EXTENDING GAMEPLAY WITH PHYSICAL ACTIVITY MONITORING DEVICE

• US 20140257534A1
• Filed: 03/05/2013
• Published: 09/11/2014
• Est. Priority Date: 03/05/2013
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Morris, Daniel, Shariff, Farah, Tom, Dennis, Saponas, T. Scott, Kelner, Ilya, Guillory, Andrew
• Granted Patent: US 8,951,164 B2
• Time in Patent Office: Days
• US Class Current: 700/91
• CPC Class Codes: A63F 13/211 using inertial sensors, e.g. accelerometers or gyroscopes
• CPC Class Codes: A63F 13/212 using sensors worn by the player, e.g. for measuring heart beat or leg activity
• CPC Class Codes: A63F 13/42 by mapping the input signals into game commands, e.g. mapping the displacement of a stylus on a touch screen to the steering angle of a virtual vehicle
• CPC Class Codes: A63F 13/46 Computing the game score
• CPC Class Codes: A63F 13/65 automatically by game devices or servers from real world data, e.g. measurement in live racing competition
• CPC Class Codes: A63F 13/816 Athletics, e.g. track-and-field sports
• CPC Class Codes: A63F 2300/1012 involving biosensors worn by the player, e.g. for measuring heart beat, limb activity
• CPC Class Codes: A63F 2300/105 using inertial sensors, e.g. accelerometers, gyroscopes
• CPC Class Codes: A63F 2300/403 Connection between platform and handheld device
• CPC Class Codes: A63F 2300/6045 for mapping control signals received from the input arrangement into game commands
• CPC Class Codes: A63F 2300/61 Score computation
• CPC Class Codes: A63F 2300/69 Involving elements of the real world in the game world, e.g. measurement in live races, real video
• CPC Class Codes: A63F 2300/8005 Athletics
• CPC Class Codes: A63F 2300/8094 Unusual game types, e.g. virtual cooking
• CPC Class Codes: G06F 17/40 Data acquisition and logging for input to computer G06F3/00

Abstract

A physical activity monitoring device receives an indication of one or more physical activities to be performed as an extension of a game being played on a game system and measures physical activity attributes of a user wearing the physical activity monitoring device. The physical activity monitoring device determines the user'"'"'s progress towards completion of the one or more physical activities based on the physical activity attributes and outputs to the game device an indication of the user'"'"'s progress towards completion of the one or more physical activities.

Claims

1. A method of augmenting a gaming experience, comprising:

at a physical activity monitoring device, receiving from a game system an indication of one or more physical activities to be performed as an extension of a game being played on the game system;

at the physical activity monitoring device, measuring physical activity attributes of a user wearing the physical activity monitoring device;

at the physical activity monitoring device, determining the user'"'"'s progress towards completion of the one or more physical activities based on the physical activity attributes; and

outputting from the physical activity monitoring device to the game device an indication of the user'"'"'s progress towards completion of the one or more physical activities.

2. The method of claim 1, further comprising:

indicating to the user information of the game as affected by progress towards completion of the one or more physical activities.

3. The method of claim 1, further comprising:

at the physical activity monitoring device, calculating one or more current biometric markers for the user performing the one or more physical activities.

4. The method of claim 3, further comprising:

indicating to the user one or more current biometric markers.

5. The method of claim 4, where the one or more current biometric markers include an amount of calories burned by the user performing the one or more physical activities.

6. The method of claim 1, where the physical activity attributes of the user wearing the physical activity monitoring device are measured by a sensor array including one or more sensors included in the physical activity monitoring device.

7. The method of claim 6, where the one or more sensors include an accelerometer.

8. The method of claim 6, further comprising:

at the physical activity monitoring device, automatically determining time intervals where the user is actively engaged in the physical activity based on the physical activity attributes.

9. The method of claim 8, where determining time intervals where the user is actively engaged in the physical activity includes:

acquiring signal information with the sensor array that is representative of the physical activity attributes of the user;

dividing the signal information into overlapping segments;

identifying predetermined signal characteristics for each overlapping segment; and

analyzing the predetermined signal characteristics for each overlapping segment using a supervised classifier trained to recognize if the user is actively engaged in the physical activity during the overlapping segment.

10. The method of claim 9, where the supervised classifier includes a support vector machine, and where analyzing the predetermined signal characteristics further includes:

training the support vector machine with data collected from a plurality of users during time intervals where the users were engaged in a plurality of types of physical activity;

generating a set of transformation vectors and a weight vector representative of a user engaged in a type of physical activity;

multiplying the predetermined signal characteristics by the set of transformation vectors and weight vector to obtain a plurality of multiplication products;

comparing the multiplication products to data sets representative of each of a plurality of predetermined activities where the data sets have been predetermined through machine learning; and

classifying overlapping segments as representative of a type of physical activity.

11. The method of claim 10, where the physical activity monitoring device further includes an aggregator configured to determine a time interval defined by a plurality of classified overlapping segments where the user is likely to be actively engaged in a physical activity.

12. The method of claim 1, further comprising:

determining a number of repetitions of a repetitive physical activity performed by the user with a method that reduces the dimensionality of the signals received from the sensor array.

13. The method of claim 12, where the number of repetitions is determined through a counting method that includes:

counting a number of peaks of the dimensionally reduced signal; and

outputting the number of peaks.

14. The method of claim 13, where the counting method further includes:

determining a set of candidate peaks;

filtering the candidate peaks using local period estimates;

filtering the candidate peaks using amplitude statistics; and

outputting the number of peaks.

15. The method of claim 14, where the counting method further includes:

determining a set of candidate valleys;

filtering the candidate valleys using local period estimates;

filtering the candidate valleys using amplitude statistics;

counting a number of valleys of the dimensionally reduced signal;

comparing the number of valleys to the number of peaks; and

designating the greater of the number of valleys and the number of peaks as a number of repetitions; and

outputting the number of repetitions.

16. A physical activity monitoring device, comprising:

a communication subsystem configured to receive from a game system an indication of one or more physical activities to be performed as an extension of a game being played on the game system;

a sensor array including one or more sensors configured to measure physical activity attributes of a user wearing the physical activity monitoring device;

a controller trained with a machine learning process to determine the user'"'"'s progress towards completion of the one or more physical activities based on the physical activity attributes; and

a reporter configured to output to the game device an indication of the user'"'"'s progress towards completion of the one or more physical activities.

17. The physical activity monitoring device of claim 16, further comprising a supervised classifier.

18. The physical activity monitoring device of claim 17, where the supervised classifier includes a support vector machine.

19. The physical activity monitoring device of claim 17, where the supervised classifier utilizes a machine learning decision tree.

20. A method of augmenting a gaming experience, comprising:

at a physical activity monitoring device, receiving from a game system an indication of one or more physical activities to be performed as an extension of a game being played on the game system;

at the physical activity monitoring device, measuring physical activity attributes of a user wearing the physical activity monitoring device with a sensor array including one or more sensors included in the physical activity monitoring device;

at the physical activity monitoring device worn by the user, automatically determining the user'"'"'s progress towards completion of the one or more physical activities based on the physical activity attributes;

communicating to the user an indication of a game attribute affected by the user'"'"'s progress towards completion of the one or more physical activities; and

outputting from the physical activity monitoring device to the game device an indication of the user'"'"'s progress towards completion of the one or more physical activities.