Sensor-based athletic activity measurements
Determining pace or speed based on sensor data may include determining an amount of contact time a user's foot has with a workout surface such as the ground. Contact time may be determined by identifying samples in the sensor data that correspond to various events such as a heelstrike, a toe-off and a subsequent heelstrike. In one example, these events may be identified by determining a sequence of three sample values (e.g., a triplet) that exceeds corresponding thresholds. The validity of an identified triplet (e.g., heelstrike, toe-off and heelstrike) may be confirmed by determining whether a difference between a last event sample and a middle event sample is greater than a difference between the middle event sample and an initial event sample. Once confirmed, a contact time may be determined from the triplet. A linear or non-linear relationship may then be applied to the contact time to determine a speed or pace.
1. A method comprising:
receiving a sensor output signal from a foot-based sensor device, wherein the sensor output signal comprises a plurality of samples;
determining a sample rate corresponding to the sensor output signal;
calculating a primary peak window size for identifying a first heelstrike event, wherein the primary peak window size is based on a ratio between a default sample rate and the sample rate corresponding to the sensor output signal;
determining a sample shift amount for searching for a first toe-off event;
determining a window width for searching for the first toe-off event;
identifying the first toe-off event from a first toe-off search window, wherein the first toe-off search window starts at a current sample shifted by the sample shift amount and extends a sample amount corresponding to the window width;
analyzing a plurality of heelstrike events and toe-off events to determine a performance metric, wherein the plurality of heelstrike events and toe-off events includes the first heelstrike event and the first toe-off event; and
responsive to receiving a user request, providing the determined performance metric to a user display device.
2. The method of claim 1 , further comprising:
calculating a mean value of the sensor output signal from the plurality of samples;
determining a heelstrike threshold based on the mean value; and
determining a toe-off threshold based on the mean value.
3. The method of claim 2 , wherein the sample shift amount is determined and used when a potential heelstrike sample exceeds the heelstrike threshold.
4. The method of claim 1 , wherein the sample shift amount is determined and used after identifying and storing a triplet, the triplet comprising a sequences of a first heelstrike event, a first toe-off event, and a second heelstrike event.
5. The method of claim 4 , wherein analyzing the plurality of heelstrike events and toe-off events includes analyzing a plurality of consecutive triplets.
6. The method of claim 1 , wherein the primary peak window size is determined according to the following formula:
primary peak window size=round( z *Default Rate/Actual Rate),
wherein z corresponds to a constant number, Default Rate corresponds to the default sample rate, Actual Rate corresponds to the determined sample rate, and round corresponds to a round function used to round a resulting value to a nearest integer.
7. The method of claim 1 , wherein the sample shift amount is calculated based on a mean value of the sensor output signal from the plurality of samples and a ratio of the default sample rate to the determined sample rate.
8. The method of claim 1 , wherein the sample shift amount and the window width are periodically updated as the sensor output signal is analyzed.
9. The method of claim 8 , wherein the sample shift amount and the window width are updated in accordance with a predetermined frequency, upon prompting by a user, or upon detection of a shift in a determined performance metric.
10. The method of claim 1 , wherein the sensor output signal is an accelerometer output signal, and wherein the determined performance metric includes a pace.
11. A performance monitoring apparatus comprising:
a foot-based sensor; and
at least one processor configured to:
receive a sensor output signal from the foot-based sensor, wherein the sensor output signal comprises a plurality of samples;
determine a sample rate corresponding to the sensor output signal;
calculate a primary peak window size for identifying a first heelstrike event;
determine a sample shift amount and a window width for searching for a first toe-off event;
identify the first toe-off event from a first toe-off search window, wherein the first toe-off search window starts at a current sample shifted by the sample shift amount and extends a sample amount corresponding to the window width;
analyze a plurality of heelstrike events and toe-off events to determine a performance metric, wherein the plurality of heelstrike events and toe-off events includes the first heelstrike event and the first toe-off event; and
provide the determined performance metric to a user display device.
12. The performance monitoring apparatus of claim 11 , wherein the at least one processor is further configured to:
calculate a mean value of the sensor output signal from the plurality of samples;
determine a heelstrike threshold based on the mean value; and
determining a toe-off threshold based on the mean value.
13. The performance monitoring apparatus of claim 12 , wherein the sample shift amount is determined and used when a potential heelstrike sample exceeds the heelstrike threshold.
14. The performance monitoring apparatus of claim 11 , wherein the sample shift amount is determined and used after identifying and storing a triplet, the triplet comprising a sequences of a first heelstrike event, a first toe-off event, and a second heelstrike event.
15. The performance monitoring apparatus of claim 14 , wherein analyzing the plurality of heelstrike events and toe-off events includes analyzing a plurality of consecutive triplets.
16. The performance monitoring apparatus of claim 11 , wherein the primary peak window size is determined according to the following formula:
primary peak window size=round( z *Default Rate/Actual Rate),
wherein z corresponds to a constant number, Default Rate corresponds to a default sample rate, Actual Rate corresponds to the determined sample rate, and round corresponds to a round function used to round a resulting value to a nearest integer.
17. The performance monitoring apparatus of claim 11 , wherein the sample shift amount is calculated based on a mean value of the sensor output signal from the plurality of samples and a ratio of a default sample rate to the determined sample rate.
18. The performance monitoring apparatus of claim 11 , wherein the sample shift amount and the window width are periodically updated as the sensor output signal is analyzed.
19. The performance monitoring apparatus of claim 18 , wherein the sample shift amount and the window width are updated in accordance with a predetermined frequency, upon prompting by a user, or upon detection of a shift in a determined performance metric.
20. The performance monitoring apparatus of claim 11 , wherein the foot-based sensor includes an accelerometer, and wherein the determined performance metric includes a pace.