Extending gameplay with physical activity monitoring device

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 based on signal information received from a sensor array including one or more sensors included in 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;

at the physical activity monitoring device, determining a number of repetitions of a repetitive physical activity performed by the user with a method that reduces a dimensionality of the signal information received from the sensor array; and

outputting from the physical activity monitoring device to the game device system 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 information of the game to the user, the information of the game updated 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 one or more sensors include an accelerometer.

7. The method of claim 1 , 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.

8. The method of claim 7 , 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.

9. The method of claim 8 , 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.

10. The method of claim 9 , 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.

11. The method of claim 1 , 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.

12. The method of claim 11 , 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.

13. The method of claim 12 , 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.

14. 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:

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

divide the signal information into overlapping segments;

identify predetermined signal characteristics for each overlapping segment;

analyze 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; and

automatically determine time intervals where the user is actively engaged in the physical activity based on the physical activity attributes;

determine the user's progress towards completion of the one or more physical activities based on the physical activity attributes during time intervals where the user is actively engaged in the physical activity; and

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

15. The physical activity monitoring device of claim 14 , further comprising a supervised classifier.

16. The physical activity monitoring device of claim 15 , where the supervised classifier includes a support vector machine.

17. The physical activity monitoring device of claim 15 , where the supervised classifier utilizes a machine learning decision tree.

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

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

at the physical activity monitoring device, determining a number of repetitions of a repetitive physical activity performed by the user with a method that reduces a dimensionality of the signal information received from the sensor array;

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 system an indication of the user's progress towards completion of the one or more physical activities.