CALCULATING AN ESTIMATE OF WIND RESISTANCE EXPERIENCED BY A CYCLIST

• US 20170074897A1
• Filed: 09/14/2016
• Published: 03/16/2017
• Est. Priority Date: 09/16/2015
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: MERMEL, Craig H., TRIETSCH, Daniel M., MOORE, Richard Channing III, SINGH ALVARADO, Alexander, PHAM, Hung A., RAGHURAM, Karthik Jayaraman
• Granted Patent: US 10,699,594 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A63B 2071/063 Spoken or verbal instructions
• CPC Class Codes: A63B 2220/12 Absolute positions, e.g. by using GPS
• CPC Class Codes: A63B 2220/13 Relative positions
• CPC Class Codes: A63B 2220/20 Distances or displacements
• CPC Class Codes: A63B 2220/30 Speed
• CPC Class Codes: A63B 2220/36 Speed measurement by electric or magnetic parameters
• CPC Class Codes: A63B 2220/40 Acceleration
• CPC Class Codes: A63B 2220/51 Force
• CPC Class Codes: A63B 2220/62 Time or time measurement used for time reference, time stamp, master time or clock signal
• CPC Class Codes: A63B 2220/70 Measuring or simulating ambient conditions, e.g. weather, terrain or surface conditions
• CPC Class Codes: A63B 2220/73 Altitude
• CPC Class Codes: A63B 2220/74 Atmospheric pressure
• CPC Class Codes: A63B 2220/76 Wind conditions
• CPC Class Codes: A63B 2220/803 Motion sensors
• CPC Class Codes: A63B 2220/806 Video cameras
• CPC Class Codes: A63B 2220/808 Microphones
• CPC Class Codes: A63B 2225/50 Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2230/06 : heartbeat rate only
• CPC Class Codes: A63B 2244/20 : Swimming
• CPC Class Codes: A63B 69/0028 : for running, jogging or speed-walking movable endless bands A63B22/02
• CPC Class Codes: A63B 69/16 : for cycling , i.e. arrangements on or for real bicycles
• CPC Class Codes: A63B 71/0622 : Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
• CPC Class Codes: G01L 3/247 : by measuring and simultaneously multiplying tractive or propulsive force and velocity
• CPC Class Codes: G01S 19/19 : Sporting applications
• CPC Class Codes: G09B 19/0038 : Sports

Abstract

Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.

Claims

1. A method comprising:

collecting a plurality of time-stamped measurements of position, speed, heading, and altitude of a wearer engaged in an activity;

splitting the plurality of time-stamped measurements of position, speed, and heading into a plurality of straight-line segments;

determining a plurality of time-stamped grade estimates based on one or more of the plurality of time-stamped position, speed, heading, and altitude measurements;

determining a plurality of time-stamped total power outputs of the wearer engaged in the activity;

determining a wind speed;

determining a wind direction; and

estimating one or more of power output due to wind resistance, relative air velocity, coefficient of rolling resistance, coefficient of drag, and exposed surface area based on at least one of the plurality of time-stamped total power outputs, the plurality of time-stamped measurements, the determined wind speed, and the determined wind direction.

2. The method of claim 1, further comprising detecting, by the wearable device, that the activity the wearer is engaged in is a known activity.

3. The method of claim 1, wherein the activity is riding a bicycle.

4. The method of claim 1, wherein the time-stamped measurements are collected at irregular intervals.

5. The method of claim 1, wherein the measurements collected at a particular one of the plurality of time-stamped measurements comprise a subset of the position, speed, heading, altitude, and total power output of the wearer engaged in the activity.

6. The method of claim 1, wherein determining a plurality of time-stamped total power outputs comprises:

measuring a plurality of time-stamped heart rates of the wearer of the device; and

estimating a plurality of time-stamped total power output of the wearer of the device based on the heart rate of the wearer.

7. The method of claim 6, further comprising:

increasing the interval between measurements of time-stamped heart rates after estimating one or more of relative air velocity, coefficient of rolling resistance, coefficient of drag, and exposed surface area; and

estimating total power output based on the plurality of time-stamped measurements and the estimated one or more of relative air velocity, coefficient of rolling resistance, coefficient of drag, and exposed surface area.

8. The method of claim 1, further comprising:

estimating a direction of gravity relative to the wearable device based on motion information from the wearable device;

estimating a hand position of the wearer of the wearable device based on the estimated direction of gravity; and

changing the coefficient of rolling resistance based on the estimated hand position of the wearer.

9. The method of claim 1, wherein determining a wind direction comprises retrieving a wind direction from a remote server and wherein determining a wind direction comprises retrieving a wind direction from the remote server.

10. The method of claim 1, wherein determining a wind direction comprises estimating a direction of the wind based on the plurality of time-stamped total power outputs and the plurality of time-stamped measurements of heading.

11. The method of claim 1, wherein the estimated coefficient of rolling resistance is changed based on a determination of surface roughness made by analyzing a plurality of accelerometer measurements.

12. A wearable device comprising:

a positional sensor for obtaining position, speed, heading, and altitude information of a wearer of the wearable device;

a power output sensor for obtaining data correlated to the total power output of the wearer of the wearable device; and

a processor communicatively coupled to the positional sensor and the power sensor, wherein the processor is configured to;

receive a plurality of time-stamped measurements of position, speed, heading, and altitude information from the positional sensor;

receive power output data from the power output sensor;

split the position, speed, and heading information into a plurality of straight-line segments;

determine a plurality of time-stamped grade estimates based on one or more of the plurality of time-stamped measurements of position, speed, heading, and altitude;

determine a plurality of time-stamped power output measurements from the power output data;

determine a wind speed;

determine a wind direction; and

estimate one or more of power output due to wind resistance, relative air velocity, coefficient of rolling resistance, coefficient of drag, and exposed surface area based on at least one of the plurality of time-stamped total power outputs, the plurality of time-stamped measurements, the determined wind speed, and the determined wind direction.

13. The wearable device of claim 12, wherein the processor is further configured to determine that the user is riding a bicycle.

14. The wearable device of claim 12, wherein the time-stamped measurements are received at regular intervals.

15. The wearable device of claim 12, wherein the power output sensor is a heart rate sensor.

16. The wearable device of claim 12, wherein the processor is further configured to:

estimate a direction of gravity relative to the wearable device based on motion information from a motion sensor communicatively coupled to the processor;

estimate a hand position of the wearer of the wearable device based on the estimated direction of gravity; and

refine the estimate of the coefficient of rolling resistance based on the estimated hand position of the wearer.

17. The wearable device of claim 12, further comprising a network interface communicatively coupled to the processor, wherein determining a wind speed and determining a wind direction comprise retrieving a wind direction and a wind speed from a remote server via the network interface.

18. The wearable device of claim 12, wherein determining a wind direction comprises estimating a direction of the wind based on the plurality of time-stamped total power outputs and the plurality of time-stamped measurements of heading.

19. The wearable device of claim 18, further comprising one or more accelerometers communicatively coupled to the processor, wherein the processor is further configured to:

receive a plurality of acceleration measurements from the one or more accelerometers;

derive a plurality of high-frequency acceleration measurements from the plurality of acceleration measurements; and

change the estimated coefficient of rolling resistance based on the derived plurality of high-frequency acceleration measurements.

20. The wearable device of claim 12, wherein the positional sensor is a companion device with a GPS receiver.