Apparatus and method for detecting blood flow signal free from motion artifact and stress test apparatus using the same

• US 20050038349A1
• Filed: 08/03/2004
• Published: 02/17/2005
• Est. Priority Date: 08/11/2003
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Choi, Ki-wan, Lee, Hyoung-ki, Bang, Seok-won
• Granted Patent: US 7,727,159 B2
• Time in Patent Office: Days
• US Class Current: 600/504
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts

Abstract

An apparatus and method to detect a blood flow signal free from a motion artifact, and a stress test apparatus using the same, enhance data reliability of the blood flow signal by removing the motion artifact from the blood flow signal detected by photo-plethysmography. The apparatus to detect the blood flow signal includes a base pattern correlation coefficient calculating unit to determine peak points in the blood flow signal sensed from a body of an examinee using a blood flow sensing unit, and to calculate correlation coefficients of each peak point using a predetermined base pattern, and a motion artifact processing unit to determine the motion artifact using the calculated correlation coefficients and to remove the motion artifact from the blood flow signal. Thus, reliability of the blood flow signal is enhanced by effectively removing the motion artifact from the blood flow signal detected by the photo-plethysmography.

Claims

1. An apparatus to detect a blood flow signal free from a motion artifact, comprising:

a base pattern correlation coefficient calculating unit to determine peak points in the blood flow signal sensed from a body of an examinee, and to calculate correlation coefficients of each peak point using a predetermined base pattern; and

a motion artifact processing unit to determine the motion artifact using the calculated correlation coefficients and to remove the motion artifact from the blood flow signal.

2. The apparatus as claimed in claim 1, wherein the predetermined base pattern is extracted from a predetermined area of the blood flow signal where a pure blood flow signal measured under a test environment free from the motion artifact is determined to be optimal.

3. The apparatus as claimed in claim 1, wherein the correlation coefficients are calculated using the following equation:

$\begin{array}{c}{C}_i=\frac{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)<br><br>\left(b_n-\stackrel{\_}{b}\right)}{\sqrt{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)}^2<br><br>\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(b_n-\stackrel{\_}{b}\right)}^2}}\\ k<br><br>\left(i,n\right)=\frac{\left(N-n\right)<br><br>P_i+n<br><br>\text{\hspace{1em}<br><br>}<br><br>P_{i+1}}{N}\end{array}$

wherein

where x_n is an n^th point of the blood flow signal,

b_n is an n^th point of the base pattern,

k(i,n)) is an n^th point position from the i^th peak,

P_i is a i^th peak point, and

N is the number of the base pattern signal,

i and n being integers.

4. The apparatus as claimed in claim 1, wherein the motion artifact is determined by comparing the calculated correlation coefficients with a predetermined threshold value and determining whether the correlation coefficients are less than the predetermined threshold value.

5. The apparatus as claimed in claim 4, wherein the predetermined threshold value has a range from 0.7 to 0.9.

6. The apparatus as claimed in claim 5, wherein the predetermined threshold value is approximately 0.8.

50. The apparatus as claimed in claim 5, wherein the predetermined threshold value is approximately 0.8.

7. A method to detect a blood flow signal free from a motion artifact, the method comprising:

detecting the blood flow signal sensed from a body of an examinee;

determining peak points in the detected blood flow signal and calculating correlation coefficients of each peak point using a predetermined base pattern; and

determining the motion artifact using the calculated correlation coefficients and removing the motion artifact from the blood flow signal.

8. The method as claimed in claim 7, wherein the predetermined base pattern is extracted from a predetermined area of the blood flow signal where a pure blood flow signal measured under a test environment free from the motion artifact is determined to be optimal.

9. The method as claimed in claim 7, wherein the correlation coefficients are calculated using the following equation:

$\begin{array}{c}{C}_i=\frac{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)<br><br>\left(b_n-\stackrel{\_}{b}\right)}{\sqrt{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)}^2<br><br>\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(b_n-\stackrel{\_}{b}\right)}^2}},\\ k<br><br>\left(i,n\right)=\frac{\left(N-n\right)<br><br>P_i+n<br><br>\text{\hspace{1em}<br><br>}<br><br>P_{i+1}}{N}\end{array}$

wherein

where x_n, is an n^th point of the blood flow signal,

b_n, is an n^th point of the base pattern,

k(i,n)) is an n^th point position from the i^th peak,

P_i is a i^th peak point, and

N is the number of the base pattern signal,

i and n being integers.

10. The method as claimed in claim 7, wherein the determining the motion artifact using the calculated correlation coefficients compares the calculated correlation coefficients with a predetermined threshold value and determines whether the correlation coefficients are less than the predetermined threshold value.

11. The method as claimed in claim 10, wherein the predetermined threshold value has a range from 0.7 to 0.9.

12. The method as claimed in claim 11, wherein the predetermined threshold value is approximately 0.8.

13. A stress test apparatus using an apparatus to detect a blood flow signal free from a motion artifact, comprising:

a motion artifact removing section to remove the motion artifact caused by an examinee from the blood flow signal detected from a body of the examinee;

a heartbeat information calculating section to calculate heartbeat information using the blood flow signal from which the motion artifact is removed utilizing the motion artifact removing section; and

a stress testing section to calculate a stress index using the heartbeat information calculated utilizing the heartbeat information calculating section and checking a physical state of the examinee.

14. The stress test apparatus as claimed in claim 13, further comprising:

a display section to provide information on the physical state of the examinee obtained utilizing the stress testing section on a graphic user interface (GUI) screen; and

a storage section to store information on the physical state of the examinee and information on a suitable prescription according to the physical state of the examinee.

15. The stress test apparatus as claimed in claim 13, wherein the motion artifact removing section comprises:

a base pattern correlation coefficient calculating part to determine peak points in the blood flow signal sensed from the physical state of the examinee using the blood flow sensing unit, and to calculate correlation coefficients of each peak point using a predetermined base pattern; and

a motion artifact processing part to determine the motion artifact using the calculated correlation coefficients and to remove the motion artifact from the blood flow signal.

16. The stress test apparatus as claimed in claim 15, wherein the predetermined base pattern is extracted from a predetermined area of the blood flow signal where a pure blood flow signal measured under a test environment free from the motion artifact is determined to be optimal.

17. The stress test apparatus as claimed in claim 15, wherein the correlation coefficients are calculated using the following equation:

$\begin{array}{c}{C}_i=\frac{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)<br><br>\left(b_n-\stackrel{\_}{b}\right)}{\sqrt{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)}^2<br><br>\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(b_n-\stackrel{\_}{b}\right)}^2}},\\ k<br><br>\left(i,n\right)=\frac{\left(N-n\right)<br><br>P_i+n<br><br>\text{\hspace{1em}<br><br>}<br><br>P_{i+1}}{N}\end{array}$

wherein

where x_n, is an n^th point of the blood flow signal,

b_n, is an n^th point of the base pattern,

k(i,n)) is an n^th point position from the i^th peak,

P_i is a i^th peak point, and

N is the number of the base pattern signal,

i and n being integers.

18. The stress test apparatus as claimed in claim 15, wherein the determining the motion artifact using the calculated correlation coefficients compares the calculated correlation coefficients with a predetermined threshold value and determines whether the correlation coefficients are less than the predetermined threshold value.

19. The stress test apparatus as claimed in claim 18, wherein the predetermined threshold value has a range from 0.7 to 0.9.

20. The stress test apparatus as claimed in claim 19, wherein the predetermined threshold value is approximately 0.8.

21. The stress test apparatus as claimed in claim 13, wherein the heartbeat information calculating section comprises:

a heart rate calculating part to calculate a heart rate using an interval between the peak points which are determined to be the blood flow signal utilizing the motion artifact removing section, and to determine the motion artifact by comparing the interval between the peak points with a reference range and comparing the heart rate with the reference range; and

a heart rate variability generating part to cause removal of the motion artifact utilizing the motion artifact removing section and the heart rate calculating part that determines the heart rate at peak points of the blood flow signal, and to generate heart rate variability by collecting each peak point which is determined to be the blood flow signal.

22. The stress test apparatus as claimed in claim 13, wherein the stress index is determined by analyzing information on sympathetic and parasympathetic nerves, the information on sympathetic and parasympathetic nerves being obtained by analyzing the calculated heartbeat information using frequency and time domains.

23. A computer medium having computer-readable instructions stored thereon to detect a blood flow signal free from a motion artifact, the computer-readable instructions comprising:

using base pattern correlation coefficient calculating instructions to determine peak points in the blood flow signal sensed from a body of an examinee, and to calculate correlation coefficients of each peak point using a predetermined base pattern; and

using motion artifact processing and the calculated correlation coefficients to determine the motion artifact and to remove the motion artifact from the blood flow signal.

24. The computer medium as claimed in claim 23, wherein the predetermined base pattern is extracted from a predetermined area of blood flow signal where a pure blood flow signal measured under a test environment free from the motion artifact is determined to be optimal.

25. The computer medium as claimed in claim 23, wherein the correlation coefficients are calculated using the following equation:

$\begin{array}{c}{C}_i=\frac{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)<br><br>\left(b_n-\stackrel{\_}{b}\right)}{\sqrt{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)}^2<br><br>\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(b_n-\stackrel{\_}{b}\right)}^2}},\\ k<br><br>\left(i,n\right)=\frac{\left(N-n\right)<br><br>P_i+n<br><br>\text{\hspace{1em}<br><br>}<br><br>P_{i+1}}{N}\end{array}$

wherein

where x_n is an n^th point of the blood flow signal,

b_n, is an n^th point of the base pattern,

k(i,n)) is an n^th point position from the i^th peak,

P_i is a i^th peak point, and

N is the number of the base pattern signal,

i and n being integers.

26. The computer medium as claimed in claim 23, wherein the motion artifact is determined by comparing the calculated correlation coefficients with a predetermined threshold value and determining whether the correlation coefficients are less than the predetermined threshold value.

27. The computer medium as claimed in claim 26, wherein the predetermined threshold value has a range from 0.7 to 0.9.

28. The computer medium as claimed in claim 27, wherein the predetermined threshold value is approximately 0.8.

29. A computer medium having computer-readable instructions stored thereon to detect a blood flow signal free from a motion artifact, the computer-readable instructions performing:

detecting the blood flow signal sensed from a body of an examinee;

determining peak points in the detected blood flow signal and calculating correlation coefficients of each peak point using a predetermined base pattern; and

determining the motion artifact using the calculated correlation coefficients and removing the motion artifact from the blood flow signal.

30. The computer medium as claimed in claim 29, wherein the predetermined base pattern is extracted from a predetermined area of the blood flow signal where a pure blood flow signal measured under a test environment free from the motion artifact is determined to be optimal.

31. The computer medium as claimed in claim 29, wherein the correlation coefficients are calculated using the following equation:

$\begin{array}{c}{C}_i=\frac{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)<br><br>\left(b_n-\stackrel{\_}{b}\right)}{\sqrt{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)}^2<br><br>\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(b_n-\stackrel{\_}{b}\right)}^2}},\\ k<br><br>\left(i,n\right)=\frac{\left(N-n\right)<br><br>P_i+n<br><br>\text{\hspace{1em}<br><br>}<br><br>P_{i+1}}{N}\end{array}$

wherein

where x_n is an n^th point of the blood flow signal,

b_n, is an n^th point of the base pattern,

k(i,n)) is an n^th point position from the i^th peak,

P_i is a i^th peak point, and

N is the number of the base pattern signa,

i and n being integers.

32. The computer medium as claimed in claim 29, wherein the determining the motion artifact using the calculated correlation coefficients compares the calculated correlation coefficients with a predetermined threshold value and determines whether the correlation coefficients are less than the predetermined threshold value.

33. The computer medium as claimed in claim 32, wherein the predetermined threshold value has a range from 0.7 to 0.9.

34. The computer medium as claimed in claim 33, wherein the predetermined threshold value is approximately 0.8.

35. A computer medium having computer-readable instructions stored thereon to detect a blood flow signal free from a motion artifact, the computer-readable instructions comprising:

removing the motion artifact caused by an examinee from the blood flow signal detected from a body of the examinee;

calculating heartbeat information using the blood flow signal from which the motion artifact is removed; and

calculating a stress index using the heartbeat information and information on a physical state of the examinee.

36. The computer medium as claimed in claim 35, further comprising:

providing information on the physical state of the examinee on a graphic user interface (GUI) screen; and

storing information on the physical state of the examinee and information on a suitable prescription according to the physical state of the examinee.

37. The computer medium as claimed in claim 35, including:

calculating a base pattern correlation coefficient to determine peak points in the blood flow signal sensed from the physical state of the examinee, and calculating correlation coefficients of each peak point using a predetermined base pattern; and

using motion artifact processing to determine the motion artifact using the calculated correlation coefficients and removing the motion artifact from the blood flow signal.

38. The computer medium as claimed in claim 37, wherein the predetermined base pattern is extracted from a predetermined area of the blood flow signal where a pure blood flow signal measured under a test environment free from the motion artifact is determined to be optimal.

39. The computer medium as claimed in claim 37, wherein the correlation coefficients are calculated using the following equation:

$\begin{array}{c}{C}_i=\frac{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)<br><br>\left(b_n-\stackrel{\_}{b}\right)}{\sqrt{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)}^2<br><br>\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(b_n-\stackrel{\_}{b}\right)}^2}},\\ k<br><br>\left(i,n\right)=\frac{\left(N-n\right)<br><br>P_i+n<br><br>\text{\hspace{1em}<br><br>}<br><br>P_{i+1}}{N}\end{array}$

wherein

where x_n is an n^th point of the blood flow signal,

b_n, is an n^th point of the base pattern,

k(i,n)) is an n^th point position from the i^th peak,

P_i is a i^th peak point, and

N is the number of the base pattern signal,

i and n being integers.

40. The computer medium as claimed in claim 37, wherein the determining the motion artifact using the calculated correlation coefficients compares the calculated correlation coefficients with a predetermined threshold value and determines whether the correlation coefficients are less than the predetermined threshold value.

41. The computer medium as claimed in claim 40, wherein the predetermined threshold value has a range from 0.7 to 0.9.

42. The computer medium as claimed in claim 41, wherein the predetermined threshold value is approximately 0.8.

43. The computer medium as claimed in claim 35, wherein the calculating the heartbeat information comprises:

calculating a heart rate using an interval between the peak points which are determined to be the blood flow signal, and determining the motion artifact by comparing the interval between the peak points with a reference range and comparing the heart rate with the reference range; and

removing the motion artifact using the heart rate calculated at peak points of the blood flow signal, and generating a heart rate variability by collecting each peak point which is determined to be the blood flow signal.

44. The computer medium as claimed in claim 35, wherein the stress index is determined by analyzing information on sympathetic and parasympathetic nerves, the information on sympathetic and parasympathetic nerves being obtained by analyzing the calculated heartbeat information using frequency and time domains.

45. An apparatus to remove a motion artifact from a filtered blood flow signal, wherein the filtered blood flow signal has been filtered to obtain waveforms of a predetermined frequency band, the apparatus comprising:

a base pattern correlation coefficient calculating unit to determine peak points in the waveforms of the predetermined frequency band, and to calculate correlation coefficients of each peak point using a predetermined base pattern; and

a motion artifact processing unit to determine the motion artifact using the calculated correlation coefficients and to remove the motion artifact from the blood flow signal.

46. The apparatus as claimed in claim 45, wherein the predetermined base pattern is extracted from a predetermined area of the blood flow signal where a pure blood flow signal measured under a test environment free from the motion artifact is determined to be optimal.

47. The apparatus as claimed in claim 45, wherein the correlation coefficients are calculated using the following equation:

$\begin{array}{c}{C}_i=\frac{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)<br><br>\left(b_n-\stackrel{\_}{b}\right)}{\sqrt{\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(x_{k<br><br>\left(i,n\right)}-\stackrel{\_}{x}\right)}^2<br><br>\underset{n=0}{\overset{N}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>{\left(b_n-\stackrel{\_}{b}\right)}^2}},\\ k<br><br>\left(i,n\right)=\frac{\left(N-n\right)<br><br>P_i+n<br><br>\text{\hspace{1em}<br><br>}<br><br>P_{i+1}}{N}\end{array}$

wherein

where x_n, is an n^th point of the blood flow signal,

b_n, is an n^th point of the base pattern,

k(i,n)) is an n^th point position from the i^th peak,

P_i is a i^th peak point, and

N is the number of the base pattern signal,

i and n being integers.

48. The apparatus as claimed in claim 45, wherein the motion artifact is determined by comparing the calculated correlation coefficients with a predetermined threshold value and determining whether the correlation coefficients are less than the predetermined threshold value.

49. The apparatus as claimed in claim 48, wherein the predetermined threshold value has a range from 0.7 to 0.9.