for example, include any number of input devices…sensors), first glucose measurements measured for a user for a first time period of multiple time periods of a current day (Paragraph [0025] - Examples of such patterns include… high for the time of day, low for the time of day, best time of day, fasting high, fasting low, pre-lunch high, pre-lunch low, pre-throughout high, pre-dinner low, post dinner high, post dinner low);
identifying, based on the glucose measurements, multiple glucose management feedbacks that correspond to the glucose measurements (Paragraph [0042] - Pattern Manager display interface 500B for presenting and managing detected patterns according to embodiments of the present invention. The Pattern Manager display interface 500B includes areas for interactive lists of Active 504, Additional 506, and Archived 508 detected patterns. These categories of detected patterns are discussed in more detail below);
determining one of the multiple glucose feedbacks having a highest ranking (Paragraph [0081] – The Rank parameter represents the priority level of a particular pattern. It is assigned to each pattern in the group (Type) and it is unique for that particular pattern within the Type (in some embodiments, no two patterns within the same Type have the same Rank). Only one pattern from each Type is set to “Active” status automatically by the Pattern Manager. That would be the pattern with the highest priority. For example, a “Running High” pattern and a “Post-Dinner High” pattern might be triggered at the same time. The “running high” may be a sign of an underlying acute abnormality, whereas the “high after dinner” may indicate a need for medication adjustment. The acute abnormality consideration would be a higher priority pattern to alert the user); and
causing the determined glucose feedback having the highest ranking to be displayed (Paragraph [0053] - If a certain pattern is detected, then the Pattern Manager module 1004 triggers notification of a new pattern. After acknowledging this notification, a series of UI messages (e.g., screen displays) referred to as IMB Pattern Maps, will be presented to the user one after another depending on the level of choices the user makes on each screen. IMB patterns can be divided into critical IMB patterns and non-critical IMB patterns).
Gass et. al.’507 fails to disclose the glucose sensor being inserted at an insertion site of the user. Vaddiraju et. al.’938 teaches a glucose sensor being inserted at an insertion site of a user (Paragraph [0025] - monitoring device 102 that is communicatively coupled to a sensing element 104 that is inserted into the body of a patient or otherwise worn by the patient to obtain measurement data indicative of a physiological condition in the body of the patient, such as a sensed glucose level). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Gass et. al.’507 that includes a sensor to include a glucose sensor inserted at an insertion site of a user in order to obtain data in real time as seen in Vaddiraju et. al.’938 (Paragraph [0131] - the monitoring device 102 may be configured to periodically sample the sensing element 104 (e.g., every minute, every five minutes, or the like), and in a real-time mode, automatically provide new measurement data samples to the client device 106 as they become available).
Gass et. al.’507 in view of Vaddiraju et. al.’938 fails to disclose for each of the multiple diabetes management feedbacks, generating a quantitative improvement metric based on a magnitude of an improvement in the diabetes management measurements and ranking the multiple diabetes management feedbacks based on the respective quantitative improvement metrics. Uchida et. al.’911 teaches providing a degree of improvement to different diabetes management feedbacks and graphically showcasing – ranking - these degrees of improvement to understand what actions contribute to various degrees of improvement (Paragraph [0003] - generate improvement degree display information graphically showing the degree of improvement in lifestyle…improvement degree display information are pieces of data that can be displayed on one sheet, the lifestyle question information includes only actions that contribute to improvement of blood sugar level, and the improvement degree display information indicates a degree of execution of an action that contributes to improvement of blood sugar level). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the rank parameter of Gass et. al.’507 in view of Vaddiraju et. al.’938 to include assigning degrees of improvement and identifying patterns of improvement based on those degrees in order to better identify what contributions affect diabetes management within a user the most as seen in Uchida et. al.’911.
Regarding Claim 20, Gass et. al.’507 in view of Vaddiraju et. al.’938 and further in view of Uchida et. al.’911 discloses the method outlined in Claim 19 above. Additionally, Gass et. al.’507 discloses feedback identifying improvements in glucose measurements for a given time period over one or more previous days (Paragraph [0043] - FIG. 6A is a screenshot of an example display interface 600A for presenting details of a detected “improved” pattern; Figure 6A); and
feedback identifying potential behavior modification that a user could take to engage in beneficial diabetes management behavior (Paragraph [0076] - following up with user's progress on managing patterns through notifications and reminders, providing informational, motivational and behavioral messages and recording user's notes about associated triggered patterns and BG Records (if applicable) related to the associated patterns).
Response to Amendment
Applicant's arguments filed 17 October 2025 have been fully considered and they are not entirely persuasive.
Applicant’s amendments have overcome the prior claim objections.
Applicant’s amendments have overcome the prior rejections under 35 U.S.C. 112(b).
Applicant’s amendments and reasonings to overcome the prior 35 U.S.C. 101 Rejections were considered, but they were not found to be persuasive. The applicant has argued that the claims do not address organizing human activities. The examiner notes that the abstract idea is drawn to "Mental Process" for the reasons stated above in Paragraph 3. Furthermore, the applicant is arguing that the claims are directed towards an "improvement in technology", but the examiner notes that the applicant must provide evidence that addresses these improvements beyond just stating that these improvements exists.
Claims 1-2 and 5-20 are rejected under 35 U.S.C. 103 with an additional reference cited as necessitated by amendments, as discussed in Paragraphs 4-8 above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SARAH ANN WESTFALL whose telephone number is (571) 272-3845. The examiner can normally be reached Monday-Friday 7:30am-4:30pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer Robertson can be reached at (571) 272-5001. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SARAH ANN WESTFALL/Examiner, Art Unit 3791
/ETSUB D BERHANU/Primary Examiner, Art Unit 3791
