Calendar Integration Methods and Systems for Presentation of Events Having Combined Activity and Location Information

• US 20130325399A1
• Filed: 08/05/2013
• Published: 12/05/2013
• Est. Priority Date: 09/30/2010
• Status: Active Grant

• Current Assignee: Fitbit, Inc. (Alphabet Inc.)
• Original Assignee: Fitbit, Inc. (Alphabet Inc.)
• Inventors: Yuen, Shelten Gee Jao, Park, James, Lee, Hans Christiansen
• Granted Patent: US 8,712,724 B2
• Time in Patent Office: Days
• US Class Current: 702/178
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2560/045 with a separable interface unit, e.g. for communication
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/222 combined with detection or measurement of physiological parameters, e.g. heart rate
• CPC Class Codes: A61B 5/4806 Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6838 Clamps or clips
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/744 Displaying an avatar, e.g. an animated cartoon character
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G04B 25/00 Indicating the time by other means or by combined means electric or electromechanical indicating G04C ; illumination of dials or hands G04B19/30; indicating the time by acoustic means G04B21/00; arrangements producing acoustic signals at preselected times G04B23/00; continuously indicating the time optically by electric means G04C19/00; producing acoustic time signals by electrical means G04C21/00; devices for cooking eggs A47J29/00
• CPC Class Codes: G06Q 10/1095 Meeting or appointment
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 24/00 : Supervisory, monitoring or testing arrangements
• CPC Class Codes: H04W 4/026 : using orientation information, e.g. compass
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 64/00 : Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

A method includes receiving geo-location data collected over time period. The geo-location data is associated with a monitoring device. The method further includes receiving motion tracking data of the monitoring device. The motion tracking data is collected over time period. The method includes identifying one or more activities. The activities are identified based on inference rules that identify certain activities to have occurred when at least part of the motion tracking data is correlated to the received geo-location data. The method further includes defining a metric for one or more of the identified activities. The metric is associated to a calendar date. The method includes sending the metric to a calendar application with integration instructions. The integration instructions define the calendar date to which the metric will be added.

Claims

1. A method comprising:

receiving geo-location data collected over a period of time, the geo-location data associated with a monitoring device that is configured to be used by a user;

receiving motion tracking data of the monitoring device, the motion tracking data collected over the period of time;

identifying one or more activities for the period of time, the activities being identified based on inference rules that identify certain activities to have occurred when at least part of the motion tracking data is correlated to the received geo-location data;

defining a metric for one or more of the identified activities, the metric being associated to a calendar date; and

sending the metric to a calendar application with integration instructions, the integration instructions defining the calendar date to which the metric will be added, wherein the method is executed by a processor.

2. The method of claim 1, wherein the motion tracking data includes data identifying one or more positions of the monitoring device when worn by the user.

3. The method of claim 1, wherein the inference rules associate a speed between two geo-locations as corresponding to an activity and a motion between two positions as corresponding to an activity.

4. The method of claim 1, wherein at least part of the motion tracking data is correlated to the received geo-location when the geo-location is received at a time the user is performing a motion, the motion used to generate the motion tracking data, wherein the inference rules are used to determine whether the received geo-location identifies a location that is inconsistent with an activity identified using the received motion tracking data.

5. The method of claim 1, wherein the metric includes a number of steps taken during the period of time, or a number of stairs climbed during the period of time, or a number of stairs descended during the time period, or an amount of calories burned during the time period, or a wake-up time of the user, or a bed time of the user, or an amount of time of performing one of the activities, or an amount of time of performing one of the activities at a location, or a combination thereof.

6. The method of claim 1, wherein the calendar application is an application executed on a cloud or an application executed on a computing device.

7. The method of claim 1, wherein the integration instructions include format data for presenting the metric on a calendar when rendered by the calendar application, wherein the integration instructions include instructions regarding a location of the metrics on the calendar and regarding the format data.

8. The method of claim 1, wherein the integration instructions include format data for presenting the metric on a calendar when rendered by the calendar application, wherein the format data includes a size of the metric, or a shape of the metric, or a color of the metric, or a shade of the metric, or a texture of the metric, or a combination thereof.

9. A method comprising:

obtaining geo-location data collected over a period of time associated with a monitoring device that is configured to be used by a user;

obtaining motion tracking data of the monitoring device, the motion tracking data collected over the period of time;

identifying one or more activities for the period of time, the activities being identified based on inference rules that identify certain activities to have occurred when at least part of the motion tracking data is correlated to the received geo-location data;

defining a metric for one or more of the identified activities, the metric being associated to a calendar date; and

executing a calendar application and integration instructions, the integration instructions defining the calendar date to which the metric will be added, wherein the method is executed by a processor.

10. The method of claim 9, wherein the motion tracking data includes data identifying one or more positions of the monitoring device when worn by the user.

11. The method of claim 9, wherein the inference rules associate a speed between two geo-locations as corresponding to an activity and a motion between two positions as corresponding to an activity.

12. The method of claim 9, wherein at least part of the motion tracking data is correlated to the received geo-location when the geo-location is received at a time the user is performing a motion, the motion used to generate the motion tracking data, wherein the inference rules are used to determine whether the received geo-location identifies a location that is inconsistent with an activity identified using the received motion tracking data.

13. A method comprising:

obtaining one or more geo-locations of a monitoring device when used by a user;

determining one or more spatial positions of the monitoring device;

determining one or more times corresponding to the spatial positions and the geo-locations;

determining activity data based on the times, the geo-locations, and the spatial positions, the activity data including one or more activity levels and one or more classes of activities detected by the monitoring device;

determining one or more locations of the monitoring device based on the times, the geo-locations, and the spatial positions;

determining a metric and a description summarizing the metric, the metric associated with the activities performed at the locations based on the activity data and the times; and

displaying a calendar on a screen associated with the monitoring device, the calendar having one or more calendar dates that are populated with the metric and the description.

14. The method of claim 13, wherein the metric is determined over multiple time periods of performance of the activities at the locations.

15. The method of claim 14, further comprising determining a statistical metric of the activities performed at the locations over a time horizon.

16. The method of claim 15, further comprising generating a description of the statistical metric.

17. The method of claim 13, further comprising generating an award based on the statistical metric, the award provided to a user account of the user over the time horizon.

18. The method of claim 13, wherein the metric is determined over multiple time periods of performance of the activities at the locations, the method further comprising generating an award based on the metric, the award provided to a user account of the user.

19. The method of claim 13, further comprising displaying a group of event data in relation to the calendar, the event data including the activity data, one or more identifiers of the locations, and one or more identifiers of the activities.

20. The method of claim 19, further comprising overlaying a map on the event data.

21. The method of claim 20, wherein the map includes a route recorded using the monitoring device during performance of the activities.

22. The method of claim 20, wherein the map is of a different dimension than that of the activity data.

23. The method of claim 19, further comprising receiving a selection of the calendar date, wherein displaying the group of event data includes displaying event data from the group, the event data displayed from the group associated with the calendar date upon receiving the selection.

24. The method of claim 13, further comprising:

receiving a selection of an activity level from the user; and

centering a map on one of the locations for which the activity level is selected.

25. A method comprising:

receiving one or more geo-locations of a monitoring device, the monitoring device usable by a user;

receiving one or more spatial positions of the monitoring device;

receiving one or more times corresponding to the spatial positions and the geo-locations;

determining activity data based on the times, the geo-locations, and the spatial positions, the activity data including one or more activity levels and one or more classes of activities detected by the monitoring device;

determining one or more locations of the monitoring device based on the times, the geo-locations, and the spatial positions;

determining a metric associated with the activities performed at the locations based on the activity data and the times; and

sending the metric to a calendar, the metric being added to a calendar date of the calendar, such that display of the calendar on a screen includes the metric.

26. The method of claim 25, wherein the metric is determined over multiple time periods of performance of the activities at the locations.

27. The method of claim 25, further comprising determining a statistical metric of the activities performed at the locations over a time horizon.

28. The method of claim 27, further comprising generating a description of the statistical metric.

29. The method of claim 27, further comprising generating an award based on the statistical metric, the award provided to a user account of the user over the time horizon.

30. The method of claim 25, wherein the metric is determined over multiple time periods of performance of the activities at the locations, the method further comprising generating an award based on the metric, the award provided to a user account of the user.