Human activity energy consumption measuring method and energy consumption measuring system

• US 10,330,492 B2
• Filed: 11/20/2014
• Issued: 06/25/2019
• Est. Priority Date: 06/25/2014
• Status: Active Grant

• Current Assignee: BOE Technology Group Co., Ltd.
• Original Assignee: BOE Technology Group Co., Ltd.
• Inventors: Wei, Qiang
• Primary Examiner(s): Hur, J. H.
• Application Number:
  US14/443,790
• Publication Number:
  US 20160273938A1
• Time in Patent Office: 1,678 Days
• Field of Search: None
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A63B 24/0075 Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The present invention provides an energy consumption measuring method and an energy consumption measuring system. According to the energy consumption measuring method and energy consumption measuring system provided by the present invention, by processing motion data of a user to acquire a corresponding motion feature vector of the user within a time period and comparing the acquired motion feature vector with a standard motion feature vector in a database, the energy consumption within this time period is acquired.

Claims

1. An energy consumption measuring method, comprising:

acquiring motion data of a user within a time period;

processing, by a motion data processing unit, the acquired motion data to acquire a motion feature vector;

comparing the acquired motion feature vector with a standard motion feature vector in a database so as to judge whether a motion model of the user matches a motion model in the database;

acquiring an energy consumption value according to the data in the database if matching; and

allowing the user to create a customized motion model and input a corresponding energy consumption value if not matching,

wherein the acquiring a motion feature vector comprises;

partitioning, by a data partition subunit of the motion data processing unit, the motion data into m data units in unit of certain time, each data unit contains n data points of each of motion variables, wherein both m and n are natural numbers greater than or equal to two, the motion variables include displacement, velocity and acceleration, and the displacement, the velocity and the acceleration are acquired by an acceleration sensor and an angular velocity sensor;

for the m data units, calculating, by a component calculation subunit of the motion data processing unit, average values, variances and histogram slopes of the n data points of each of the motion variables in x-axis, y-axis and z-axis directions, respectively;

performing, by a discretizing and fitting subunit of the motion data processing unit, Gaussian probability distribution calculation on the average values, variances and histogram slopes of the n data points of each of the motion variables of all the m data units in the x-axis, y-axis and z-axis directions to acquire discrete feature values and position feature values of a corresponding Gaussian distribution curve, and using a calculation result of least square fitting of the position feature values as a feature vector of the corresponding motion variable; and

using, by a motion feature vector generation subunit of the motion data processing unit, a set of the feature vectors of the motion variables as the motion feature vector of the corresponding data unit.

2. The energy consumption measuring method according to claim 1, wherein the motion data is recorded and stored by the acceleration sensor and the angular velocity sensor.

3. The energy consumption measuring method according to claim 1, wherein the motion variables comprise motion elements and user elements, the motion elements comprising the displacement, the velocity and the acceleration, and further height and time, the user elements comprising age, gender, weight, height, vital capacity and body mass index.

4. The energy consumption measuring method according to claim 1, wherein the comparing comprises:

calculating a similarity of the acquired motion feature vector and the standard motion feature vector by a normalized Euclidean distance;

comparing the acquired similarity with a set value; and

indicating matching when the absolute value of the similarity is less than the set value, and indicating not matching when the absolute value of the similarity is greater than or equal to the set value.

5. The energy consumption measuring method according to claim 4, wherein the set value is a discrete feature value of a Gaussian distribution curve of the standard motion feature vector.

6. The energy consumption measuring method according to claim 1, wherein the database comprises a user-customized motion model library and a cloud motion model library,

the cloud motion model library is configured to store a standard motion model and corresponding energy consumption thereof, and

the customized motion model library is configured to store a motion feature vector which is not matched with the cloud motion model library, and store corresponding energy consumption input by the user.

7. An energy consumption measuring system, comprising:

a motion data acquisition unit, configured to acquire motion data of a user within a time period;

a motion data processing unit comprising an acceleration sensor and an angular velocity sensor, and configured to process the acquired motion data to acquire a motion feature vector; and

a comparison unit, configured to compare the acquired motion feature vector with a standard motion feature vector in a database so as to judge whether a motion model of the user matches a motion model in the database, acquire an energy consumption value according to the data in the database if matching, and allow the user to create a customized motion model and input a corresponding energy consumption value if not matching,

wherein the motion data processing unit comprises;

a data partition subunit, configured to partition the motion data into m data units in unit of certain time, each data unit contains n data points of each of motion variables, wherein both m and n are natural numbers greater than or equal to two, the motion variables include displacement, velocity and acceleration, and the displacement, the velocity and the acceleration are acquired by the acceleration sensor and the angular velocity sensor;

a component calculation subunit, configured to, for the m data units, calculate average values, variances and histogram slopes of the n data points of each of the motion variables in x-axis, y-axis and z-axis directions, respectively;

a discretizing and fitting subunit, configured to perform Gaussian probability distribution calculation on the average values, variances and histogram slopes of the n data points of each of the motion variables of all the m data units in the x-axis, y-axis and z-axis directions to acquire discrete feature values and position feature values of a corresponding Gaussian distribution curve, and use a calculation result of least square fitting of the position feature values as a feature vector of the corresponding motion variable; and

a motion feature vector generation subunit, configured to use a set of the feature vectors of the motion variables as the motion feature vector of the corresponding data unit.

8. The energy consumption measuring system according to claim 7, wherein the motion data is recorded and stored by the acceleration sensor and the angular velocity sensor.

9. The energy consumption measuring system according to claim 7, wherein the database comprises a user-customized motion model library and a cloud motion model library;

the cloud motion model library is configured to store a standard motion model and corresponding energy consumption thereof; and

the customized motion model library is configured to store a motion feature vector which is not matched with the cloud motion model library, and store corresponding energy consumption input by the user.

10. The energy consumption measuring system according to claim 9, further comprising a data transceiver unit, configured to request motion model data from the database, and receive or transmit the motion model data.

11. The energy consumption measuring system according to claim 7, further comprising an energy consumption acquisition unit, wherein the energy consumption acquisition unit acquires the corresponding energy consumption according to the standard motion feature vector in the database when the motion model of the user matches the motion model in the database;

and, the energy consumption acquisition unit acquires energy consumption input by the user in the case of not matching.

12. The energy consumption measuring system according to claim 11, further comprising a display unit configured to display the energy consumption acquired by the energy consumption acquisition unit.