Performance metrics

• US 10,039,969 B2
• Filed: 03/23/2015
• Issued: 08/07/2018
• Est. Priority Date: 01/15/2009
• Status: Active Grant

• Current Assignee: Avid Sports, Incorporated (Avid Technology Incorporated)
• Original Assignee: Avid Sports, Incorporated (Avid Technology Incorporated)
• Inventors: Burton, Bruce J., Videtich, John, Guthrie, Warren, Johnson, Ryan, Duckworth, Paul
• Primary Examiner(s): Lau, Hoi
• Application Number:
  US14/665,980
• Publication Number:
  US 20150196827A1
• Time in Patent Office: 1,233 Days
• Field of Search: 3406861, 3405731, 3405721, 34053913, 34053911, 382103, 382190, 382115, 348157, 348156, 348159, 348564
• CPC Class Codes: A63B 2220/12 Absolute positions, e.g. by using GPS
• CPC Class Codes: A63B 2220/40 Acceleration
• CPC Class Codes: A63B 2220/806 Video cameras
• CPC Class Codes: A63B 2225/50 Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2244/20 Swimming
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: A63B 71/0616 Means for conducting or scheduling competition, league, tournaments or rankings
• CPC Class Codes: G01C 23/00 Combined instruments indicating more than one navigational value, e.g. for aircraft; Combined measuring devices for measuring two or more variables of movement, e.g. distance, speed or acceleration
• CPC Class Codes: G06V 40/23 Recognition of whole body movements, e.g. for sport training
• CPC Class Codes: G06V 40/28 Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources

Abstract

A method and system relates to locating or otherwise generating positional information for an object, such as but not limited generating positional coordinates for an object attached to an athlete engaging in an athletic event. The positional coordinates may be processed with other telemetry and biometrical information to provide real-time performance metrics while the athlete engages in the athletic event.

Claims

1. A system for generating performance metrics for a user comprising:

at least two arm sensors operable to sense user arm movement in an x, y, and z direction and/or at least one head sensor operable to sense user head movement in an x, y, and z direction;

at least one processor operable to determine performance metrics for the user based on the movement sensed by the arm and/or head sensors;

wherein at least one performance metric determined by at least one of the at least one processor identifies a number of swimming strokes performed by the user between a starting marker and an ending marker based on movement sensed by at least one of the at least two arm sensors and the at least one head sensor;

wherein the number of swimming strokes is determined by correlating x, y, and z values sensed while the user swims between the starting and ending markers with a reference stroke selected from the x, y and z values, the x, y, and z values being used by the arm sensors to quantify movement in the corresponding x, y, and z directions; and

wherein the correlating of the x, y, and z values with the reference stroke includes filtering the x, y, and z values with the reference stroke to identify amplitude peaks, wherein each amplitude peak correlating with at least a P percentage of the reference stroke is counted as one of the number of swimming strokes.

2. The system of claim 1 wherein at least one performance metric determined by at least one of the at least one processor identifies whether left and right arms of the user are performing an alternating swimming stroke based on movement sensed while one of the at least two arm sensors senses user movement of the left arm (referred to as a left arm sensor) and one of the at least two arm sensors senses user movement of the right arm (referred to as a right arm sensor).

3. The system of claim 2 wherein the alternating type swimming stroke is determined in the event a value A is greater than zero, wherein A is determined according to the following formula:

4. The system of claim 1 wherein at least one performance metric determined by at least one of the at least one processors identifies whether the head of the user is orientated to reflect performing one of a head-up type and a head-down type swimming stroke based on movement sensed by the at least one head sensor.

5. The system of claim 4 wherein the head-up type swimming stroke is determined in the event a value H is greater than a threshold and the head-down type swimming stoke is determined in the event the value H is less than the threshold, wherein H is determined according to the following formula:

H=x_H+z_H;

wherein x_H and z_H are values used by the head sensor to quantify movement in the corresponding x and z directions.

6. The system of claim 1 wherein at least one performance metric determined by at least one of the at least one processor identifies whether left and right arms of the user are performing one of a breast stroke and a butterfly swimming stroke based on movement sensed while one of the at least two arm sensors senses user movement of the left arm (referred to as a left arm sensor) and one of the at least two arm sensors senses user movement of the right arm (referred to as a right arm sensor).

7. The system of claim 6 wherein the breast stroke is determined in the event a value B_a is less than a threshold and the butterfly swimming stoke is determined in the event the value B_a is greater than the threshold, wherein B_a is determined according to the following formula:

B_a=avg(x_L+x_R)−

avg(y_L++y_R)

wherein x_L and y_L are values used by the left arm sensor to quantify movement in the corresponding x and y directions; and

wherein x_R and y_R are values used by the right arm sensor to quantify movement in the corresponding x and y directions.

8. The system of claim 1 wherein:

at least one performance metric determined by at least one of the at least one processors identifies whether the head of the user is orientated to reflect performing a crawl type swimming stroke based on movement sensed by the at least one head sensor;

wherein the crawl swimming stroke is determined in the event a value C is greater than a threshold and not determined in the event the value C is less than the threshold, wherein C is determined according to the following formula;

C=y_H/(x_H+z_H);

wherein x_H, y_H, and z_H are values used by the head sensor to quantify movement in the corresponding x, y and z directions.

9. The system of claim 1 wherein:

at least one performance metric determined by at least one of the at least one processor identifies whether left and right arms of the user are performing one of a breast stroke and a butterfly swimming stroke based on movement sensed by the at least one head sensor;

the breast stroke is determined in the event a best-fit of x_H, z_H, and z_H values used by the head sensor to quantify movement in the corresponding x, y and z directions is with one of a plurality of breast stroke correlation filters; and

the butterfly stroke is determined in the event a best-fit of x_H, z_H, and z_H values used by the head sensor to quantify movement in the corresponding x, y and z directions is with one of a plurality butterfly stroke correlation filters.

10. The system of claim 1 further comprising:

the P percentage being at least one of 35% and a value corresponding with a lowest amplitude peak within the greatest ⅔

of the amplitude peaks; and

characterizing a first stroke occurring proximate the starting marker to be a matched stroke in the event the corresponding amplitude peak is at least 50% and a last stroke occurring proximate the ending marker to be a matched stroke in the event the corresponding amplitude peak is at least 50%.

13. The system of claim 1 wherein:

at least one performance metric determined by at least one of the at least one processors identifies a length of time taken for the user to swim one length of a pool based on movement sensed by the at least one head sensor;

the length of time is counted from a start marker to an end marker, wherein the start and end markers are determined based on movement sensed by the at least one head sensor, the start marker corresponding with movement indicating a first push-off event following a first head event, and the end marker corresponding with movement indicating a second push-off event following a second head event

the first and second head events are determined in the event at least one of the following conditions occur;

(i) a head dip defined as z_H−

x_H>

T, wherein T is a threshold and x_H and z_H are values used by the head sensor to quantify movement in the corresponding x and z directions;

(ii) a head throw defined as y_H>

T_d, wherein T_d is a dynamic threshold and y_H is a value used by the head sensor to quantify movement in the y direction; and

(iii) a head roll defined as z_H<

T_z for S number of seconds before the head dip and z_H>

T_z for the S number of seconds following the same head dip, wherein T_z is a threshold and z_H is a value used by the head sensor to quantify movement in the z direction.

14. The system of claim 13 wherein the first and second push-off events are determined in the event z_H−

x_H>

T, wherein T is a threshold and x_H and z_H are values used by the head sensor to quantify movement in the corresponding x and z directions.

11. A system for generating performance metrics for a user comprising:

at least two arm sensors operable to sense user arm movement in an x, y, and z direction and/or at least one head sensor operable to sense user head movement in an x, y, and z direction;

at least one processor operable to determine performance metrics for the user based on the movement sensed by the arm and/or head sensors; and

wherein the number of swimming strokes is determined by correlating x and y values sensed while the user swims between the starting and ending markers with a reference stroke selected from the x and y values, the x and y values being used by the head sensor to quantify movement in the corresponding x and y directions.

12. The system of claim 11 wherein:

the correlating of the x and y values with the reference stroke includes filtering the x and y values with the reference stroke to identify amplitude peaks, wherein each amplitude peak correlating with at least a 35% percentage of the reference stroke is counted as one of the number of swimming strokes; and

at least one of the at least one processor characterizes each of the number of swimming strokes as one of matched and irregular, the matched strokes having amplitude peaks of greater than 79% and each irregular stroke having amplitude peaks of between 79% and 35%.

15. A method of counting a number of strokes performed by a swimmer based a movement signal generated by at least one of an arm sensor and a head sensor during a swum lap, the method comprising:

identifying a dominate stroke period of the swum lap from the movement signal;

selecting a portion of the movement signal coinciding with one of the dominate periods to be a first reference stroke;

filtering the movement signal based on the first reference stroke to identify a number of potential strokes;

determining the number of strokes based on the identified number of potential strokes;

averaging portions of the movement signal corresponding with two or more of the potential strokes to generate a second reference stroke;

filtering the movement signal based on the second reference stroke to identify a number of final strokes; and

determining the number of strokes to be the number of final strokes having amplitudes greater than a threshold.

16. The method of claim 15 further comprising:

centering phase of the first reference stroke to a phase of a first stroke of the swum length prior to filtering the movement signal to identify the number of potential strokes, including aligning the reference stroke relative a beginning of the first stroke, the beginning of the first stroke being determined with an activity-detection filter that filters a region of the first stoke to identify a transition point from no activity to activity, the transition point being the beginning of the first stroke.