Information processing system and method

• US 9,486,161 B2
• Filed: 06/07/2011
• Issued: 11/08/2016
• Est. Priority Date: 06/07/2011
• Status: Active Grant

• Current Assignee: Happiness Planet Limited
• Original Assignee: Hitachi, Ltd.
• Inventors: Ara, Koji, Akitomi, Tomoaki, Yano, Kazuo
• Primary Examiner(s): DO, AN H
• Application Number:
  US14/124,067
• Publication Number:
  US 20140379292A1
• Time in Patent Office: 1,981 Days
• Field of Search: 702/127, 702/141, 702/142, 702/149
• US Class Current: 1/1
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Abstract

An information processing system includes a sensor node and a server. The sensor node obtains acceleration data and transmits the data to the server. The server obtains and records the number of zero crossings from the acceleration data. The server obtains and records the frequency distribution of the number of zero crossings. The server obtains one or more of the following: the slope of the approximate line of the distribution; the linearity of the distribution; the inflection point; the slope of the approximate line in the zero crossing range below the inflection point; the slope of the approximate line in the zero crossing range above the inflection point; the linearity of the distribution in the zero crossing range below the inflection point; and the linearity of the distribution in the zero crossing range above the inflection point. Then, the server records the obtained value.

Claims

1. An information processing system comprising:

a sensor for measuring a human acceleration produced by human movement for a predetermined time period;

a processing part for obtaining feature data related to a speed of human movement based on the measured acceleration data; and

a storage part for storing the obtained feature data,

wherein the processing part is configured to;

obtain the speed of movement per predetermined unit time from the acceleration data measured by the sensor;

count the speed of movement above a reference value, from the obtained speed of movement per unit time, with respect to each of a plurality of reference values of the speed of movement, as a cumulative frequency for the reference value of the speed of movement; and

obtain statistical data based on the distribution between the reference values of the speed of movement, and the log of the cumulative frequency for the reference values, as the feature data of human movement, and storing the feature data in the storage part,

wherein the speed of movement is a zero crossing number indicating the number of times the acceleration data is zero or crosses zero,

wherein the processing part is configured to;

obtain the number of zero crossings per predetermined unit time, as the speed of movement, from the acceleration data measured by the sensor;

count the number of zero crossings above a reference value, from the number of zero crossings obtained per unit time, with respect to each of a plurality of reference values of the zero crossing number, as a cumulative frequency for the reference value of the zero crossing number;

obtain statistical data based on the reference value of the zero crossing number and on the log of the cumulative frequency for the reference value, as feature data of human behavior; and

store the obtained feature data in the storage part.

2. An information processing system according to claim 1,

wherein the processing part obtains an index indicating the slope or linearity of one approximate line or a plurality of approximate lines, as the feature data.

3. An information processing system according to claim 1,

wherein the processing part obtains feature data including one or more of the following:

first feature data which is an inflection point at which the distribution between the reference value of the zero crossing number, and the log of the cumulative frequency for the reference value is approximated by a curve or a plurality of straight lines;

second feature data which is the slope of a first approximate line in the zero crossing range below the inflection point;

third feature data which is the slope of a second approximate line in the zero crossing range above the inflection point; and

fourth feature data which is an index indicating the linearity of the distribution in the zero crossing range below the inflection point,

wherein the processing part stores the obtained feature data in the storage part.

4. An information processing system according to claim 3,

wherein the feature data includes all of the first to fourth feature data.

5. An information processing system according to claim 3,

wherein the feature data further includes one or more of the following:

the slope of the approximate line of the entire distribution;

the linearity of the entire distribution; and

the linearity of the distribution in the zero crossing range above the inflection point.

6. An information processing system according to claim 3 comprising a plurality of sensors,

wherein the plurality of sensors measure the acceleration of each person to be measured,

wherein the processing part is configured to:

obtain the first to fourth feature data for each person to be measured;

input the previously indexed stress value of the person to be measured;

obtain each weight coefficient so that the sum of the error between the estimated stress value obtained based on the obtained first to fourth feature data and on the weight coefficients of each of the first to fourth feature data, and the input stress value is reduced, with respect to each person to be measured; and

store the obtained weight coefficient in the storage part.

7. An information processing system according to claim 6,

wherein the processing part obtains the estimated stress value based on the obtained first to fourth feature data and on the weight coefficients for each of the first to fourth feature data, and stores the estimated stress value in the storage part.

8. An information processing system according to claim 1,

wherein the processing part obtains feature data including one or more of the following:

the average of the number of zero crossings;

the slope of a third approximate line in the zero crossing range below the average of the number of zero crossings;

the slope of a fourth approximate line in the zero crossing range above the average of the number of zero crossings;

the difference between the slope of the third approximate line and the slope of the fourth approximate line; and

the slope of the approximate line of the entire distribution.

9. An information processing system according to claim 1,

wherein the processing part outputs the obtained feature data to a display device.

10. An information processing system according to claim 1, comprising:

a sensor node including the sensor and a transmission part for transmitting measured acceleration data; and

a server including a receiving part for receiving the acceleration data from the sensor node, the processing part, and the storage part.

11. An information processing system according to claim 1 comprising a sensor node including the sensor, the processing part, and the storage part.

12. An information processing system comprising:

a sensor for measuring a human acceleration produced by human movement for a predetermined time period;

a processing part for obtaining feature data of a speed of human movement based on the measured acceleration data; and

a storage part for storing the obtained feature data,

wherein the processing part is configured to;

obtain the speed of movement per predetermined unit time from the acceleration data measured by the sensor;

determine active or inactive state in each time period, based on whether the speed of movement per unit time exceeds a predetermined threshold;

obtain the duration of the active state and/or the duration of the inactive state in a chronological order;

count the duration above a reference value, from the obtained duration of the active state and/or the obtained duration of the inactive state, with respect to each of a plurality of reference values of the duration, as a cumulative frequency for the reference value of the duration;

obtaining statistical data based on the distribution between the reference value of the duration and on the log of the cumulative frequency for the reference value, as the feature data of human behavior; and

store the obtained feature data in the storage part,

wherein the processing part obtains feature data including one or more of the following;

first feature data which is the inflection point at which the distribution between the reference value of the duration, and the log of the cumulative frequency for the reference value, is approximated by a curve or a plurality of straight lines;

second feature data which is slope a first approximate line in the duration range below the inflection point;

third feature data which is the slope of a second approximate line in the duration range above the inflection point;

fourth feature data which is an index indicating the linearity of the distribution in the duration range below the inflection point;

fifth feature data which is the average of the duration;

sixth feature data which is the slope of a third approximate line in the duration range below the average of the duration; and

seventh feature data which is the slope of a fourth approximate line in the duration range above the average of the duration,

wherein the processing part stores the obtained feature data in the storage part.

13. An information processing system according to claim 12,

wherein the speed of movement is the zero crossing number indicating the number of times the acceleration data is zero or crosses zero.

14. An information processing system according to claim 12,

wherein the processing part obtains an index indicating the slope or linearity of one approximate line or a plurality of approximate lines for the distribution, as the feature data.

15. An information processing system according to claim 12,

wherein the feature data further includes one or more of the following:

the difference between the slope of the third approximate line and the slope of the fourth approximate line; and

the index indicating the linearity of the entire distribution.

16. An information processing method comprising:

obtaining, by a processing part, a speed of movement per predetermined unit time, from acceleration data measured by a sensor for measuring a human acceleration produced by a human movement for a predetermined time period;

counting, by the processing part, the speed of movement above a reference value, from the obtained speed of movement per unit time, with respect to each of a plurality of reference values of the speed of movement, as a cumulative frequency for the reference value of the speed of movement;

obtaining, by the processing part, statistical data based on the distribution between the reference value of the speed of movement and the log of the cumulative frequency for the reference value, as feature data of human behavior, and storing the obtained feature data in a storage unit,

wherein the speed of movement is a zero crossing number indicating the number of times the acceleration data is zero or crosses zero,

wherein the method further comprising;

obtaining, by the processing part, the number of zero crossings per predetermined unit time, as the speed of movement, from the acceleration data measured by the sensor;

counting, by the processing part, the number of zero crossings above a reference value, from the number of zero crossings obtained per unit time, with respect to each of a plurality of reference values of the zero crossing number, as a cumulative frequency for the reference value of the zero crossing number;

obtaining, by the processing part, statistical data based on the reference value of the zero crossing number and on the log of the cumulative frequency for the reference value, as the feature data of human behavior; and

storing, by the processing part, the obtained feature data in the storage unit.

17. An information processing method comprising:

obtaining, by a processing unit, a speed of movement per predetermined unit time, from acceleration data measured by a sensor for measuring a human acceleration produced by human movement for a predetermined time period;

determining, by the processing part, active or inactive state in a particular time, based on whether the speed of movement per unit time exceeds a predetermined threshold;

obtaining, by the processing part, the duration of the active state and/or the duration of the inactive state in a chronological order;

counting, by the processing part, the duration above a reference value, from the obtained duration of the active state and/or the obtained duration of the inactive state, with respect to each of a plurality of reference values of the duration, as a cumulative frequency for the reference value of the duration; and

obtaining, by the processing part, statistical data based on the distribution between the reference value of the duration and the log of the cumulative frequency for the reference value, as feature data of human behavior, and storing the obtained feature data in a storage unit,

wherein the speed of movement is a zero crossing number indicating the number of times the acceleration data is zero or crosses zero,

wherein the method further comprises;

obtaining, by the processing part, the number of zero crossings per predetermined unit time, as the speed of movement, from the acceleration data measured by the sensor;

counting, by the processing part, the number of zero crossings above a reference value, from the number of zero crossings obtained per unit time, with respect to each of a plurality of reference values of the zero crossing number, as a cumulative frequency for the reference value of the zero crossing number;

obtaining, by the processing part, statistical data based on the reference value of the zero crossing number and on the log of the cumulative frequency for the reference value, as the feature data of human behavior; and

storing, by the processing part, the obtained feature data in the storage unit.