DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 9/1/2026 has been entered.
Claim Status
Claims 2-14, 16-21 and 24 are pending for examination.
Response to Arguments / Remarks
Applicant's arguments filed 9/1/2026 have been fully considered.
In response to the “Double Patenting” rejection on page 7, the Office acknowledges Applicant’s intention to file a Terminal Disclaimer at a later stage of examination. Accordingly, the rejection is maintained.
In response to the “Rejections under 35 USC § 112(a)” and “Rejections under 35 USC § 112(b) on pages 7-8, the previous rejections have been withdrawn in view of the amendment. However, the current amendment presents new 35 USC § 112(a) and 35 USC § 112(b) rejections. Please see below for details.
In response to the “Rejections under 35 USC § 102(a)(1)”, the Applicant argues Utley fails to teach the current amendment. Specifically, the limitation in claim 2 that recites “… transmitting information stored in a database specific to a behavioral-modification program to the one or more processors, wherein the information comprises a prompt or communication topic applicable to the behavioral-modification program …” and “ … using the biological state or the event, the user data, and the information to customize a reporting interface …”, and claim 20 that recites “ ... transmitting information stored in a database specific to a behavioral-modification program to a server, wherein the information comprises a prompt or communication topic applicable to the behavioral-modification program; updating a user database maintained in one or more data stores with the plurality of user- specific data and the information; comparing, via at least one of the one or more processors, the biological data to a user-specific baseline derived from previously collected biological data of the user; using the activity, the comparison, the plurality of user-specific data, and the information …”.
However, Utley discloses at Figs. 7-14, and para [0077],
“The patient entered data may be received in response to a prompt to the patient on, e.g., a mobile device such as device 104, or entered without prompting on the patient's volition. For example, some of the patient entered data may include information regarding phone calls, athletics, work, sport, stress, sex, drinking, smoking, and other suitable patient entered data.”,
and
para [0094]
“At step 704, the processor receives patient entered data in response to a prompt displayed to the patient on, e.g., a smart phone, and/or patient data entered without a prompt on the patient's volition. The patient entered data may include stressors, life events, location, daily events, administrations of nicotine patches or other formulas, administrations of other drugs for smoking cessation, and other suitable patient entered data.” (emphasis underlined).
The cited paragraph clearly teaches that the mobile device 104 prompts the patient to input patient entered data, such as location, smoke and/or time. Fig. 11 shows an illustration of a prompt screen. The prompt screen displays a question that is applicable to the smoking cessation system (analogous to “behavioral-modification program”). The mobile device transmits the patient’s answer stored in the mobile device’s memory (analogous to “a database specific to a behavioral-modification program”) to server 106 at step 704. The server performs the steps in Figs. 7, 14-18 to determine a baseline or trend that is used to detect smoking events based on the patient’s biological and entered data (analogous to “biological state or the event”) and to dynamically output a dashboard shown in Figs. 22-24 based on the detected smoking event, biological patient data (analogous to “user data”) and patient entered data (analogous to “information”).
In contrast to the Applicant’s argument that Utley uses two biological data types (e.g., PPG and SpCO) from the same category, Utley teaches the use of two distinct categories of information. The first category of information is patient biological data (e.g., CO level) obtained from measurements by the watch 102 and the second category of information is patient entered data (e.g., location, home) obtained from the patient’s manual input via the mobile device 104. Fig 10 and Fig. 11 of Utley clearly show that these two categories of information contain distinct data.
Accordingly, the rejection is maintained in view of Utley.
Non-Statutory Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 2-14, 16-21 and 24 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-14 of U.S. Patent No. 12,136,480 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because the pending claims are obvious modification of the patented claims.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 24 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 24, recites the limitation “wherein the mobile device comprises a server and a processor” in lines 7-8. This limitation does not appear to be supported by the specification. Specifically, Figs. 1 and 9 show the mobile device 56 and the server 60 are distinct entities. In other words, the server is not comprised or part of the mobile device.
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.
Regarding claims 3-8, 12 and 16, recite the limitation “the patient” in various locations. There is insufficient antecedent basis for this limitation in the claim.
Regarding claims 9-11, are also rejected because they depend on claim 7.
Regarding claim 21, recite the limitation “the individual-user” in various locations. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 24, recite the limitation “updating a user database with the user data and the information in the server, wherein the user database is stored locally on the mobile device”. The limitation is indefinite because it is unclear whether the “user database” is located at the server or the mobile device.
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.
Claims 2-5, 7-14 and 16-24 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Utley (WO 2016/164484 A1).
Regarding claim 2, Utley teaches a method for modifying a behavior of a patient (Abstract, System and method for predicating smoking behavior to assist smoking cessation), the method comprising:
collecting user data from the user from a device associated with the user, wherein the device comprises at least one sensor configured to measure biological data of the user, wherein the user data comprises the biological data comprising one or more parameters measured in real-time or near real-time (Fig. 1, para [0058], “When wearing the wearable device for a suitable period of time, e.g., five days, a number of parameters may be measured real-time or near real time.” and para [0071], “Device 102 includes a processor, a memory, and a communications link for sending and receiving data from device 104 and/or server 106. Device 102 includes one or more sensors to measure the patient's smoking behavior based on measuring one or more of the patient's CO, eCO, SpCO, SpO2, heart rate, respiratory rate, blood pressure, body temperature, sweating, heart rate variability, electrical rhythm, pulse velocity, galvanic skin response, pupil size, geographic location, environment, ambient temperature, stressors, life events, and other suitable parameters.”. The watch 102 collects one or more user data in real time);
automatically communicating the user data from the device to one or more processors (Fig .1, Fig. 7 step 702, para [0071], “Device 102 includes a processor, a memory, and a communications link for sending and receiving data from device 104 and/or server 106.”. The watch 102 automatically transmits the patient data to the server 106);
transmitting information stored in a database specific to a behavioral-modification program to the one or more processors, wherein the information comprises a prompt or communication topic applicable to the behavioral-modification program (Fig. 7 step 704, para [0094], “At step 704, the processor receives patient entered data in response to a prompt displayed to the patient on, e.g., a smart phone, and/or patient data entered without a prompt on the patient's volition. The patient entered data may include stressors, life events, location, daily events, administrations of nicotine patches or other formulas, administrations of other drugs for smoking cessation, and other suitable patient entered data.”. The mobile device 104 transmits the patient entered data in response to a prompt to the server 106. The patient entered data (e.g., location) is specific to the disclosed smoking cessation program);
updating a user database maintained in one or more data stores with the user data and the information (Fig. 7, step 706, para [0094], “At step 706, the processor sends instructions to update a patient database with the received data. For example, the processor may transmit the patient data to a healthcare provider server or a cloud server that hosts the patient database.”);
analyzing the user data to determine a biological state or an event associated with the behavior via at least one of the one or more processors (Fig. 7, step 708, para [0095], “At step 708, the processor analyzes the patient data to determine smoking events. The processor may compile the data, analyze the data for trends, and correlate the data either real time or after the evaluation period is complete. For example, the processor may analyze the information to determine CO trends, averages, peaks, shape of curve, and associations, other vital sign trends during day, and how those vitals change before during and after smoking. The processor may analyze the SpCO trends to determine parameters such as total number of cigarettes smoked, average number of cigarettes smoked per day, maximum number of cigarettes smoked per day, intensity of each cigarette smoked, time of day, day of week, associated stressors, geography, location, and movement. For example, the total number of peaks in a given day may indicate the number of cigarettes smoked, while the gradient of each peak may indicate the intensity of each cigarette smoked.”), wherein the at least one processor determines the biological state or the event by compiling parameters of the user data over a period of time to establish a baseline specific to the user (Fig. 7 step 712, para [0096], “At step 712, the processor determines whether the evaluation period has ended. For example, the evaluation period may be five days or another suitable time period.” and para [0064], “In some embodiments, the data collected during the five-day evaluation, while the patient is smoking as usual and prior to the quit program, is used to establish a baseline for a patient's vital signs, e.g., CO, eCO, SpCO level. The system may generate a baseline curve for the patient's vital signs based on variance in CO, eCO, SpCO levels in the collected data. The baseline curve may serve as a reference for comparing against future measurements of the patient's CO, eCO, SpCO levels.”. Fig. 9, run-in period 902. The system obtains the baseline or trend during the evaluation / run-in period.) and detecting a change in the one or more parameters relative to the baseline (Fig. 9, shows the changes to the user’s CO level before and after the smoking cessation program.); and
using the biological state or the event, the user data, and the information to customize a reporting interface (Figs. 8-9 and Figs, 20-24. The cessation program includes a reporting interface that displays the smoking events, CO level, and location and/or time).
Regarding claim 3, Utley teaches the method of claim 2, wherein the patient database includes a plurality of user-specific input data specific to the patient, where the plurality of user-specific input data includes a subset of individual-user biological input data and at least one of a subset of individual-user psychographic information and a subset of individual-user personal information, where at least a portion of the plurality of user-specific input data is previously collected (para [0071], “Device 102 includes one or more sensors to measure the patient's smoking behavior based on measuring one or more of the patient's CO, eCO, SpCO, SpO2, heart rate, respiratory rate, blood pressure, body temperature, sweating, heart rate variability, electrical rhythm, pulse velocity, galvanic skin response, pupil size, geographic location, environment, ambient temperature, stressors, life events, and other suitable parameters.” and para [0131], “at step 1410, the processor determines if the time and/or location are indicative of an expected smoking event. For example, the processor may determine that the patient typically smokes when they wake up in the morning around 7 a.m. In another example, the processor may determine that the patient typically smokes soon after they arrive at work. In yet another example, the processor may determine that the patient typically smokes in the evening whenever they visit a particular restaurant or bar.” Heart rate is biological data, stressor and/or daily smoke in the morning are psychographic data, and life event and/or user location are personal data.).
Regarding claim 4, Utley teaches the method of claim 2, wherein the patient database further includes a behavior summary of the patient, where the behavior summary comprises an association of patient biological input data from the patient with at least one of a plurality of behavioral data supplied by the patient (Fig. 13, the server provides a summary of the user’s progress based on the collected biological data and the user has stopped smoking for 15 days. The user has stopped smoking for 15 days is considered as the user’s behavioral data and time is non-biologic.).
Regarding claim 5, Utley teaches the method of claim 3, wherein the subset of individual-user personal information in the patient database includes information from a group consisting of background, traits, demographics, and previous notes about the patient (para [0058], “For example, some of the patient entered data may include information regarding phone calls, athletics, work, sport, stress, sex, drinking, smoking, and other suitable patient entered data.”).
Regarding claim 7, Utley teaches the method of claim 2, wherein transmitting the patient data is based on a prompt displayed to the patient, wherein the prompt is drawn from a database of behavioral information from a plurality of users (Fig. 11, para [0088], “The patient entered data may be received in response to a prompt to the patient on, e.g., a mobile device such as device 104, or entered without prompting on the patient's volition. For example, some of the patient entered data may include information regarding phone calls, athletics, work, sport, stress, sex, drinking, smoking, and other suitable patient entered data.”. Fig. 11, shows the mobile device displays a prompt to collect patient data. The prompt is a template used by the server to collect behavior information from a plurality of users.).
Regarding claim 8, Utley teaches the method of claim 7, wherein the prompt is configured to be responded to by the patient (Fig. 11 and para [0077], the patient enters the data via the display).
Regarding claim 9, Utley teaches the method of claim 8, wherein the parameters comprise one or more of movement data, location data, and time of day data (Fig. 14, steps 1406-1410, para [0119], “at step 1410, the processor determines if the time and/or location are indicative of an expected smoking event. For example, the processor may determine that the patient typically smokes when they wake up in the morning around 7 a.m. In another example, the processor may determine that the patient typically smokes soon after they arrive at work. In yet another example, the processor may determine that the patient typically smokes in the evening whenever they visit a particular restaurant or bar.”. The server determines whether the user will smoke based movement, location and/or time of day.).
Regarding claim 10, Utley teaches the method of claim 7, wherein the reporting interface allows a coach-counselor to electronically access the database of behavioral information (para [0086], “Server 106 (e.g., a healthcare database server) may receive such data from one or both of devices 102 and 104. In some embodiments, the data may be stored on a combination of one or more of devices 102, 104, and 106. The data may be reported to various stakeholders, such as the patient, patient's doctor, peer groups, family, counselors, employer, and other suitable”.).
Regarding claim 11, Utley teaches the method of claim 7, wherein the behavioral information from the plurality of users includes information from a group consisting of background, traits, demographics, and previous notes about each of the plurality of users (Fig. 11, para [0058], “For example, some of the patient entered data may include information regarding phone calls, athletics, work, sport, stress, sex, drinking, smoking, and other suitable patient entered data.” and para [0119], “at step 1410, the processor determines if the time and/or location are indicative of an expected smoking event. For example, the processor may determine that the patient typically smokes when they wake up in the morning around 7 a.m. In another example, the processor may determine that the patient typically smokes soon after they arrive at work. In yet another example, the processor may determine that the patient typically smokes in the evening whenever they visit a particular restaurant or bar.”).
Regarding claim 12, Utley teaches the method of claim 2, further comprising updating the patient database with the event determined by the processor (Fig. 14, the system detects an expected smoking event at step S1406-1410 and updates the result of the prevention at step 1416 and 1418).
Regarding claim 13, Utley teaches the method of claim 2, wherein the processor is configured to determine a smoking event based on trends of carbon monoxide, exhaled carbon monoxide, or carboxyhemoglobin levels and time (Fig. 14, and para [0119], “At step 1408, the processor determines whether the SpCO trend indicates an expected smoking event.”. and para [0009], “The systems and methods non-invasively can detect and quantify smoking behavior for a patient based on measuring one or more of the patient's biometric data such as CO level or exhaled CO level. However other biometric data can also be used. Such data includes carboxyhemoglobin (SpCO),”).
Regarding claim 14, Utley teaches the method of claim 13, wherein the processor is configured to initiate a prevention protocol upon detection of the smoking event, wherein the prevention protocol comprises an alarm on a mobile device (Fig. 12, Fig. 14, step 1412, para [0120], “The information for the prevention protocol may include instructions for one or more intervention options to initiate when the patient is about to smoke. For example, the processor may initiate an alarm in the patient's mobile phone and display an app screen similar to FIG. 12.”).
Regarding claim 16, Utley teaches the method of claim 2, wherein the patient device comprises a photoplethysmography sensor (Para [0071], “For example, device 102 may include PPG-based sensors for measuring CO, eCO, SpCO and SpO2,”. PPG sensor.).
Regarding claim 17, Utley teaches the method of claim 2, wherein the behavior comprises oral placement of substances (para [0157], “While exemplary embodiments of the systems and methods described above focus on smoking behaviors, examples of which include but are not limited to smoking of tobacco via cigarettes, pipes, cigars, and water pipes, and smoking of illegal products such as marijuana, cocaine, heroin, and alcohol related behaviors, it will be immediately apparent to those skilled in the art that the teachings of the present invention are equally applicable to any number of other undesired behaviors. Such other examples include: oral placement of certain substances, with specific examples including but not limited to placing chewing tobacco and snuff in the oral cavity,”).
Regarding claim 18, Utley teaches the method of claim 2, wherein the behavior comprises transdermal absorption of substances (para [0157], “While exemplary embodiments of the systems and methods described above focus on smoking behaviors, examples of which include but are not limited to smoking of tobacco via cigarettes, pipes, cigars, and water pipes, and smoking of illegal products such as marijuana, cocaine, heroin, and alcohol related behaviors, it will be immediately apparent to those skilled in the art that the teachings of the present invention are equally applicable to any number of other undesired behaviors. Such other examples include: … transdermal absorption of certain substances,”).
Regarding claim 19, Utley teaches the method of claim 2, wherein the behavior comprises nasal ingestion of substances (para [0157], “While exemplary embodiments of the systems and methods described above focus on smoking behaviors, examples of which include but are not limited to smoking of tobacco via cigarettes, pipes, cigars, and water pipes, and smoking of illegal products such as marijuana, cocaine, heroin, and alcohol related behaviors, it will be immediately apparent to those skilled in the art that the teachings of the present invention are equally applicable to any number of other undesired behaviors. Such other examples include: oral placement of certain substances, with specific examples including but not limited to placing chewing tobacco and snuff in the oral cavity, transdermal absorption of certain substances, with specific examples including but not limited to application … nasal sniffing of drugs”).
Regarding claim 20, Utley teaches a method of providing customized content to a user participating in a behavioral-modification program (Abstract, System and method for predicating smoking behavior to assist in smoking cessation), the method comprising:
providing a first database comprised of a plurality of user-specific data specific to the user, wherein at least a portion of the plurality of user-specific data comprises biological data collected from at least one sensor of a device associated with the user (Fig. 1, para [0058], “When wearing the wearable device for a suitable period of time, e.g., five days, a number of parameters may be measured real-time or near real time.” and para [0071], “Device 102 includes a processor, a memory, and a communications link for sending and receiving data from device 104 and/or server 106. Device 102 includes one or more sensors to measure the patient's smoking behavior based on measuring one or more of the patient's CO, eCO, SpCO, SpO2, heart rate, respiratory rate, blood pressure, body temperature, sweating, heart rate variability, electrical rhythm, pulse velocity, galvanic skin response, pupil size, geographic location, environment, ambient temperature, stressors, life events, and other suitable parameters.” and Fig. 7 step 702. The watch 102 collects one or more user data and transmit them to the server 106);
transmitting information stored in a database specific to a behavioral-modification program to a server, wherein the information comprises a prompt or communication topic applicable to the behavioral-modification program (Fig. 7 step 704, para [0094], “At step 704, the processor receives patient entered data in response to a prompt displayed to the patient on, e.g., a smart phone, and/or patient data entered without a prompt on the patient's volition. The patient entered data may include stressors, life events, location, daily events, administrations of nicotine patches or other formulas, administrations of other drugs for smoking cessation, and other suitable patient entered data.”. The mobile device 104 transmits the patient entered data in response to a prompt to the server 106. The patient entered data (e.g., location) is specific to the disclosed smoking cessation program);
electronically monitoring an activity of the user (Fig. 7, step 708, para [0095], “At step 708, the processor analyzes the patient data to determine smoking events.” and Fig. 14, step 1406, para [0119], “At step 1406, the processor analyzes the current and prior measurements for the patient parameters and determines whether a smoking event is expected.”), wherein electronically monitoring the activity comprises receiving the biological data from the device on a continuous, periodic, or per-sample basis (Fig. 7, step 702 and . 14, step 1402. The server receives the patient data continuously in a loop);
updating a user database maintained in one or more data stores with the plurality of user-specific data and the information (Fig. 7, step 706, para [0094], “At step 706, the processor sends instructions to update a patient database with the received data. For example, the processor may transmit the patient data to a healthcare provider server or a cloud server that hosts the patient database.”);
comparing, via at least one of the one or more processors, the biological data to a user-specific baseline derived from previously collected biological data of the user (Fig. 17 step 1706, “At step 1706, the processor compares the current and prior patient data to detect a smoking event. For example, the processor may analyze a spike in CO level of the patient. Detecting the spike may include detecting a relative increase in the patient's CO level from a previously measured baseline. The processor may detect a spike as a change in the slope of the patient's CO trend over a period of time. For example, the CO trend moving from a negative slope to a positive slope may indicate smoking behavior. In another example, the processor may apply one or more algorithms to changes in heart rate, increasing heart rate variability, changes in blood pressure, or variation in other suitable data in order to detect a smoking event.”. The server compares the previously measured baseline with the current patient data to determine a smoking event);
using the activity, the comparison, the plurality of user-specific data, and the information to customize a program-related content (Fig. 22 – Fig. 24, the server uses the comparison from step 1706 to determine a smoking event at step 1708, and uses received CO level and the location/time of the smoking event to generate a dashboard view shown in Figs. 22-24);
electronically transmitting the program-related content to the user as an electronic message (Fig. 19, the server transmits the dashboard view to the mobile device 110 via link 116); and
monitoring an electronic interaction of the user with the program-related content, and modifying a subsequent selection of program-related content based on the electronic interaction (para [0181], “FIG. 23 shows another variation of a dashboard 118 displaying similar information to that shown in FIG. 22. As noted above, the displayed information is customizable. For example, this variation illustrates the eCO load 140 in a graphical display that shows historical data (yesterday's load), current eCO Burden or load, as well as a target level for that of non-smokers. As shown in FIGS. 22 and 23, the individual previous attempts at quitting smoking 138 can be displayed. In addition, the graphical representation 120 of the eCO trend 412 can be illustrated with individual eCO readings (of the respective sample) can be displayed with information regarding the smoking times 426 as well as a graphic showing the time or duration of smoking (as shown by the circles of varying diameter). As noted above, such information can be entered by the portable sampling unit and displayed in additional forms as shown in 126 and 127, which respectively show historical and current data regarding the number of times smoked and the number of whole cigarettes smoked.”. The dashboard allows the user to customize which smoking cessation contents to be displayed. For instance, Fig. 23 shows the user selects to remove content 122 from Fig. 22).
Regarding claim 21, Utley teaches the method of claim 20, wherein the first database further includes a behavior summary of the individual-user, where the behavior summary comprises an association of an individual-user biological input data with at least one of a plurality of behavioral data supplied by the individual-user (Fig. 13, the server provides a summary of the user’s progress based on the collected biological data and the user has stopped smoking for 15 days. The user has stopped smoking for 15 days is considered as the user’s behavioral data and time is non-biologic.).
Regarding claim 24, Utley teaches a method for modifying a behavior of a user (Abstract, System and method for predicating smoking behavior to assist smoking cessation), the method comprising:
collecting user data from the user from a device associated with the user, wherein the device comprises at least one sensor configured to measure biological data of the user, wherein the user data comprises the biological data comprising one or more parameters measured in real-time or near real-time (Fig. 1, para [0058], “When wearing the wearable device for a suitable period of time, e.g., five days, a number of parameters may be measured real-time or near real time.” and para [0071], “Device 102 includes a processor, a memory, and a communications link for sending and receiving data from device 104 and/or server 106. Device 102 includes one or more sensors to measure the patient's smoking behavior based on measuring one or more of the patient's CO, eCO, SpCO, SpO2, heart rate, respiratory rate, blood pressure, body temperature, sweating, heart rate variability, electrical rhythm, pulse velocity, galvanic skin response, pupil size, geographic location, environment, ambient temperature, stressors, life events, and other suitable parameters.”. The watch 102 collects one or more user data in real time);
transmitting the user data from the device to a mobile device, wherein transmitting the user data is automatically entered, wherein the mobile device comprises a server and a processor (Fig. 1, mobile phone 104, para [0074], “Device 104 includes a processor, a memory, and a communications link for sending and receiving data from device 102 and/or server 106. Device 104 may receive data from device 102.” and Fig .1, Fig. 7 step 702, para [0071], “Device 102 includes a processor, a memory, and a communications link for sending and receiving data from device 104 and/or server 106.”. The watch 102 automatically transmits the patient data to the server 106 via mobile device 104);
transmitting information stored in a database specific to a behavioral-modification program to the server, wherein the information comprises a prompt or communication topic applicable to the behavioral-modification program (Fig. 7 step 704, para [0094], “At step 704, the processor receives patient entered data in response to a prompt displayed to the patient on, e.g., a smart phone, and/or patient data entered without a prompt on the patient's volition. The patient entered data may include stressors, life events, location, daily events, administrations of nicotine patches or other formulas, administrations of other drugs for smoking cessation, and other suitable patient entered data.”. The watch 102 / mobile device 104 transmits the patient entered data in response to a prompt to the server 106. The patient entered data (e.g., location) is specific to the disclosed smoking cessation program);
updating a user database with the user data and the information in the server (Fig. 7, step 706, para [0094], “At step 706, the processor sends instructions to update a patient database with the received data. For example, the processor may transmit the patient data to a healthcare provider server or a cloud server that hosts the patient database.”), wherein the user database is stored locally on the mobile device;
analyzing the user data to determine a biological state or an event associated with the behavior (Fig. 7, step 708, para [0095], “At step 708, the processor analyzes the patient data to determine smoking events. The processor may compile the data, analyze the data for trends, and correlate the data either real time or after the evaluation period is complete. For example, the processor may analyze the information to determine CO trends, averages, peaks, shape of curve, and associations, other vital sign trends during day, and how those vitals change before during and after smoking. The processor may analyze the SpCO trends to determine parameters such as total number of cigarettes smoked, average number of cigarettes smoked per day, maximum number of cigarettes smoked per day, intensity of each cigarette smoked, time of day, day of week, associated stressors, geography, location, and movement. For example, the total number of peaks in a given day may indicate the number of cigarettes smoked, while the gradient of each peak may indicate the intensity of each cigarette smoked.”), wherein the processor determines the biological state or the event by compiling parameters of the user data before the event (Fig. 7 step 712, para [0096], “At step 712, the processor determines whether the evaluation period has ended. For example, the evaluation period may be five days or another suitable time period.” and para [0064], “In some embodiments, the data collected during the five-day evaluation, while the patient is smoking as usual and prior to the quit program, is used to establish a baseline for a patient's vital signs, e.g., CO, eCO, SpCO level. The system may generate a baseline curve for the patient's vital signs based on variance in CO, eCO, SpCO levels in the collected data. The baseline curve may serve as a reference for comparing against future measurements of the patient's CO, eCO, SpCO levels.”. Fig. 9, run-in period 902. The system obtains the baseline during the evaluation / run-in period.); and
using the biological state or the event, the user data, and the information in the server to customize a reporting interface (Figs. 8-9 and Figs, 20-24. The cessation program includes a reporting interface that displays the smoking events, CO level, and location and/or time).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 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.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Utley (WO 2016/164484 A1) in view of Cobb (Pub. No.: US 2007/0168501 A1).
Regarding claim 6, Utley teaches the method of claim 3, wherein Utley’s method includes a user input interface to receive user data to assist the user to quit smoking and but fails to expressly teach wherein the subset of individual-user psychographic information in the patient database includes milestones and targets.
However, in the same field of behavior modification, Cobb teaches a method that includes a user input interface to receive the user’s target of quitting smoke within the next 6 months. See Fig. 13 item 112 and Para [0064].
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Utley’s user input interface, such as Fig. 11, to include a target time for quitting smoking to improve performance.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHEN Y WU whose telephone number is (571)272-5711. The examiner can normally be reached Monday-Friday, 10AM-6PM, EST.
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, Quan-Zhen Wang can be reached at 571-272-3114. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ZHEN Y WU/Primary Examiner, Art Unit 2685
