Synthesizing data sources

• US 10,402,417 B2
• Filed: 04/04/2017
• Issued: 09/03/2019
• Est. Priority Date: 02/09/2017
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Kulshreshtha, Jitendra, Fernandes, Avon
• Primary Examiner(s): Hoang, Son T
• Application Number:
  US15/478,972
• Publication Number:
  US 20180225342A1
• Time in Patent Office: 882 Days
• Field of Search: None
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A63B 2220/17 Counting, e.g. counting periodical movements, revolutions or cycles, or including further data processing to determine distances or speed
• CPC Class Codes: A63B 2220/20 Distances or displacements
• CPC Class Codes: A63B 2220/30 Speed
• CPC Class Codes: A63B 2225/20 with means for remote communication, e.g. internet or the like
• CPC Class Codes: A63B 2225/50 Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2230/06 heartbeat rate only
• CPC Class Codes: A63B 2230/50 temperature
• CPC Class Codes: A63B 2230/75 calorie expenditure
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: G16H 50/00 : ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

In example embodiments, a machine accesses metadata items from multiple different sources associated with a user. The machine determines that metadata items from two or more sources are related to an event of the user, the two or more sources being from among the multiple different sources. The machine stores the metadata items from the two or more of the sources in conjunction with the event.

Claims

1. A system comprising:

one or more processors; and

a memory comprising instructions which, when executed by the one or more processors, cause the one or more processors to perform operations comprising;

accessing user metadata from multiple different sources associated with a user;

determining that metadata items from two or more sources are related to an event of the user, the two or more sources being from among the multiple different sources;

storing the metadata items from the two or more sources in conjunction with the event;

accessing, from one or more data repositories, a set of externa factors related to the event;

storing the set of external factors in conjunction with the event, wherein;

the event comprises a sleep event on a specified night;

the metadata items comprise a heart rate from a wearable heart rate tracker, a sleep start time from a mobile phone, a sleep end time from the mobile phone, and a number of times woken up during the specified night from the mobile phone; and

the set of external factors comprises calendar events of the user from a day preceding the specified night, and weather in a geographic location of the user during the specified night and during the day preceding the specified night; and

providing, to the user, an output representing the event, the metadata items, and the set of external factors.

2. The system of claim 1, wherein:

the set of external factors comprises one or more of;

weather, travel, allergies, diet, or daylight;

the set of external factors occur contemporaneously and in a common geographic location with the event; and

the one or more data repositories are distinct from the multiple different sources.

3. The system of claim 1, wherein the multiple different sources comprise one or more client devices or one or more wearable devices associated with the user.

4. The system of claim 1, wherein the event further comprises one or more of:

a run event, a bike event, or a workout event.

5. The system of claim 1, wherein the determining that the metadata items from the two or more sources are related to the event of the user comprises:

determining that the two or more metadata items occur contemporaneously or determining that the two or more metadata items are associated with a common metric.

6. The system of claim 5, wherein the common metric comprises a number of steps taken during a predefined time period or a distance walked during the predefined time period.

7. The system of claim 1, wherein the user metadata comprise two or more metadata items.

8. The system of claim 1, wherein the set of external factors comprises one or more external factors.

9. A non-transitory machine-readable medium comprising instructions which, when executed by one or more processors of a machine, cause the one or more processors to perform operations comprising:

accessing user metadata from multiple different sources associated with a user;

determining that metadata items from two or more sources are related to an event of the user, the two or more sources being from among the multiple different sources;

storing the metadata items from the two or more sources in conjunction with the event;

accessing, from one or more data repositories, a set of external factors related to the event;

storing the set of external factors in conjunction with the event, wherein;

the event comprises a sleep event on a specified night;

the metadata items comprise a heart rate from a wearable heart rate tracker, a sleep start time from a mobile phone, a sleep end time from the mobile phone, and a number of times woken up during the specified night from the mobile phone; and

the set of external factors comprises calendar events of the user from a day preceding the specified night, and weather in a geographic location of the user during the specified night and during the day preceding the specified night; and

providing, to the user, an output representing the event, the metadata items, and the set of external factors.

10. The machine-readable medium of claim 9, wherein:

the set of external factors comprises one or more of;

weather, travel, allergies, diet, or daylight;

the set of external factors occur contemporaneously and in a common geographic location with the event; and

the one or more data repositories are distinct from the multiple different sources.

11. The machine-readable medium of claim 9, wherein the multiple different sources comprise one or more client devices or one or more wearable devices associated with the user.

12. The machine-readable medium of claim 9, wherein the event further comprises one or more of:

a run event, a bike event, or a workout event.

13. The machine-readable medium of claim 9, wherein the determining that the metadata items from the two or more sources are related to the event of the user comprises:

determining that the two or more metadata items occur contemporaneously or determining that the two or more metadata items are associated with a common metric.

14. The machine-readable medium of claim 13, wherein the common metric comprises a number of steps taken during a predefined time period or a distance walked during the predefined time period.

15. A method implemented by at least one computing device, comprising:

accessing user metadata from multiple different sources associated with a user;

determining that metadata items from two or more sources are related to an event of the user, the two or more sources being from among the multiple different sources;

storing the metadata items from the two or more sources in conjunction with the event;

accessing, from one or more data repositories, a set of external factors related to the event;

storing the set of external factors in conjunction with the event, wherein;

the event comprises a sleep event on a specified night;

the metadata items comprise a heart rate from a wearable heart rate tracker, a sleep start time from a mobile phone, a sleep end time from the mobile phone, and a number of times woken up during the specified night from the mobile phone; and

the set of external factors comprises calendar events of the user from a day preceding the specified night, and weather in a geographic location of the user during the specified night and during the day preceding the specified night; and

providing, to the user, an output representing the event, the metadata items, and the set of external factors.

16. The method of claim 15, wherein:

the set of external factors comprises one or more of;

weather, travel, allergies, diet, or daylight;

the set of external factors occur contemporaneously and in a common geographic location with the event; and

the one or more data repositories are distinct from the multiple different sources.