BACK-FILLING OF GEOLOCATION-BASED EXERCISE ROUTES

• US 20160269868A1
• Filed: 05/19/2016
• Published: 09/15/2016
• Est. Priority Date: 05/19/2016
• Status: Active Grant

• Current Assignee: Fitbit, Inc. (Alphabet Inc.)
• Original Assignee: Fitbit, Inc. (Alphabet Inc.)
• Inventors: Su, Hao-Wei, Niehaus, Logan, Duyan, Peter, Foxlin, Eric, Venkatraman, Subramaniam, Yuen, Shelton Gee Jao, Roberts, Timothy M.
• Granted Patent: US 9,730,027 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A63B 22/02 with movable endless bands , e.g. treadmills other training appliances for running on the spot A63B69/0028
• CPC Class Codes: A63B 22/0605 performing a circular movement, e.g. ergometers
• CPC Class Codes: A63B 2220/12 Absolute positions, e.g. by using GPS
• CPC Class Codes: A63B 2220/13 Relative positions
• 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 2220/40 Acceleration
• CPC Class Codes: A63B 2220/70 Measuring or simulating ambient conditions, e.g. weather, terrain or surface conditions
• CPC Class Codes: A63B 2220/72 Temperature
• CPC Class Codes: A63B 2220/73 Altitude
• CPC Class Codes: A63B 2220/75 Humidity
• CPC Class Codes: A63B 2220/805 : Optical or opto-electronic sensors
• 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 2230/01 : User's weight
• CPC Class Codes: A63B 2230/06 : heartbeat rate only
• CPC Class Codes: A63B 2230/40 : respiratory characteristics
• CPC Class Codes: A63B 2230/50 : temperature
• CPC Class Codes: A63B 2230/60 : muscle strain, i.e. measured on the user
• CPC Class Codes: A63B 2230/70 : body fat
• CPC Class Codes: A63B 2244/20 : Swimming
• CPC Class Codes: A63B 29/00 : Apparatus for mountaineering helmets A42B3/00; non-skid devices or attachments for footwear, e.g. crampons, A43C15/00; breathing masks or helmets for use at high altitudes A62B18/00; picks B25D7/00
• CPC Class Codes: A63B 69/0028 : for running, jogging or speed-walking movable endless bands A63B22/02
• CPC Class Codes: A63B 69/16 : for cycling , i.e. arrangements on or for real bicycles
• CPC Class Codes: G01C 22/006 : Pedometers
• CPC Class Codes: G01S 19/19 : Sporting applications
• CPC Class Codes: G06Q 50/01 : Social networking
• CPC Class Codes: G06Q 50/20 : Education
• CPC Class Codes: G06Q 50/22 : Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: G16Z 99/00 : Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: H04B 1/385 : Transceivers carried on the body, e.g. in helmets
• CPC Class Codes: H04M 1/72454 : according to context-related or environment-related conditions
• CPC Class Codes: H04M 1/72457 : according to geographic location
• CPC Class Codes: H04W 4/027 : using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 4/80 : Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

Abstract

Techniques for automatic tracking of user data for exercises are disclosed. In one aspect, a method of operating a wearable device may involve determining that a user of the wearable device has started an exercise, activating the GPS receiver in response to determining that the user has started the exercise, and detecting a time at which the GPS receiver achieves an initial GPS fix of a location of the wearable device. The method may further involve logging, based on output of the one or more biometric sensors, a first set of user data during a first time interval between the start of the exercise and the detected time of the initial GPS fix, and back-filling an exercise route of the user during the first time interval based on the first set of user data.

Claims

1. A method of operating a wearable device, the wearable device comprising one or more biometric sensors and a global positioning system (GPS) receiver, the method comprising:

determining that a user of the wearable device has started an exercise;

activating the GPS receiver in response to determining that the user has started the exercise;

detecting a time at which the GPS receiver achieves an initial GPS fix of a location of the wearable device;

logging, based on output of the one or more biometric sensors, a first set of user data relating to at least one of distance, direction, and speed of the user during a first time interval between the start of the exercise and the detected time of the initial GPS fix; and

back-filling an exercise route of the user during the first time interval based on the first set of user data.

2. The method of claim 1, wherein activating the GPS receiver comprises turning on the GPS receiver in response to determining that the user has started the exercise.

3. The method of claim 1, further comprising:

retrieving one or more candidate start locations of the exercise from a memory; and

identifying one of the one or more candidate start locations as a start location of the exercise,

wherein the back-filling comprises back-filling the exercise route from the location of the initial GPS fix to the identified start location of the exercise.

4. The method of claim 1, further comprising:

logging a second set of user data corresponding to position data from the GPS receiver collected during a second time interval after the initial GPS fix,

wherein the back-filling of the exercise route is further based on the second set of user data.

5. The method of claim 4, wherein:

the logging of the second set of user data comprises determining one or more second direction vectors representative of the user'"'"'s movement during the second time interval based on the position data from the GPS receiver;

the logging of the first set of user data comprises determining one or more first direction vectors representative of the user'"'"'s movement during the first time interval based on at least one of (i) output of the one or more biometric sensors and (ii) the second direction vectors; and

the back-filling of the exercise route is further based on the one or more of the first and second direction vectors.

6. The method of claim 1, further comprising:

retrieving a plurality of candidate start locations of the exercise from a memory;

logging a second set of user data corresponding to position data from the GPS receiver collected during a second time interval after the initial GPS fix; and

identifying one of the candidate start locations as a start location of the exercise based on the first and second sets of user data,

wherein the back-filling of the exercise route is further based on the second set of user data and the identified start location of the exercise.

7. The method of claim 6, wherein the memory is located in at least one of the wearable device, a paired mobile device, and a server.

8. The method of claim 1, further comprising:

logging a second set of user data corresponding to position data from the GPS receiver collected during a second time interval after the initial GPS fix; and

calibrating the first set of user data based at least in part on the second set of user data,

wherein the back-filling of the exercise route based on the first set of user data comprises back-filling of the exercise route based on the calibrated first set of user data.

9. The method of claim 8, wherein:

the logging of the first set of user data further comprises estimating a stride length of the user during the first time interval,

the logging of the second set of user data further comprising calculating a stride length of the user during the second time interval, and

the calibrating of the first set of user data comprises adjusting the estimated stride length during the first time interval based on the calculated stride length during the second time interval.

10. The method of claim 1, wherein the first set of user data comprises one or more of step count, step rate, stride length, cadence, and a distance-to-cadence ratio for the user.

11. The method of claim 1, further comprising:

receiving input from the user regarding at least one candidate start location; and

storing the at least one candidate start location in a memory.

12. The method of claim 1, wherein the back-filling comprises estimating a start location of the exercise based on the first set of user data, the method further comprising:

storing the estimated start location of the exercise in a memory; and

refining the estimated start location via clustering a plurality of previously stored start locations.

13. The method of claim 1, wherein the back-filling comprises:

estimating a start location of the exercise based on the first set of user data;

retrieving a plurality of candidate start locations of the exercise from a memory;

determining that the estimated start location is within a defined distance from one of the candidate start locations;

selecting the one of the candidate start locations in response to determining that the estimated start location is within the defined distance from the one of the candidate start locations; and

back-filling the exercise route between the selected candidate start location and the location of the initial GPS fix of the location of the wearable device.

14. The method of claim 1, wherein the determining that the user of the wearable device has started the exercise is based on output of the one or more biometric sensors.

15. The method of claim 1, wherein:

the logging of the first set of user data comprises determining one or more direction vectors representative of the user'"'"'s movement during the first time interval based on output of the one or more biometric sensors; and

the back-filling of the exercise route is further based on the determined one or more direction vectors.

16. The method of claim 1, further comprising:

identifying a type of the exercise that the user has started based on comparing the output of the one or more biometric sensors to defined sensor data for a plurality of exercise types;

estimating a rate of periodic movement of the user during the first time interval; and

estimating a distance that the user has traveled during the first time interval based on the rate of periodic movement,

wherein the back-filling of the exercise route is further based on the distance that the user has traveled during the first time interval.

17. A wearable device, comprising:

one or more biometric sensors;

a global positioning system (GPS) receiver;

at least one processor coupled to the one or more biometric sensors and the GPS receiver; and

a memory storing computer-executable instructions for controlling the at least one processor to;

determine that a user of the wearable device has started an exercise;

activate the GPS receiver in response to determining that the user has started the exercise;

detect a time at which the GPS receiver achieves an initial GPS fix of a location of the wearable device;

determine, based on output of the one or more biometric sensors, a first set of user data relating to at least one of distance, direction, and speed of the user during a first time interval between the start of the exercise and the detected time of the initial GPS fix; and

back-fill an exercise route of the user during the first time interval based on the first set of user data.

18. The wearable device of claim 17, wherein activating the GPS receiver comprises turning on the GPS receiver in response to determining that the user has started the exercise.

19. The wearable device of claim 17, wherein the memory further comprises computer-executable instructions for controlling the at least one processor to:

retrieve one or more candidate start locations of the exercise from a memory; and

identify one of the one or more candidate start locations as a start location of the exercise,

wherein the back-filling comprises back-filling the exercise route from the location of the initial GPS fix to the identified start location of the exercise.

20. The wearable device of claim 17, wherein the memory further comprises computer-executable instructions for controlling the at least one processor to:

determine, based on position data from the GPS receiver collected during a second time interval after the initial GPS fix, a second set of user data relating to locations of the wearable device during the second time interval,

wherein the back-filling of the exercise route is further based on the second set of user data.

21. The wearable device of claim 17, wherein the memory further comprises computer-executable instructions for controlling the at least one processor to:

retrieve at plurality of candidate start locations of the exercise from a memory;

determine, based on position data from the GPS receiver collected during a second time interval after the initial GPS fix, a second set of user data relating to locations of the wearable device during the second time interval; and

identify one of the candidate start locations as a start location of the exercise based on the first and second sets of user data,

wherein the back-filling of the exercise route is further based on the second set of user data and the identified start location of the exercise.

22. A non-transitory computer readable storage medium having stored thereon instructions that, when executed, cause a processor of a wearable device to:

determine that a user of the wearable device has started an exercise;

activate a global positioning system (GPS) receiver of the wearable device in response to determining that the user has started the exercise;

detect a time at which the GPS receiver achieves an initial GPS fix of a location of the wearable device;

log, based on output of one or more biometric sensors of the wearable device, a first set of user data relating to at least one of distance, direction, and speed of the user during a first time interval between the start of the exercise and the detected time of the initial GPS fix; and

back-fill an exercise route of the user during the first time interval based on the first set of user data.

23. The non-transitory computer readable storage medium of claim 22, wherein activating the GPS receiver comprises turning on the GPS receiver in response to determining that the user has started the exercise.

24. The non-transitory computer readable storage medium of claim 22, further having stored thereon instructions that, when executed, cause the processor to:

retrieve one or more candidate start locations of the exercise from a memory; and

identify one of the one or more candidate start locations as a start location of the exercise,

wherein the back-filling comprises back-filling the exercise route from the location of the initial GPS fix to the identified start location of the exercise.

25. The non-transitory computer readable storage medium of claim 22, further having stored thereon instructions that, when executed, cause the processor to:

log, based on position data from the GPS receiver collected during a second time interval after the initial GPS fix, a second set of user data relating to locations of the wearable device during the second time interval,

wherein the back-filling of the exercise route is further based on the second set of user data.

26. The non-transitory computer readable storage medium of claim 22, further having stored thereon instructions that, when executed, cause the processor to:

retrieve at plurality of candidate start locations of the exercise from a memory;

log, based on position data from the GPS receiver collected during a second time interval after the initial GPS fix, a second set of user data relating to locations of the wearable device during the second time interval; and

identify one of the candidate start locations as a start location of the exercise based on the first and second sets of user data,

wherein the back-filling of the exercise route is further based on the second set of user data and the identified start location of the exercise.

27. The non-transitory computer readable storage medium of claim 22, further having stored thereon instructions that, when executed, cause the processor to:

log, based on position data from the GPS receiver collected during a second time interval after the initial GPS fix, a second set of user data relating to at least one location of the wearable device during the second time interval; and

calibrate the first set of user data based at least in part on the second set of user data,

wherein the back-filling of the exercise route based on the first set of user data comprises back-filing of the exercise route based on the calibrated first set of user data.

28. A method of operating a wearable device, the wearable device comprising a geolocation sensor, the method comprising:

determining that a user of the wearable device has started an exercise;

activating the geolocation sensor in response to determining that the user has started the exercise;

obtaining an initial geolocation fix of a location of the wearable device from the geolocation sensor;

retrieving one or more candidate start locations of the exercise from a memory;

identifying one of the one or more candidate start locations as a start location of the exercise; and

back-filling an exercise route of the user from the location of the initial geolocation fix to the identified start location of the exercise.

29. The method of claim 28, wherein the wearable device further comprises one or more biometric sensors, the method further comprising:

logging, based on output of the one or more biometric sensors, a first set of user data relating to at least one of distance, direction, and speed of the user during a first time interval between the start of the exercise and a detected time of the initial geolocation fix,

wherein the back-filling is further based on the first set of user data.

30. The method of claim 28, wherein activating the geolocation sensor comprises turning on the geolocation sensor in response to determining that the user has started the exercise.