Method for improving recognition rate of respiratory wave

• US 20070135726A1
• Filed: 11/29/2006
• Published: 06/14/2007
• Est. Priority Date: 12/08/2005
• Status: Active Grant

• Current Assignee: Shenzhen Mindray Bio-Medical Electronics Co., Ltd. (Excelsior Union Ltd.)
• Original Assignee: Shenzhen Mindray Bio-Medical Electronics Co., Ltd. (Excelsior Union Ltd.)
• Inventors: Ye, Jilun, Deng, Yun, Yang, Yulin
• Granted Patent: US 8,152,733 B2
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 5/0809 by impedance pneumography

Abstract

The present invention discloses a method for improving recognition rate of respiratory wave, which is used for a data processing module of a respiratory rate measuring or monitoring device, specifically, said method comprises the steps of: receiving, via a data processing module, respiratory wave data which come from a measuring circuit and have been analog-to-digital converted; according to the feature that each crest or trough signal in the respiratory wave data has rising stairs and falling stairs, sequentially searching for and finding out, based on a predetermined number of stairs, the data corresponding to each crest and trough via said data processing module; and determining each crest and trough in a corresponding respiratory wave. According to the present invention, interferences may be effectively eliminated and recognition rate of respiratory waveform may be effectively improved, so that the computation of respiratory rate will be more accurate and stable, and the measuring or monitoring device will have a higher clinical practicability.

Claims

1. A method for improving recognition rate of respiratory wave, which is used for a data processing module of a respiratory rate measuring or monitoring device, said method comprising the steps of:

A. receiving, via a data processing module, respiratory wave data which come from a measuring circuit and have been analog-to-digital converted;

C. determining each crest and trough in a corresponding respiratory wave;

wherein between said step of A and said step of C is the step of;

B. according to the feature that each crest or trough signal in the respiratory wave data has rising stairs and falling stairs, sequentially searching for and finding out, based on a predetermined number of stairs, the data corresponding to each crest and trough via said data processing module.

2. The method for improving recognition rate of respiratory wave according to claim 1, wherein a searching process of said step of B comprises the steps of:

a. comparing said respiratory wave data with data received before so as to determine whether the corresponding waveform is rising or falling;

b. recording the positions of the maximum or minimum values of the rising or falling in the searched data, when said rising or falling reaches its predetermined extent;

c. judging whether the overall tendency of the current data in the waveform is falling or rising so as to determine whether to recognize retroactively the recorded extremal position as the previous crest or trough; and

d. taking the next respiratory wave data and returning to the step of a until the searching process completes.

3. The method for improving recognition rate of respiratory wave according to claim 1, wherein

count parameters are provided in said step of B for judging the rising or falling tendency of the waveform, said count parameters including a rising count, a maximum rising count, a falling count and a maximum falling count;

said count parameters are first initialized to 0 in said step of B; and

in the step of a, when the current data is larger than the previous data, if said rising count is less than twice of said predetermined number of stairs, then said rising count is increased by 1;

if said falling count is larger than 0, then said falling count is decreased by 1; and

if said maximum rising count is less than said rising count, then it will be set as the value of said rising count;

when the current data is less than the previous data, if said falling count is less than twice of said predetermined number of stairs, then said falling count is increased by 1;

if said rising count is larger than 0, then said rising count is decreased by 1; and

if said maximum falling count is less than said falling count, then it will be set as the value of said falling count; and

in the step of c, when the values of said rising count and falling count are both equal to said predetermined number of stairs, the recorded extremal position will be recognized as the previous crest when the value of said maximum rising count is twice of said predetermined number of stairs, and said maximum rising count will be set as 0; and

the recorded extremal position will be recognized as the previous trough when the value of said maximum falling count is twice of said predetermined number of stairs, and said maximum falling count will be set as 0; and

in the step of b, if the current data is larger than the previous data, i.e., rising, then said predetermined extent will be set as said rising count and maximum rising count being equal to twice of said predetermined number of stairs;

if the current data is less than the previous data, i.e., falling, then said predetermined extent will be set as said falling count and maximum falling count being equal to twice of said predetermined number of stairs.

4. The method for improving recognition rate of respiratory wave according to claim 2, wherein

count parameters are provided in said step of B for judging the rising or falling tendency of the waveform, said count parameters including a rising count, a maximum rising count, a falling count and a maximum falling count;

said count parameters are first initialized to 0 in said step of B; and

in the step of a, when the current data is larger than the previous data, if said rising count is less than twice of said predetermined number of stairs, then said rising count is increased by 1;

if said falling count is larger than 0, then said falling count is decreased by 1; and

if said maximum rising count is less than said rising count, then it will be set as the value of said rising count;

when the current data is less than the previous data, if said falling count is less than twice of said predetermined number of stairs, then said falling count is increased by 1;

if said rising count is larger than 0, then said rising count is decreased by 1; and

if said maximum falling count is less than said falling count, then it will be set as the value of said falling count; and

in the step of c, when the values of said rising count and falling count are both equal to said predetermined number of stairs, the recorded extremal position will be recognized as the previous crest when the value of said maximum rising count is twice of said predetermined number of stairs, and said maximum rising count will be set as 0; and

the recorded extremal position will be recognized as the previous trough when the value of said maximum falling count is twice of said predetermined number of stairs, and said maximum falling count will be set as 0; and

in the step of b, if the current data is larger than the previous data, i.e., rising, then said predetermined extent will be set as said rising count and maximum rising count being equal to twice of said predetermined number of stairs;

if the current data is less than the previous data, i.e., falling, then said predetermined extent will be set as said falling count and maximum falling count being equal to twice of said predetermined number of stairs.

5. The method for improving recognition rate of respiratory wave according to claim 1, wherein said step of C comprises:

judging whether the amplitude or frequency variation of the waveform extends beyond a predetermined range according to the data corresponding to each of the currently searched crests and troughs;

when it extends beyond the predetermined range, a heartbeat filtering processing is started in said step of A.

6. The method for improving recognition rate of respiratory wave according to claim 5,

wherein said heartbeat filtering is realized via a

$\mathrm{FIR}$

 

⁢

filter⁢

 

⁢

y⁡

(n)=1L⁢

∑

k=0L-1⁢

x⁡

(n-k),

where x(n) is the measured respiratory wave data, y(n) is the result obtained after the heartbeat filtering of said data, and L is approximately the number of sampling points of the respiration in a heartbeat cycle.

7. The method for improving recognition rate of respiratory wave according to claim 5, wherein said step of A further comprises a gain compensation processing for performing a gain compensation on the data obtained after said heartbeat filtering processing.

8. The method for improving recognition rate of respiratory wave according to claim 7, wherein in said gain compensation processing, a corresponding gain compensation coefficient is obtained by looking up in a pre-established attenuation coefficient table.

9. The method for improving recognition rate of respiratory wave according to claim 1, wherein said step of C further comprises:

judging whether the amplitude or cycle variation of waveform is within a predetermined range according to the data corresponding to each of the currently searched crests and troughs;

if the variations of the amplitude and cycle of waveform are within the predetermined range in a predetermined time period, then an amplification coefficient of the received data will be increased in said step of A or before said step of A; and

if the variations of the amplitude and cycle of waveform are not within the predetermined range in a predetermined time period, then said amplification coefficient will be decreased.

10. The method for improving recognition rate of respiratory wave according to claim 1, wherein said step of C further comprises the steps of judging true or false of each of said crests and troughs by using a self-adaptive threshold method, comprising:

i. obtaining a series of threshold parameters by sensitivity settings, said threshold parameters including parameters for judging true or false of respiratory crests and troughs;

ii. dividing each of the respiratory crests or troughs recognized in said step of B into various types by using said threshold parameters; and

iii. determining and selecting real crests and troughs.

11. The method for improving recognition rate of respiratory wave according to claim 5, wherein said step of C further comprises the steps of judging true or false of each of said crests and troughs by using a self-adaptive threshold method, comprising:

i. obtaining a series of threshold parameters by sensitivity settings, said threshold parameters including parameters for judging true or false of respiratory crests and troughs;

ii. dividing each of the respiratory crests or troughs recognized in said step of B into various types by using said threshold parameters; and

iii. determining and selecting real crests and troughs.

12. The method for improving recognition rate of respiratory wave according to claim 9, wherein said step of C further comprises the steps of judging true or false of each of said crests and troughs by using a self-adaptive threshold method, comprising:

i. obtaining a series of threshold parameters by sensitivity settings, said threshold parameters including parameters for judging true or false of respiratory crests and troughs;

ii. dividing each of the respiratory crests or troughs recognized in said step of B into various types by using said threshold parameters; and

iii. determining and selecting real crests and troughs.

13. The method for improving recognition rate of respiratory wave according to claim 10, wherein the types of said respiratory crests or troughs include real crest, real trough, false crest or false trough;

wherein, for a real crest and a real trough, both necessary conditions and either of half sufficient conditions must be met; and

for a false crest and a false trough, the necessary conditions cannot be met or any of the half sufficient conditions cannot be met.

14. The method for improving recognition rate of respiratory wave according to claim 13, wherein

said necessary conditions include that the amplitude of said crest or trough must reach a predetermined threshold and the respiration cycle must be within a predetermined range;

and

said half sufficient conditions include two kinds of predetermined thresholds selected from the thresholds of amplitude, time and area.

15. The method for improving recognition rate of respiratory wave according to claim 10, wherein the true and false of said respiratory crest or trough types can be converted therebetween, which comprises:

reverting the wrongly recognized real crest or real trough to the false crest or false trough;

or reverting the originally recognized false crest or false trough to the real crest or real trough which is miss-recognized.

16. The method for improving recognition rate of respiratory wave according to claim 11, wherein the true and false of said respiratory crest or trough types can be converted therebetween, which comprises:

reverting the wrongly recognized real crest or real trough to the false crest or false trough;

or reverting the originally recognized false crest or false trough to the real crest or real trough which is miss-recognized.

17. The method for improving recognition rate of respiratory wave according to claim 12, wherein the true and false of said respiratory crest or trough types can be converted therebetween, which comprises:

reverting the wrongly recognized real crest or real trough to the false crest or false trough;

or reverting the originally recognized false crest or false trough to the real crest or real trough which is miss-recognized.

18. The method for improving recognition rate of respiratory wave according to claim 13, wherein the true and false of said respiratory crest or trough types can be converted therebetween, which comprises:

reverting the wrongly recognized real crest or real trough to the false crest or false trough;

or reverting the originally recognized false crest or false trough to the real crest or real trough which is miss-recognized.