Monitoring activity of a user in locomotion on foot

• US 8,712,725 B2
• Filed: 06/13/2011
• Issued: 04/29/2014
• Est. Priority Date: 10/02/1997
• Status: Expired due to Fees

• Current Assignee: Nike, Inc.
• Original Assignee: Nike, Inc.
• Inventors: Darley, Jesse, Blackadar, Thomas P.
• Primary Examiner(s): Teixeira Moffat, Jonathan C.
• Assistant Examiner(s): VO, HIEN XUAN
• Application Number:
  US13/158,984
• Publication Number:
  US 20110251822A1
• Time in Patent Office: 1,051 Days
• Field of Search: 702/165, 600/300, 600/481, 600/587, 600/483, 600/502, 600/520
• US Class Current: 702/165
• CPC Class Codes: A43B 23/24 Ornamental buckles; Other ornaments for shoes without fastening function
• CPC Class Codes: A43B 3/0031 provided with a pocket, e.g. for keys or a card
• CPC Class Codes: A43B 3/0078 provided with logos, letters, signatures or the like decoration A43B23/24 takes precedence
• CPC Class Codes: A43B 3/34 with electrical or electronic arrangements
• CPC Class Codes: A61B 2503/10 Athletes
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/08 Sensors provided with means for identification, e.g. barcodes or memory chips
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/6807 Footwear
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/6895 Sport equipment
• CPC Class Codes: A61B 5/7246 : using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/725 : using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7278 : Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/743 : Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/7475 : User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A63B 2024/0065 : Evaluating the fitness, e.g. fitness level or fitness index
• 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 2225/02 : Testing, calibrating or measuring of equipment
• CPC Class Codes: A63B 69/0028 : for running, jogging or speed-walking movable endless bands A63B22/02
• CPC Class Codes: G01C 22/006 : Pedometers
• CPC Class Codes: G01N 2291/02827 : Elastic parameters, strength or force
• CPC Class Codes: G01P 1/023 : for acceleration measuring devices
• CPC Class Codes: G01P 15/08 : with conversion into electric or magnetic values
• CPC Class Codes: G01P 15/0922 : of the bending or flexing mode type
• CPC Class Codes: G04G 21/025 : for measuring physiological data
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Abstract

One disclosed method involves using at least one device supported by a user while the user is in locomotion on foot during an outing to automatically measure amounts of time taken by the user to complete respective distance intervals. During the outing, data representing the automatically measured amounts of time may be automatically stored in memory of the least one device. Another disclosed method involves using at least one device supported by a user while the user is in locomotion on foot during an outing to automatically identify occasions on which a user completes respective distance intervals. During the outing, the at least one device may display at least one of an average pace of the user since a most recently completed distance interval, an average speed of the user since the most recently completed distance interval, and a projected time to complete a current distance interval based on monitored performance since the most recently completed distance interval. Yet another disclosed method involves using at least one device supported by a user while the user is in locomotion on foot during an outing to monitor a distance traveled by the user. An input to the at least one device may be received that specifies a goal distance for the outing, and the at least one device may determine a remaining distance to be traveled to complete one of the specified goal distance for the outing and a calculated fraction of the specified goal distance for the outing.

Claims

1. An apparatus comprising:

a processor; and

a memory comprising computer-executable instructions that, when executed by the processor, causes the apparatus to at least perform;

receiving, via a network, exercise data from a measurement unit that is configured to generate the exercise data based on movement by a user;

calculating, from the exercise data, a fitness index as proportional to a foot contact time multiplied by a heart rate of the user;

updating historical workout information of the user based on the exercise data; and

generating a graphical representation based on the exercise data for presentation.

2. The apparatus of claim 1, wherein the graphical representation depicts a measured exercise parameter over a period of time.

3. The apparatus of claim 1, wherein the memory further comprise computer-executable instructions that, when executed by the processor, further perform at least;

analyzing, by the apparatus, the exercise data to identify changes in pace or speed of the user in response to changes in grades or altitudes.

4. The apparatus of claim 1, wherein the memory further comprises computer-executable instruction that, when executed by the processor, further perform at least;

analyzing, by the apparatus, the exercise data to evaluate changes in pace over a distance during a workout.

5. The apparatus of claim 1, wherein the memory further comprises computer-executable instructions that, when executed by the processor, further perform at least;

analyzing, by the apparatus, the exercise data to determine mileage traveled using a pair of footwear.

6. The apparatus of claim 1, wherein the memory further comprises computer-executable instructions that, when executed by the processor, further perform at least;

analyzing, by the apparatus, the exercise data to determine an average value of an exercise parameter.

7. The apparatus of claim 1, wherein the memory further comprises computer-executable instruction that, when executed by the processor, further perform at least;

analyzing by the apparatus, the exercise data to determine a total value of an exercise parameter.

8. The apparatus of claim 1, wherein the graphical representation depicts multiple performance parameters on a per distance unit basis.

9. The apparatus of claim 1, wherein the memory further comprise computer-executable instructions that, when executed by the processor, further perform at least;

analyzing, by the apparatus, exercise data to determine at least one physiological parameter and at least one performance parameter.

10. The apparatus of claim 1, wherein the fitness index is substantially constant for different combinations of foot contact time and heart rate.

11. A memory storing computer-executable instructions that, when executed, causes an apparatus at least to perform:

receiving, via a network, exercise data from a measurement unit that is configured to generate the exercise data based on movement by a user;

calculating, from the exercise data, a fitness index as proportional to a foot contact time multiple by a heart rate of the user;

updating historical workout information of the user based on the exercise data; and

generating a graphical representation based on the exercise data for presentation.

12. The memory of claim 11, wherein the memory further comprises computer-executable instruction that, when executed by the processor, further perform at least;

analyzing, by the apparatus, the exercise data to identify changes in pace or speed of the user in response to changes in grades or altitudes.

13. The memory of claim 11, wherein the memory further comprises computer-executable instruction that, when executed by the processor, further perform at least;

analyzing, by the apparatus, the exercise data to evaluate changes in pace over a distance during a workout.

14. The memory of claim 11, wherein the memory further comprises computer-executable instruction that, when executed by the processor, further perform at least;

analyzing, by the apparatus, the exercise data to determine mileage traveled using a pair of footwear.

15. The memory of claim 11, wherein the memory further comprises computer-executable instructions that, when executed by the processor, further causes the apparatus to:

analyze the exercise data to determine at least one physiological parameter and at least one performance parameter; and

generate a fitness index of the user based on the at least one physiological parameter and the at least one performance parameter.

16. A computer-implemented method comprising:

receiving, via a network, exercise data from a measurement unit that is configured to generate the exercise data based on movement by a user;

calculating, from the exercise data, a fitness index as proportional to a foot contact time multiplied by rate of the user;

updating, by a computer, historical workout information of the user based on the exercise data; and

generating a graphical representation based on the exercise data for presentation.

17. The method of claim 16, further comprising analyzing the exercise data to identify changes in pace or speed of the user in response to changes in grades or altitudes.

18. The method of claim 16, further comprising analyzing the exercise data to evaluate changes in pace over a distance during a workout.

19. The method of claim 16, further comprising analyzing the exercise data to determine mileage traveled using a pair of footwear.

20. The method of claim 16, further comprising:

analyzing the exercise data to determine at least one physiological parameter and at least one performance parameter; and

generating a fitness index of the user based on the at least one physiological parameter and the at least one performance parameter.