Apparatus and method for removing noise from biosignals

• US 9,241,671 B2
• Filed: 02/26/2013
• Issued: 01/26/2016
• Est. Priority Date: 03/13/2012
• Status: Active Grant

• Current Assignee: Industry Academic Cooperation Foundation
• Original Assignee: Industry Academic Cooperation Foundation
• Inventors: Hwang, Do-Sik, Jang, Ung, Kim, Ji-han
• Primary Examiner(s): Flory, Christopher A
• Application Number:
  US13/777,433
• Publication Number:
  US 20130245479A1
• Time in Patent Office: 1,064 Days
• Field of Search: 600/509, 600/517, 600/321, 600/521
• US Class Current: 1/1
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity

Abstract

Disclosed are an apparatus and a method for removing noise from biosignals. An embodiment of the invention provides an apparatus for removing noise from biosignals measured for a particular period of time that includes: a similarity calculating unit configured to calculate a similarity between any one biosignal from among the biosignals and other biosignals; and a noise removal unit configured to remove noise from the any one biosignal by using the similarity. Aspects of the invention provide the advantage of effectively removing noise from biosignals without distorting the waveforms of the biosignals.

Claims

1. An apparatus for removing noise from biosignals measured for a particular period of time, the apparatus comprising:

a selection unit configured to select a target signal from a plurality of the biosignals;

a similarity calculating unit configured to calculate a similarity between the target signal and other biosignals,

wherein the similarity calculating unit comprises,

an alignment unit configured to aligning the biosignals with respect to an R peak of a QRS complex wave form included in the biosignals,

a search window setting unit configured to set a range of a search window to include the target signal and biosignals within a particular range centering around the target signal,

a unit window setting unit configured to set a size of a unit window within the search window, and

a calculating unit configured to calculate a similarity between signals included in a first unit window centering around the target signal and signals included in a second unit window centering around the other biosignals in the search window,

wherein the calculating unit calculates the similarity between the target signal and the other biosignals based on a sum of absolute deviation (SAD) between the first unit window and the second unit window for each of the other biosignals; and

a noise removal unit configured to remove noise from the target biosignal by using the similarity, wherein the noise removal unit comprises,

a weight calculating unit configured to calculate weights for the biosignals in the search window respectively by using the similarity, and

a weighted averaging unit configured to calculate a weighted average of the biosignals in the search window by using the weights and to remove noise from the target signal based on the weighted average of the biosignals.

2. The apparatus of claim 1, wherein the target signal is an electrocardiogram (ECG) signal, and the ECG signal includes a P-wave, the QRS-complex, and a T-wave waveform.

3. The apparatus of claim 2, wherein the weights used for calculating the weighted average is determined as follows:

w_n=e<sup>−

SADn/β</sup>

,

wherein w_n is the weight for a biosignal I_n, e is Euler'"'"'s number, β

is a constant for adjusting degree of noise removal, and SAD_n is the similarity between the biosignal I_n and the target signal I_R.

4. The apparatus of claim 3, wherein the alignment unit is configured to separate the biosignals based on a preset area centering around the R peak and is configured to align the separated biosignals with respect to the R peak.

5. The apparatus of claim 3, wherein the search window setting unit sets the range of the search window differently according to a type of waveform to which the selected target signal belongs, and

the unit window setting unit sets the size of the unit window differently according to the type of waveform to which the selected target signal belongs.

6. A method for removing noise from biosignals measured for a particular period of time, the method comprising:

calculating a similarity between a target signal from the biosignals and other biosignals, wherein the calculating of the similarity comprises;

aligning the biosignals with respect to an R peak of a QRS complex waveform included in the biosignals;

selecting the target signal for noise removal from the biosignals;

setting a range of a search window to include the target signal and biosignals within a particular range centering around the target signal from the biosignals included in the aligned biosignals;

setting a size of a unit window within the search window for the calculating of similarity; and

calculating a similarity between signals included in a first unit window centering around the target signal and signals included in a second unit window centering around the other biosignals in the search window,

wherein a sum of absolute deviation (SAD) between the first unit window and the second unit window for each of the other biosignals is used to calculate the similarity between the target signal and the other biosignals, and removing noise from the target signal by using the similarity,

wherein removing of the noise comprises;

calculating weights of the biosignals included in the search window respectively by using the similarity,

calculating a weighted average of the biosignals in the search window by using the weights, and

removing the noises from the target signal based on the weighted average of the biosignals.

7. The method of claim 6, wherein the target signal is an electrocardiogram (ECG) signal including a P-wave, the QRS-complex, and a T-wave waveform.

8. The method of claim 7, wherein the weights used for calculating the weighted average is determined as follows:

w_n=e<sup>−

SADn/β</sup>

,

wherein w_n is the weight for a biosignal I_n, e is Euler'"'"'s number, β

is a constant for adjusting degree of noise removal, and SAD_n is the similarity between the biosignal I_n and the target signal I_R.

9. The method of claim 8, wherein the target signal is selected from signals belonging to the P-wave, the QRS-complex, and the T-wave waveforms, and the setting of the range of the search window comprises setting the range of the search window differently according to a type of waveform to which the selected target signal belongs.

10. The method of claim 9, wherein the setting of the size of the unit window comprises setting the size of the unit window differently according to the type of waveform to which the selected target signal belongs.