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 .
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 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 3, 4, 7, 8 and 12 are rejected under pre-AIA 35 U.S.C. 102(a)(1) as being anticipated by US 20210358627 A1 (Longmire et al.) (hereinafter Longmire).
In re claim 1, Longmire discloses a method (Fig. 1, [0003], “This disclosure relates generally to a field of a method and system for utilizing collected caregiver data, patient and physicians to develop improved care plans for patients at home”), comprising: collecting, via a processor (Fig. 3:300, [0033], “The system architecture on a processor 300 includes several modules where metadata is captured, multi-directional communication abilities across stakeholder categories, provision of a dynamic care plan and automatic update methods possible through EHR and patient portal integrations”), metrics that are relevant to a managed or coordinated system ([0005], “This litany of inefficiencies results in the delivery of uncoordinated healthcare and causes critical patient data to become fractured and decentralized”. [0029], “Instant disclosure allows collecting, configuring, analyzing and provide secure data for and by the specific care team to improve patient care”. [0007], “Several embodiments for a system and method towards developing care plans for home-based patients' collected caregiver data, utilizing plurality of mobile technology platforms, applications and devices are disclosed” (collecting relevant data for patient care system). [0008], “The disclosed mobile application is enabled to collect data directly from the informal caregivers about themselves and their corresponding patients, which promotes increased engagement of all stakeholders”); integrating (Fig. 2), via said processor, said collected metrics (Fig. 8, “blood pressure, BMI, glucose”) into a shared communication channel among a plurality of participants (Fig. 10, [0031], “FIG. 1 shows a whole system approach to connect various stake holders, cloud based analysis systems, databases and mobile devices being used by this technology...A physician 104, a patient 106 and a caregiver 108 form a specific closed know team that use a mobile device 112 to connect, share, communicate, present and get feedback”. [0008], “stakeholders may include but are not limited to the clinical care teams, patients, caregivers, healthcare professionals treating the patient, and family and friends of the patient, associated with the various aspects of patients' treatment and improved treatment outcomes” (shared channel for multiple participants such as patient, family, caregiver and doctor)); annotating, via said processor, one or more messages with one or more of said relevant collected metrics and/or derivative data regarding said metrics (Fig. 16 shows annotation in a private chat with the care team, [0032], “FIG. 2 shows a flow chart of system and method for providing an improved patient care by integrating patient, caregivers and physicians as a platform. The patient, caregiver and physicians have secured mobile devices 202 that convey the raw and parsed data to and from mobile device-based application 204 to the analysis engine 206 and from third party API 210. The data gathered from all these interfaces is fed into instantly claimed backend analytical engine 212. The system and analytical engine perform various tasks such as encryption, storage, analysis, audit, Health Insurance Portability and Accountability Act (HIPPA) compliance of strict standards for all outside facing devices, connecting with patient data and most importantly presenting an outcome to the caregiver, physician and patient for a change in condition”); and exchanging, via said processor, said one or more messages between two or more of said plurality of participants (Fig. 9, [0008], “In certain embodiments the disclosed system and method includes utilizing mobile applications allowing the patients' informal caregivers to track patient outcomes and provides informal caregivers guidance through resources relevant to the patient treatment, care and positive treatment outcomes... Such increased engagement of all stakeholders provides enhanced abilities to plan and adjust care through an integrated and dynamic tool with resources and communication pathways at any stage in the patients' chronic disease treatment”. [0009], “In addition, the present invention disclosed herein, as well as the invention itself, is designed to facilitate and improve communication with patients' healthcare team, to improve patient outcomes including symptom reduction, early warning of adverse events and clinical trial and/or study drop out” (derived data and messages shared between the different stakeholders)).
In re claim 3, Longmire discloses the method of claim 1, wherein said metrics comprise any biometric, financial, or system sensor data (Fig. 8, [0058], “The system enables integration capabilities with wearables and sensors for biometric data collection and passive monitoring”).
In re claim 4, Longmire discloses the method of claim 3, said sensor data comprising any of a blood pressure reading, blood glucose reading, electrical activity, whether any of said reading is in range, how a query rate compares to historical averages, systems related readings including any of CPU load and memory usage, and moving averages of stock prices (Fig. 7B, Fig. 8, “glucose mean, range; blood pressure, mean, range”).
In re claim 7, Longmire discloses the method of claim 1, further comprising: using, via said processor, prediction techniques to make available predictive values of said metric values and enable coordinated alerting and visualizing of said predictions ([0017], “FIGS. 7A and 7B show an execution of a machine learning model to output risk level predictions across patients are performed”. [0045], “The system and method generate machine learning models to enable pattern detection and algorithm development with the most sophisticated algorithms including deep learning, decision trees, Bayesian, and unsupervised methods such as clustering”. [0048], “Analytical engine has been leveraged to detect patterns in massive patient generated data sets and generate algorithms for disease prediction and digital biomarkers”. [0050], “the survey information we collect is designed to provide the labels needed for such predictions. These labels primarily include whether the patient is experiencing adverse events. The rest of the data collected can be used to generate models that can predict, before it happens, whether a patient is about to experience adverse event”).
In re claim 8, Longmire discloses the method of claim 7, where said predictive values comprise predictions of a sensed value using a state derived from logged information inferred or specified via one or more communications ([0051], “Additionally, forecasting models can be trained to predict the evolution of patient state in time along these feature dimensions...We designed the instant method and system prediction engine to be robust and self-adapting—as we collect more and more patient information, the system can tune itself to make increasingly better predictions. We will use specialized algorithms to analyze the data collected from the walk tests and the sit/stand tests”. [0049], “These data streams include: EHRs containing diagnosis data, age and other demographic information, and treatment/comorbidity history. After data sets have been standardized, we can run algorithms on the aggregated data to explore correlations and what can be predicted while identifying inputs necessary to make such predictions”).
In re claim 12, Longmire discloses the method of claim 1, further comprising: automatically entering, via said processor, relevant metrics as annotations on each message or subset of said messages (Fig. 12, [0059], “As part of work plan we added virtual communities and support group resource links (URLs/contact information) to the caregiver dashboard and this can be automatically updated by the administrator of the app as an upgrade delivered to the user” (support group links annotated in the messages). [0064], “FIG. 12 medication reminder screen shot enables patient to set medication alerts and reminders, it is easy to design, the schedule can be set by patient or care partners for automated reminders, and proprietary computer vision technology can verify proper pill combinations taken at appropriate time of day” (automatically setting reminders for medications as annotations in the messages)).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over US 20210358627 A1 (Longmire et al.) (hereinafter Longmire) in view of US 20240115211 A1 (CABRERA, JR et al.) (hereinafter CABRERA).
In re claim 2, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: generating, via said processor, time-coordinated charts of said collected metrics; and interleaving said time-coordinated charts, via said processor, directly in-line and interleaved with said one or more messages to provide context for real-time status, coordination, and communication.
CABRERA discloses generating, via said processor, time-coordinated charts of said collected metrics; and interleaving said time-coordinated charts, via said processor, directly in-line and interleaved with said one or more messages to provide context for real-time status, coordination, and communication (Fig. 6, Fig. 13:1308, 1310, Fig. 24A, [0209], “The duration of the predetermined time interval can be selected to be long enough so that analyte sensor system 308 does not consume too much power by transmitting data more frequently than needed, yet frequent enough to provide substantially real-time sensor information (e.g., measured glucose values or analyte data) to display device 310 for output (e.g., via display 345) to a user”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire with that of CABRERA to provide a collaborative messaging system which can analyze, annotate and augment data to provide meaningful feedback and corrective actions. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
Claims 5, 6, 9, 10, 11, 13 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over US 20210358627 A1 (Longmire et al.) (hereinafter Longmire) in view of US 20190250882 A1 (SWANSEY et al.) (hereinafter SWANSEY).
In re claim 5, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: using any of natural language processing (text and/or voice), image recognition, image analysis, video analysis, optical character recognition, and related technologies to extract meaningful logging information automatically from a natural communication conversation.
SWANSEY discloses using any of natural language processing (text and/or voice), image recognition, image analysis, video analysis, optical character recognition, and related technologies to extract meaningful logging information automatically from a natural communication conversation ([0006], “This is difficult in many user environments which may be dirty, dusty or wet, or in bright sunlight, all of which can result in limited legibility of on-screen interface elements. Such programs also are not optimal for workers who: are in motion, driving or operating equipment; need to use their hands to hold tools or touch animals, plants, or equipment, while capturing data where safety or hygiene may be a factor”. [0011], “According to one embodiment, the system includes an application that integrates with an existing, remote sensing online database. This database contains the outline of one or more agricultural interest zones in a particular geographic location and is further identified by the name of the owner of the agricultural interest zone (logging information or some other identifier)...A user may then walk into any agricultural interest zone and, once a “virtual fence” (e.g., geofence) is crossed, the hands-free device may greet the user in a personal way (e.g., announcing “Good morning, Mr. Fred Smith, welcome to Field #5, on the Smith Farm”. [0025], “A worker's utterances in response to or part of the guided voice-interaction are transcribed to an electronic text file via a speech recognition engine of a processor”. [0094], “As the worker interacts with the system the dialog manager can analyze success or failure rates of speech recognition unit 818 and/or natural language processing engine 822 via the use of metadata...For such outliers, the dialog manager can initiate a read back requesting user confirmation, even where a high confidence value is obtained” (can extract user information from natural speech recognition)).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire that provides a collaborative messaging system which can analyze, annotate and knowledge share to provide meaningful conclusions and predictions with that of SWANSEY to be able to automatically extract meaningful logging information from the natural communication among participants, adding relevant metrics and meta data to the messages. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
In re claim 6, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: providing, via said processor, a direct graphical interaction mechanism for entering log data as well as structured entries for specification of state or of an interaction or change of state; and converting, via said processor, said structured entries into human-readable natural language messages shared with other of said participants.
SWANSEY discloses providing, via said processor (Fig. 5:140), a direct graphical interaction mechanism for entering log data as well as structured entries for specification of state or of an interaction or change of state ([0062], “the database management system 120 permits the user 108 to easily access information regarding a particular agricultural interest zone and to spot trends regarding specific crops, locations, pests, etc.” (interaction mechanism for a state or change in state such as trends regarding specific crops). [0120], “A web-based template authoring system may facilitate the customization of a template from a generic baseline template with suggestions and selections for each cell's parametric information (user input or structured entries). A wizard-type interface can lead inexperienced users’ step by step through the template authoring process by presenting questions one at a time (for structured entries). Similarly, an output template depicts the layout and overall content of each report. This “blank” report template would then be populated with user-entered and automated data elements with design elements like logos, colors and fonts as specified or selected by users” (graphical representation of structured entries)); and converting, via said processor, said structured entries into human-readable natural language messages shared with other of said participants ([0011], “Generally, any work activities the user chooses to take within that agricultural interest zone may be digitally tracked, stored, recorded (and optionally) shared with other users or trusted service providers”. [0092], “The speech recognition engine 818 provides a list of the “n” most likely candidates for the worker's response based on the audio, along with respective confidence scores, as is known in the art. A natural language processing engine 822 is also in communication with the processor 802. Results from the speech recognition engine 818 may be passed to the natural language processing engine 822 for further recognition where the worker uses a more natural language approach to data entry” (converting structured data entries from most likely candidates into their natural communications)).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire that provides a collaborative messaging system which can analyze, annotate and knowledge share to provide meaningful conclusions and predictions with that of SWANSEY to be able to automatically extract meaningful logging information from the natural communication among participants, adding relevant metrics and meta data to the messages. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
In re claim 9, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: automatically adding, via said processor, relevant domain-specific metadata to each message; and making available visually, via said processor, said metrics in-line with said messages themselves to avoid transcription errors and omission errors in recording relevant information that provides context to said messages.
SWANSEY discloses automatically adding, via said processor (Fig. 5:140), relevant domain-specific metadata to each message ([0119], “Meta-data documenting the field inspection process can also be used to make reports, highlight trends, perform structured queries, and detect and graph patterns”. [0121], “audio files, tagged with time stamp and location data are saved on the mobile device and cloud database for retrieval by the initiator or other interested users; and an audio report” (adding relevant meta data to the message such as time stamp and location)); and making available visually, via said processor, said metrics in-line with said messages themselves ([0103], “At step 1140, the system/app transcribes any such freeform comments, and may either verbally read them back to the worker or display the transcription on the screen, or both”. [0118], “a section may be present in which the worker may add parenthetical comments about the client, task, environment, or personal reminders. These “private notes” would be viewable and retrievable by the initiator, but not be part of the formatted report designed for distribution to their clients or intended recipient”) to avoid transcription errors and omission errors in recording relevant information that provides context to said messages ([0109], “The worker provides confirmation or correction of marginally recognized voice files which then are fed back into the language model. This loop, in concert with machine learning, is used to increase the effectiveness and accuracy of the system over time”. [0121], “The system may produce a variety of outputs, such as a CSV or spreadsheet format suitable for input to a customer's database containing the values collected for the cells; a print-ready PDF of the completed form with title block, headings and the table of captured values, transcribed notes and photos, captions; an activity log listing any error-handling paths and voice files of confirmed and corrected words; any alerts or warnings triggered by thresholds set in the templates; audio files, tagged with time stamp and location data are saved on the mobile device and cloud database for retrieval by the initiator or other interested users; and an audio report” (such supporting metrics are available visually with the message such as location, time stamp, photos etc. to avoid transcription errors)).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire that provides a collaborative messaging system which can analyze, annotate and knowledge share to provide meaningful conclusions and predictions with that of SWANSEY to be able to automatically extract images, video, and voice in messaging interactions from the natural communication among participants, adding relevant metrics and structured data to the messages. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
In re claim 10, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: automatically understanding, via said processor, any of messages, images, video, and voice in messaging interactions among one or more participants to extract log and/or diary entries from ad-hoc informal communications that are naturally provided by communicating with other participants.
SWANSEY discloses automatically understanding, via said processor, any of messages, images, video, and voice in messaging interactions among one or more participants ([0103], “In yet another alternative embodiment, the worker may begin speaking in a more natural language manner. The worker's statements are transcribed and run through the natural language processing engine 822 to parse out the input field names and associated data” (automatically understanding voice through the natural language processing system). [0086], “According to one embodiment, this functionality may be enhanced by capturing a video of an uprooted plant being inspected and image processing techniques are employed by a smart phone or tablet to pull out data about the crop from the video with little or no input required from the user 108” (automatically understanding the crop from the video with no input from the user). [0075], “For example, the system converts measurements into the proper units, processes videos and/or images to determine their content, converts audio files to text, etc. At step 218, in one embodiment, the system compares the normalized data to the criteria that was requested in the predefined criteria”. [0095], “The processor 802 may thus also have access to text-to-speech functionality. Processor 802 may also have access to various sensors and tools 826 associated with the mobile device 114 or otherwise. For example, sensors 826 may include audio mics, speakers, photographic or video cameras, GPS, or the like. Processor 802 may also include or be in communication with a voice activity detector or voice-operated switch 830 that is used to detect when the worker is speaking”) to extract log and/or diary entries from ad-hoc informal communications that are naturally provided by communicating with other participants ([0020], “Also, the method, wherein the hands-free device comprises a device that receives voice data from the user in a hands-free manner and is configured to convert the voice data to text data”. [0023], “The voice-optimized system enables users to record and document vital operational information safely and effectively while walking around, driving or riding in a vehicle. Data collected may include timestamps, location, images, workflow, observations, voice-files, measurements, sensor readings, and real-time user corrections. This data can be mined for trends, performance metrics and analyzed”. [0008], “The gathered data may include, but is not limited to, crop scouting, animal health/surveillance, farm machinery and equipment statuses, grain management, irrigation system statuses, weather and market forecasting, etc... In these embodiments, live photo, video and audio may be transmitted from the capture process, with transcription of the same by a human, an algorithm, or a combination of both”. [0119], “Meta-data documenting the field inspection process can also be used to make reports, highlight trends, perform structured queries, and detect and graph patterns” (extract structured entries from natural communication)).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire that provides a collaborative messaging system which can analyze, annotate and knowledge share to provide meaningful conclusions and predictions with that of SWANSEY to be able to automatically extract images, video, and voice in messaging interactions from the natural communication among participants, adding relevant metrics and structured data to the messages. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
In re claim 11, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: automatically understanding, via said processor, any of messages, images, video, and voice in messaging interactions among one or more participants from communications that are adapted for logging.
SWANSEY discloses automatically understanding, via said processor (Fig. 5:140), any of messages, images, video, and voice in messaging interactions among one or more participants from communications that are adapted for logging ([0103], “In yet another alternative embodiment, the worker may begin speaking in a more natural language manner. The worker's statements are transcribed and run through the natural language processing engine 822 to parse out the input field names and associated data” (automatically understanding communication through the natural language processing system). [0086], “According to one embodiment, this functionality may be enhanced by capturing a video of an uprooted plant being inspected and image processing techniques are employed by a smart phone or tablet to pull out data about the crop from the video with little or no input required from the user 108” (automatically understanding the crop from the video with no input from the user). [0075], “For example, the system converts measurements into the proper units, processes videos and/or images to determine their content, converts audio files to text, etc. At step 218, in one embodiment, the system compares the normalized data to the criteria that was requested in the predefined criteria”. [0095], “The processor 802 may thus also have access to text-to-speech functionality. Processor 802 may also have access to various sensors and tools 826 associated with the mobile device 114 or otherwise. For example, sensors 826 may include audio mics, speakers, photographic or video cameras, GPS, or the like. Processor 802 may also include or be in communication with a voice activity detector or voice-operated switch 830 that is used to detect when the worker is speaking”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire that provides a collaborative messaging system which can analyze, annotate and knowledge share to provide meaningful conclusions and predictions with that of SWANSEY to be able to automatically extract images, video, and voice in messaging interactions from the natural communication among participants, adding relevant metrics and meta data to the messages. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
In re claim 13, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: determining, via said processor, that every communication has a complete, or a subset of, metadata of relevant metrics; creating, via said processor, a real-time visualization and reflection on said metrics; and recognizing, via said processor, natural communication among said participants without requiring a separate step of logging an action to ensure that a structured log entry is recorded.
SWANSEY discloses determining, via said processor, that every communication has a complete, or a subset of, metadata of relevant metrics ([0125], “The activity flow and voice data be in a format that permits analytics so as to identify trends and correlations and to make comparisons and predictions. This may be in the form of ongoing metrics displayed on a “dashboard,” e.g. weekly tallies of number of fields scouted, reports created, minutes of voice data captured, or miles covered” (communication has metrics such as minutes of voice data captured...etc.”); creating, via said processor, a real-time visualization and reflection on said metrics ([0125], “This may be in the form of ongoing metrics displayed on a “dashboard,” e.g. weekly tallies of number of fields scouted, reports created, minutes of voice data captured, or miles covered. In addition, custom queries can be initiated manually one-by-one (e.g., “display a scatter plot on a map of Missouri showing each time the phrase “Japanese beetle” was uttered in the month of June 2015”); and recognizing, via said processor, natural communication among said participants without requiring a separate step of logging an action to ensure that a structured log entry is recorded ([0103], “In yet another alternative embodiment, the worker may begin speaking in a more natural language manner. The worker's statements are transcribed and run through the natural language processing engine 822 to parse out the input field names and associated data”. [0111], “At step 1312, the system goes to the first (or next, on subsequent runs) space in the data capture template 806, and prompts the worker. As noted previously, the worker may not need prompts, and may alternatively speak the input field names and/or input through a more natural language approach...”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire that provides a collaborative messaging system which can analyze, annotate and knowledge share to provide meaningful conclusions and predictions with that of SWANSEY to be able to automatically extract meaningful logging information from the natural communication among participants, adding relevant metrics and meta data to the messages. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
In re claim 14, Longmire discloses the method of claim 1, but does not explicitly disclose the method further comprising: turning more structured explicit log entries into natural communications.
SWANSEY discloses turning more structured explicit log entries into natural communications ([0092], “The speech recognition engine 818 provides a list of the “n” most likely candidates for the worker's response based on the audio, along with respective confidence scores, as is known in the art. A natural language processing engine 822 is also in communication with the processor 802. Results from the speech recognition engine 818 may be passed to the natural language processing engine 822 for further recognition where the worker uses a more natural language approach to data entry” (converting structured data entries from most likely candidates into their natural communications)).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Longmire that provides a collaborative messaging system which can analyze, annotate and knowledge share to provide meaningful conclusions and predictions with that of SWANSEY to be able to automatically extract meaningful logging information from the natural communication among participants, adding relevant metrics and meta data to the messages. The advantage of doing so is that such a centralized and interactive system finds use in many applications in the trading, gaming and healthcare markets.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SWATI JAIN whose telephone number is (571)270-0699. The examiner can normally be reached Mon - Fri (830 am - 530 pm).
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, Pan Yuwen can be reached on 571-272-7855. 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.
/SWATI JAIN/Examiner, Art Unit 2649
Prosecution Insights