SYSTEM AND METHOD OF DETECTING ABNORMAL MOVEMENT OF A PHYSICAL OBJECT

• US 20130345579A1
• Filed: 08/28/2013
• Published: 12/26/2013
• Est. Priority Date: 12/28/2010
• Status: Active Grant

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: TING, Chuan-Wei, WANG, Ching-Yao
• Granted Patent: US 9,314,177 B2
• Time in Patent Office: Days
• US Class Current: 600/509
• 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

The present application discloses a method of detecting abnormal movement of a physical object. A periodic signal is representative of the movement of the object. According to some embodiments, a raw matrix having a first array and a second array is generated, and then an integrated matrix is generated by performing a dimension reduction on the raw matrix. A likelihood of a predetermined type of abnormal movement of the physical object is determined by comparing the integrated matrix with a predetermined benchmark pattern. In some embodiments, the generation of the raw matrix includes 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.

Claims

1. A method of detecting 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, the predetermined portion corresponding to a predetermined time period of the periodic signal; 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

determining 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.

2. 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.

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

segmenting 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;

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 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 adjacent signal segments.

4. The method of claim 3, wherein the calculation of the mutual information index is performed based on an equation of:

5. The method of claim 1, wherein the periodic signal is output of an electrocardiography (ECG) transducer.

6. The method of claim 5, wherein the first analysis or the second analysis is a time-domain analysis, a morphology analysis, or an electric-axis analysis.

7. The method of claim 5, wherein the predetermined type of abnormal movement corresponds to a predetermined illness.

8. 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.

9. The method of claim 1, wherein the raw matrix further comprising a third array, and the generation of the raw matrix further comprising performing a third analysis different from the first analysis and the second analysis on the predetermined portion of the periodic signal to generate the third array.

10. 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.

11. 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.

12. The method of claim 11, wherein the identification of the predetermined type of abnormal movement comprising determining a likelihood of the predetermined type of abnormal movement.

13. The method of claim 11, 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.

14. The method of claim 11, wherein the dimension reduction is performed by applying principal component analysis, factor analysis, or independent component analysis on the raw matrix.

15. The method of claim 11, 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.

16. The method of claim 11, 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 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 adjacent signal segments.

17. The method of claim 16, wherein the calculation of the mutual information index is performed based on an equation of:

18. 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.

19. The abnormality analysis system of claim 18, 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 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 adjacent signal segments.

20. The abnormality analysis system of claim 19, wherein the computer program code is further configured to cause the processor to calculate the mutual information index based on an equation of: