SYSTEM AND METHOD OF DETECTING ABNORMAL MOVEMENT OF A PHYSICAL OBJECT

• US 20160183811A1
• Filed: 03/08/2016
• Published: 06/30/2016
• Est. Priority Date: 12/28/2010
• Status: Abandoned Application

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: TING, Chuan-Wei, WANG, Ching-Yao
• Application Number:
  US15/064,107
• Publication Number:
  US 20160183811A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/4803 Speech analysis specially adapted for diagnostic purposes

Abstract

A method of identifying a predetermined type of abnormal movement of a physical object includes generating a raw matrix comprising a first array and a second array, the generation of the raw matrix. The method also includes generating an integrated matrix by performing a dimension reduction on the raw matrix. The method a further includes identifying the predetermined type of abnormal movement of the physical object by comparing the integrated matrix or a set of indexes derived from the integrated matrix with a predetermined benchmark pattern corresponding to the predetermined type of abnormal movement. Generating the raw matrix includes a first analysis on a predetermined portion of a periodic signal representative of movement of the physical object to generate the first array. Generating the raw matrix also includes performing a second analysis different from the first analysis on the predetermined portion of the periodic signal to generate the second array.

Claims

1. A method of identifying a predetermined type of abnormal movement of a physical object, a periodic signal being representative of movement of the physical object, the method comprising:

generating a raw matrix comprising a first array and a second array, the generation of the raw matrix comprising;

performing a first analysis on a predetermined portion of the periodic signal to generate the first array; and

performing a second analysis different from the first analysis on the predetermined portion of the periodic signal to generate the second array;

generating an integrated matrix by performing a dimension reduction on the raw matrix; and

identifying the predetermined type of abnormal movement of the physical object by comparing the integrated matrix or a set of indexes derived from the integrated matrix with a predetermined benchmark pattern corresponding to the predetermined type of abnormal movement.

2. The method of claim 1, wherein the identification of the predetermined type of abnormal movement comprises determining a likelihood of the predetermined type of abnormal movement.

3. The method of claim 2, further comprising:

outputting the likelihood of the predetermined type of abnormal movement of the physical object to a display.

4. The method of claim 1, wherein the first analysis or the second analysis is a time-domain analysis, a pattern analysis, or deriving a feature from the predetermined duration of the periodic signal obtained according to a first spatial measurement configuration and at least a portion of another periodic signal being representative of the movement obtained according to a second spatial measurement configuration.

5. The method of claim 1, wherein the dimension reduction is performed by applying principal component analysis, factor analysis, or independent component analysis on the raw matrix.

6. The method of claim 1, wherein the periodic signal is obtained by detecting one or more of the following activities:

heartbeat, breathing, speech, earthquake or seismic activity, orbital movement of an astronomical object, periodic variances of an astronomical object, movement of a piston, or rotation of a motor.

7. The method of claim 1, wherein the first analysis is a mutual information analysis, comprising:

segmenting the predetermined portion of the periodic signal into a plurality of signal segments, each signal segment including a nominal waveform, and the plurality of signal segments including one or more pairs of adjacent signal segments;

for each pair of the one or more pairs of adjacent signal segments;

obtaining two signal arrays having the same size by re-sampling one or both of the adjacent signal segments; and

calculating joint probability and marginal probability of the two signal arrays of the re-sampled adjacent signal segments; and

calculating a mutual information index based on the calculated joint probability and the calculated marginal probability of the one or more pairs of re-sampled adjacent signal segments.

8. The method of claim 7, wherein the calculation of the mutual information index is performed based on an equation of:

9. A system comprising:

a computer readable storage medium encoded with a computer program code;

a processor coupled to the computer readable storage medium, the processor being configured to execute the computer program code;

wherein the computer program code is configured to cause the processor to;

perform a first analysis on a predetermined portion of a periodic signal to generate a first array, the periodic signal being representative of movement of a physical object, and the predetermined portion corresponding to a predetermined time period of the periodic signal;

perform a second analysis different from the first analysis on the predetermined portion of the periodic signal to generate the second array;

generate an integrated matrix by performing a dimension reduction on the raw matrix; and

determine a likelihood of a predetermined type of abnormal movement of the physical object by comparing the integrated matrix or a set of indexes derived from the integrated matrix with a predetermined benchmark pattern corresponding to the predetermined type of abnormal movement.

10. The abnormality analysis system of claim 9, wherein the first analysis is a mutual information analysis, and the computer program code is further configured to cause the processor to:

segment the predetermined duration of the periodic signal into a plurality of signal segments, each signal segment including a nominal waveform, and the plurality of signal segments including one or more pairs of adjacent signal segments;

for each pair of the one or more pairs of adjacent signal segments;

obtain two signal arrays having the same size by re-sampling one or both of the re-sampled adjacent signal segments; and

calculate joint probability and marginal probability of the two signal arrays of the adjacent signal segments; and

calculate a mutual information index based on the calculated joint probability and the calculated marginal probability of the one or more pairs of re-sampled adjacent signal segments.

11. The abnormality analysis system of claim 10, wherein the computer program code is further configured to cause the processor to calculate the mutual information index based on an equation of:

12. The abnormality analysis system of claim 9, wherein the identification of the predetermined type of abnormal movement comprises determining a likelihood of the predetermined type of abnormal movement.

13. The abnormality analysis system of claim 12, wherein the computer program code is further configured to cause the processor to:

output the likelihood of the predetermined type of abnormal movement of the physical object to a display.

14. The abnormality analysis system of claim 9, wherein the first analysis or the second analysis is a time-domain analysis, a pattern analysis, or deriving a feature from the predetermined duration of the periodic signal obtained according to a first spatial measurement configuration and at least a portion of another periodic signal being representative of the movement obtained according to a second spatial measurement configuration.

15. The abnormality analysis system of claim 9, wherein the computer program code is further configured to cause the processor to:

perform the dimension reduction by applying principal component analysis, factor analysis, or independent component analysis on the raw matrix.

16. The abnormality analysis system of claim 9, wherein the computer program code is further configured to cause the processor to:

obtain the periodic signal by detecting one or more of the following activities;

heartbeat, breathing, speech, earthquake or seismic activity, orbital movement of an astronomical object, periodic variances of an astronomical object, movement of a piston, or rotation of a motor.

17. A method, comprising:

generating a first array of a raw matrix based on a predetermined portion of a periodic signal representative of a movement of a physical object, wherein generating the first array comprises;

segmenting the predetermined portion of the periodic signal into a plurality of signal segments, each signal segment including a nominal waveform, and the plurality of signal segments including one or more pairs of adjacent signal segments;

obtaining two signal arrays having a same size by re-sampling one or both of the adjacent signal segments for each pair of the one or more pairs of adjacent signal segments;

calculating joint probability and marginal probability of the two signal arrays of the re-sampled adjacent signal segments; and

calculating a mutual information index based on the calculated joint probability and the calculated marginal probability of the one or more pairs of re-sampled adjacent signal segments;

generating a second array of the raw matrix based on the predetermined portion of the periodic signal; and

recognizing the movement of the physical object corresponds to one or more predefined types of abnormal movement based on a comparison of data derived from the raw matrix with a benchmark pattern corresponding to the one or more predefined types of abnormal movement.

18. The method of claim 17, further comprising:

calculating a likelihood of the one or more predefined types of abnormal movements to which the movement of the physical object corresponds.

19. The method of claim 17, further comprising:

outputting the one or more predefined types of abnormal movements to which the movement of the physical object corresponds to a display.

20. The method of claim 17, wherein the periodic signal is obtained by detecting one or more of a heartbeat, breathing, speech, an earthquake, a seismic activity, an orbital movement of an astronomical object, periodic variances of an astronomical object, a movement of a piston, or a rotation of a motor.