“Data Processing Platform For Individual Use” in Patent Application Approval Process (USPTO 20230185360): Patent Application

2023 JUL 05 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent application by the inventors MCMULLEN, Michele Lee (Seattle, WA, US); MESSENGER, Jared Andrew (Sunnyvale, CA, US); SANGIOVANNI, John (Seattle, WA, US), filed on December 10, 2021, was made available online on June 15, 2023, according to news reporting originating from Washington, D.C., by NewsRx correspondents.

This patent application has not been assigned to a company or institution.

The following quote was obtained by the news editors from the background information supplied by the inventors: “Due to their ubiquity, consumer electronic devices can generate a tremendous amount of data pertaining to all aspects of a user’s daily life. Big data analytics have leveraged access to collective data received through the Internet of Things to design and market products and services. Consumers are inundated with products promising life improvements through the individual tracking of aspects of a user’s activities, health, or wellbeing, yet demand for such products continues unabated. Unfortunately, such individual electronic devices are unable to generate the type of insights that might be realized from a system capable of receiving and analyzing the volume, velocity, and variety of data generated from the user’s daily engagement with multiple electronic devices.

“In the current electronic age, there is also an interest and a need for users of various connected electronic devices to prevent their personal attributes or personal information from being disseminated to a third party that may use the user’s information in such a way that it will damage the user’s reputation in society, monetary worth, self-worth or other user attributes. Moreover, patient privacy laws and consumer privacy laws have been enacted that can make various entities and other third parties liable for the use of and/or dissemination of sensitive user information, such as the Health Insurance Portability and Accountability Act (HIPAA) laws, European Union’s General Data Protection Regulation (GDPR) and California’s California Consumer Privacy Act (CCPA). Therefore, individuals and entities that develop products that receive and use user data need ways to receive and use information relating to a user’s activities, health, or wellbeing so that the information can be used to provide insights that improve aspects of an activity that the user is performing without being concerned about violating privacy laws and also assuring a user that their personal information received by the product will not be delivered to or used by a third party.

“Accordingly, there is a need for a system that solves the problems described above.”

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventors’ summary information for this patent application: “Embodiments herein provide methods, systems, and devices suitable for the analysis of both complex and conventional data pertaining to an individual user or human activity that is received in real-time and/or in batches from a variety of data source types to identify and produce results that benefit the individual user. A system of one or more computers can be configured to perform particular operations or actions of the embodiments by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions.

“One general aspect includes a computer-implemented method for improving user performance. The computer-implemented method includes: a) receiving input data from a plurality of peripheral devices, the plurality of peripheral devices may include one or more interface devices that are integrated with or connected to a user device; (b) analyzing the input data to generate signal stream information that may include a plurality of data analysis streams, each of the plurality of data analysis streams may include time-series results data for a first period of time relating to a user; © generating a plurality of time tags corresponding to second periods of time within the first period of time, where one or more of the plurality of time tags are based on insights relating to the user; and (d) generating a dashboard for display to the user. The dashboard may include a plurality of data analysis stream charts aligned by a common time axis, each chart graphically representing the time-series data over the first time period for a respective one of the plurality of data analysis streams, and a plurality of time-tag representations extending across the plurality of data analysis stream charts at the second time periods.

“One general aspect includes a computer-implemented method for improving the performance of one or more user activities. The computer-implemented method also includes (a) receiving, by a user device, time-series input data generated by a user’s interactions with the user device through a plurality of interface devices; (b) analyzing the time-series input data to generate a plurality of data analysis streams, each of the data analysis streams containing time-series results data relating to the user for a first period of time; © receiving, by use of a user interface application, user insights describing one or more events, ambient conditions, behaviors, mental states, and/or physical states experienced by the user at one or more second periods of time within the first period of time. The method also includes (d) generating one or more system insights, may include: (i)determining that there are changes in at least two of the data analysis streams that happened concurrently or proximately in time and, based on the changes, determining that an event has occurred; or (ii) determining a relationship between one or more of the data analysis streams and a user insight, where generating the one or more system insights may include applying one or more rules stored in memory; and (e) generating a dashboard for display to the user. The dashboard may include graphical representations of one or more of the data analysis streams, the user insights, and the system insights.

“One general aspect of the disclosure provided herein includes a system for improving user performance in one or more activities. The system also includes a plurality of interface devices communicatively coupled to and/or integrated with a user device, where one or more of the plurality of interface devices may include a keyboard device, a camera device, a mouse device, a microphone, or a gaming controller; one or more applications stored in memory, where the one or more applications are configured to: (a) receive time-series input data from the plurality of interface devices; (b) analyze the time-series input data to generate a plurality of data analysis streams, where one or more of the data analysis streams contain time-series results data characterizing an aspect of the user’s performance of an activity on the user device and one or more of the data analysis streams contain time-series results data characterizing an aspect of the user’s behavior during performance of the activity; © receive user insights describing one or more events, ambient conditions, behaviors, mental states, and/or physical states experienced by the user during performance of the activity; and (d) generate a dashboard for display to a user. The dashboard may include graphical representations of one or more of the data analysis streams and the user insights.

“One general aspect includes a computer-implemented platform for improving user performance. The computer-implemented platform also includes a) receiving input data from a plurality of peripheral devices that are integrated with or in communication with a user device, where the plurality of peripheral devices are selected from a group may include interface devices, personal devices, sensors, and virtual devices may include remotely executed non-platform software; (b) analyzing the input data to generate signal stream information may include a plurality of data analysis streams, each of the plurality of data analysis streams may include time-series results data for a first period of time relating to a user; © generating a plurality of time tags corresponding to second periods of time within the first period of time, where one or more of the plurality of time tags are based on insights relating to the user; and (d) generating a dashboard for display. The dashboard may include: a plurality of data analysis stream charts aligned by a common time axis, each chart graphically representing the time-series results data over the first period of time for a respective one of the plurality of data analysis streams; and a plurality of time-tag representations at the second periods of time.

“One general aspect includes a computer-implemented platform for improving user performance, including one or more platform applications stored in memory, where the one or more platform applications are configured to: a) receive time-series data relating to a user during a first period of time, where the time-series data is received from a plurality of peripheral devices that are integrated with or in communication with a user device, where the plurality of peripheral devices are selected from a group may include interface devices, personal devices, sensors, and virtual devices may include locally or remotely executed non-platform software; (b) generate a plurality of time tags corresponding to second periods of time within the first period of time, where one or more of the plurality of time tags are based on insights relating to the user; and © generate a dashboard for display. The dashboard may include signal stream information and a plurality of time-tag representations at the second periods of time, where the signal stream information is represented in a plurality of data analysis stream charts aligned by a common time axis, and the signal stream information may include: (i) one or more data analysis streams received in the time-series data; (ii) one or more data analysis streams generated by an analysis of the time-series data received from the plurality of peripheral devices; or (iii) a combination of (i) and (ii).

“Other embodiments of the above aspects of the disclosure include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

“To facilitate understanding, identical reference numerals have been used, where possible, to designate identical elements that are common to the figures. It is contemplated that elements and features of one embodiment may be beneficially incorporated in other embodiments without further recitation.”

The claims supplied by the inventors are:

“1. A computer-implemented method for improving user performance, health, and wellbeing, comprising: a) receiving input data from a plurality of peripheral devices, the plurality of peripheral devices comprising one or more interface devices that are integrated with or in communication with a user device; (b) analyzing the input data to generate signal stream information comprising a plurality of data analysis streams, each of the plurality of data analysis streams comprising time-series results data for a first period of time relating to a user; © generating a plurality of time tags corresponding to second periods of time within the first period of time, wherein one or more of the plurality of time tags are based on insights relating to the user; and (d) generating a dashboard for display, the dashboard comprising: a plurality of data analysis stream charts aligned by a common time axis, each chart graphically representing the time-series results data over the first period of time for a respective one of the plurality of data analysis streams; and a plurality of time-tag representations extending across the plurality of data analysis stream charts at the second periods of time.

“2. The computer-implemented method of claim 1, wherein the time-series results data relating to the user comprises one or more aspects of the user’s performance of an activity, user’s health, user’s wellbeing, user’s behavior, or user’s surroundings.

“3. The computer-implemented method of claim 1, further comprising: (e) generating a first feedback score for display to the user based on data in at least two of the plurality of data analysis streams; (f) generating one or more recommended actions based on information found in one of the at least two of the plurality of data analysis streams; and (g) presenting the first feedback score and the recommended actions in the dashboard.

“4. The computer-implemented method of claim 1, wherein the insights related to the user are generated by: (i) determining that there are changes in at least two of the data analysis streams that happened concurrently or proximately in time; and (ii) based on (i), determining that an event has occurred.

“5. The computer-implemented method of claim 1, wherein the insights related to the user comprise information relating to the user’s mental or physical state.

“6. The computer-implemented method of claim 1, wherein one or more of the insights relating to the user are based on an event experienced by the user.

“7. The computer-implemented method of claim 1, wherein a first data analysis stream of the plurality of data analysis streams is generated using a first input signal from a first device, and the first data analysis stream characterizes one or more aspects of the user’s interactions with the user device.

“8. The computer-implemented method of claim 7, wherein a second data analysis stream of the plurality of data analysis streams is generated using a second input signal received from a second device, the second device comprising a biometric sensor, and the second data analysis stream characterizes one or more aspects of the user’s physical activity, health, or wellbeing.

“9. The computer-implemented method of claim 8, wherein a third data analysis stream of the plurality of data analysis streams is generated using a third input signal received from a third device, the third device comprises a sensor configured to measure one or more ambient conditions, and the third data analysis stream characterizes one or more ambient conditions experienced by the user.

“10. The computer-implemented method of claim 7, wherein the first device is a keyboard device, and the first data analysis stream characterizes one or more aspects of the user’s interactions with the keyboard device.

“11. The computer-implemented method of claim 10, wherein input data used to generate the first data analysis stream is privacy-filtered event data generated from the first input signal, the privacy-filtered event data comprising destructive key events and constructive key events, the destructive key events comprising delete or backspace key events and the constructive key events comprising one or more generic key events for printable characters.

“12. The computer-implemented method of claim 11, wherein the privacy-filtered event data is free of key events that could be used to identify individual printable characters input by the user.

“13. The computer-implemented method of claim 12, wherein analyzing the input data to generate the first data analysis stream comprises comparing respective counts of constructive key events and destructive key events over repeating intervals of time to periodically characterize one or both of the user’s keyboarding accuracy or keyboarding speed.

“14. The computer-implemented method of claim 1, wherein the insights relating to the user are generated by: (i) periodically requesting the user to select a user insight from a list of predetermined user insights; or (ii) determining that there are changes in at least two of the data analysis streams that happened concurrently or proximately in time; and (iii) based on (ii), requesting that the user select the user insight from the list of predetermined user insights or manually enter a description for a new user insight.

“15. The computer-implemented method of claim 1, wherein analyzing the input data comprises generating privacy-filtered input data by: (i) removing identifiable data from input data received from one or more of the plurality of peripheral devices; (ii) extracting non-identifiable data from input data received from one or more of the plurality of peripheral devices; or (iii) analyzing input data received from one or more of the plurality of peripheral devices to generate non-identifiable metadata.

“16. The computer-implemented method of claim 1, wherein the one or more interface devices comprise a keyboard, a camera, a mouse, a microphone, or a gaming controller.

“17. A computer-implemented method for improving the performance of one or more user activities, comprising: (a) receiving, by a user device, time-series input data generated from a user’s interaction with one or more interface devices that are in communication with the used device; (b) analyzing the time-series input data to generate signal stream information comprising a plurality of data analysis streams, each of the data analysis streams containing time-series results data formed within a first period of time; © receiving, by use of a user interface application, user insights describing one or more events, ambient conditions, behaviors, mental states, and/or physical states experienced by the user at one or more second periods of time within the first period of time; (d) generating one or more system insights, comprising: (i) determining that an event has occurred by determining that there are changes in at least two of the data analysis streams that happened concurrently or proximately in time; or (ii) determining a relationship between one or more of the data analysis streams and a user insight by identifying one or more factors that affect the relationship, wherein the one or more factors are identified by comparing one or more rules stored in memory with the signal stream information; and (e) generating a dashboard for display to the user, the dashboard comprising graphical representations of one or more of the data analysis streams, the user insights, and the system insights.

“18. The computer-implemented method of claim 17, wherein the time-series results data relating to the user comprises one or more aspects of the user’s performance of an activity, user’s health, user’s wellbeing, user’s behavior, or user’s surroundings.

“19. The computer-implemented method of claim 17, wherein the signal stream information is generated from privacy-filtered input data and analyzing the time-series input data comprises generating privacy-filtered input data by: (i) removing identifiable data from input data received from one or more of the interface devices; (ii) extracting non-identifiable data from input data received from one or more of the interface devices; or (iii) analyzing input data received from one or more of the interface devices to generate non-identifiable metadata.

“20. The computer-implemented method of claim 17, further comprising: (f) generating a first feedback score for display to the user based on an analysis of at least two of the plurality of data analysis streams; (g) determining one or more recommended actions that the user can take to improve the first feedback score; and (h) presenting the first feedback score and the recommended actions in the dashboard.”

There are additional claims. Please visit full patent to read further.

URL and more information on this patent application, see: MCMULLEN, Michele Lee; MESSENGER, Jared Andrew; SANGIOVANNI, John. Data Processing Platform For Individual Use. U.S. Patent Application Number 20230185360, filed December 10, 2021 and posted June 15, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20230185360)&db=US-PGPUB&type=ids

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