Real-time estimation of speed and gait characteristics using a custom estimator

• US 10,564,288 B2
• Filed: 12/06/2016
• Issued: 02/18/2020
• Est. Priority Date: 12/06/2016
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google LLC (Alphabet Inc.)
• Inventors: Diggelen, Frank Van, Xiao, Ke, Moura, Gustavo, Riley, Wyatt
• Primary Examiner(s): Bui, Bryan
• Application Number:
  US15/370,240
• Publication Number:
  US 20180156920A1
• Time in Patent Office: 1,169 Days
• CPC Class Codes: G01S 19/19 Sporting applications
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
• CPC Class Codes: G01S 19/52 Determining velocity
• CPC Class Codes: H04L 25/03101 Theory of the Kalman algorithm
• CPC Class Codes: H04L 41/22 comprising specially adapted graphical user interfaces [GUI]
• CPC Class Codes: H04W 88/02 Terminal devices

Abstract

In a method for accurately estimating gait characteristics of a user, first parameters indicative of user movement, including a GNSS-derived speed and step count, are monitored. Values of the first parameters are processed to determine values of second parameters indicative of movement of the user. The processing includes applying, as inputs to an estimator (e.g., Kalman filter) having the second parameters as estimator states, values of at least one of the first parameters and/or values of at least one parameter derived from one or more of the first parameters. At least two of the second parameters are collectively indicative of a mapping between step frequency and step length of the user. A graphical user interface may display values of at least one of the second parameters, and/or at least one parameter derived from one or more of the second parameters.

Claims

1. A method, implemented in a computing device, for accurately estimating gait characteristics of a user, the method comprising:

monitoring a first plurality of parameters indicative of movement of the user, wherein monitoring the first plurality of parameters includes monitoring (i) a first GNSS-derived speed of the user and (ii) a step count of the user;

processing values of the monitored first plurality of parameters to determine values of a second plurality of parameters indicative of movement of the user,

wherein processing values of the monitored first plurality of parameters includes

applying, as inputs to an estimator having the second plurality of parameters as estimator states, values of at least one of the monitored first plurality of parameters, and

predicting, at each of a plurality of time intervals, that values of the estimator states are unchanged from respective values of the estimator states at a most recent time interval, and

wherein at least two parameters of the second plurality of parameters are collectively indicative of a mapping between step frequency of the user and step length of the user; and

causing a graphical user interface of the computing device or another computing device to display values of one or both of (i) at least one of the second plurality of parameters, and (ii) at least one parameter derived from one or more of the second plurality of parameters.

2. The method of claim 1, further comprising, prior to processing the values of the monitored first plurality of parameters:

selecting, from among a plurality of gait models, a first gait model corresponding to a current gait type of the user,

wherein the mapping between step frequency of the user and step length of the user is specific to the first gait model.

3. The method of claim 2, wherein the plurality of gait models includes a running gait model and a walking gait model.

4. The method of claim 2, further comprising:

using values of the mapping between step frequency of the user and step length of the user, as output by the estimator, to update the first gait model.

5. The method of claim 1, wherein the at least two parameters of the second plurality of parameters include (i) a slope of a line representing the mapping between step frequency of the user and step length of the user, and (ii) an intercept of the line representing the mapping between step frequency of the user and step length of the user.

6. The method of claim 1, wherein an additional parameter of the second plurality of parameters is a speed of the user.

7. The method of claim 1, wherein:

monitoring the first plurality of parameters includes monitoring (i) the first GNSS-derived speed of the user, (ii) a second GNSS-derived speed of the user, and (iii) the step count of the user;

the first GNSS-derived speed of the user is a speed determined using GNSS location; and

the second GNSS-derived speed of the user is a speed determined using GNSS Doppler shift.

8. The method of claim 1, wherein the estimator is a Kalman filter.

9. The method of claim 8, wherein processing values of the monitored first plurality of parameters further includes dynamically setting values of a process noise covariance used by the Kalman filter.

10. The method of claim 9, wherein dynamically setting values of the process noise covariance includes increasing the process noise covariance when at least the step count of the user indicates the user has stopped.

11. The method of claim 9, wherein dynamically setting values of the process noise covariance includes increasing the process noise covariance when at least the first GNSS-derived speed of the user indicates the user has accelerated or decelerated by more than a threshold amount.

12. The method of claim 1, wherein:

the computing device is a mobile computing device of the user; and

monitoring the first plurality of parameters indicative of movement of the user includes receiving real-time data generated by one or more devices external to the mobile computing device.

13. The method of claim 1, wherein:

the computing device is a server;

monitoring a first plurality of parameters indicative of movement of the user includes receiving, from a mobile computing device of the user via a wireless network, real-time data generated by the mobile computing device; and

causing a graphical user interface to display values includes transmitting, via the wireless network, one or both of (i) data indicative of values of the second plurality of parameters, and (ii) data indicative of values of one or more parameters derived from the second plurality of parameters, to the mobile computing device to cause a graphical user interface of the mobile computing device to display values of one or both of (i) the at least one of the second plurality of parameters, and (ii) the at least one parameter derived from the one or more of the second plurality of parameters.

14. The method of claim 1, comprising:

causing the graphical user interface of the computing device or the other computing device to display a visual representation of the mapping between step frequency of the user and step length of the user.

15. The method of claim 1, wherein applying, as inputs to the estimator, values of at least one of the monitored first plurality of parameters includes (i) deriving values of at least one parameter from one or more of the monitored first plurality of parameters, and (ii) applying the derived values as inputs to the estimator.

16. A non-transitory, computer-readable medium storing instructions that, when executed by one or more processors of a computing device, cause the computing device to:

monitor a first plurality of parameters indicative of movement of a user, wherein the first plurality of parameters includes (i) a first GNSS-derived speed of the user and (ii) a step count of the user;

process values of the monitored first plurality of parameters to determine values of a second plurality of parameters indicative of movement of the user,

wherein processing values of the monitored first plurality of parameters includes

applying, as inputs to an estimator having the second plurality of parameters as estimator states, values of at least one of the monitored first plurality of parameters, and

predicting, at each of a plurality of time intervals, that values of the estimator states are unchanged from respective values of the estimator states at a most recent time interval, and

wherein at least two parameters of the second plurality of parameters are collectively indicative of a mapping between step frequency of the user and step length of the user; and

display on a graphical user interface of the computing device, or cause a graphical user interface of another computing device to display, values of one or both of (i) at least one of the second plurality of parameters, and (ii) at least one parameter derived from one or more of the second plurality of parameters.

17. The non-transitory, computer-readable medium of claim 16, wherein the instructions further cause the computing device to:

prior to processing the values of the monitored first plurality of parameters, select, from among a plurality of gait models, a first gait model corresponding to a current gait type of the user, wherein the mapping between step frequency of the user and step length of the user is specific to the first gait model, and wherein the plurality of gait models includes a running gait model and a walking gait model; and

use values of the mapping between step frequency of the user and step length of the user, as output by the estimator, to update the first gait model.

18. A mobile computing device comprising:

a display screen;

one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the mobile computing device to

monitor a first plurality of parameters indicative of movement of a user of the mobile computing device, wherein the first plurality of parameters includes (i) a first GNSS-derived speed of the user and (ii) a step count of the user,

process values of the monitored first plurality of parameters to determine values of a second plurality of parameters indicative of movement of the user,

wherein processing values of the monitored first plurality of parameters includes

applying, as inputs to an estimator having the second plurality of parameters as estimator states, values of at least one of the monitored first plurality of parameters, and

predicting, at each of a plurality of time intervals, that values of the estimator states are unchanged from respective values of the estimator states at a most recent time interval, and

wherein at least two parameters of the second plurality of parameters are collectively indicative of a mapping between step frequency of the user and step length of the user, and

display, on a graphical user interface presented on the display screen, values of one or both of (i) at least one of the second plurality of parameters, and (ii) at least one parameter derived from one or more of the second plurality of parameters.

19. The mobile computing device of claim 18, further comprising a GNSS unit, wherein:

the first plurality of parameters includes (i) the first GNSS-derived speed of the user, (ii) a second GNSS-derived speed of the user, and (iii) the step count of the user;

the first GNSS-derived speed of the user is a speed determined using GNSS location;

the second GNSS-derived speed of the user is a speed determined using GNSS Doppler shift; and

the instructions cause the mobile computing device to (i) monitor the first GNSS-derived speed of the user at least by monitoring values of the first GNSS-derived speed generated by the GNSS unit; and

(ii) monitor the second GNSS-derived speed of the user at least by monitoring values of the second GNSS-derived speed generated by the GNSS unit.

20. The mobile computing device of claim 18, further comprising a step counter unit, wherein:

the instructions cause the mobile computing device to monitor the step count of the user at least by monitoring values of the step count generated by the step counter unit.