Method and system for removing noise from bio signal

Abstract

According to one aspect of the present invention, a method for removing noise from a biological signal is provided, comprising the steps of determining attribute information of a KZ (Kolmogorov-Zurbenko) filter, extracting a baseline component from the biological signal using the KZ filter, and removing the extracted baseline component from the biological signal.

Description

Technology Field

[0001] The present invention relates to a method and system for removing noise from a biological signal. Background Technology

[0002] With the advancement of science and technology, various technologies for monitoring biological signals are being developed.

[0003] In the process of monitoring biosignals, if there is movement of the subject (e.g., a patient), the acquired biosignals may contain noise. Since the biosignals may be difficult to analyze or display if they contain noise, it may be necessary to remove the noise from the biosignals.

[0004] As an example of conventional technology regarding a method for removing noise from biological signals, there is a method of removing noise from biological signals using a moving average filter. However, the method using the moving average filter employed in the conventional technology had two problems.

[0005] First, when the filter length (i.e., the length of the interval subject to the moving average calculation) is short, the filter's cutoff characteristics for high-frequency components may be poor, and since the signal subject to analysis (e.g., the QRS signal) is included in the baseline component, there was a problem where the signal subject to analysis was also removed during the noise removal process.

[0006] Second, when the filter length is long, the filter's response characteristics to changes in biological signals can be poor, leading to a problem where noise removal is not completely achieved.

[0007] Accordingly, the inventor(s) propose a technique that extracts a baseline component from a biological signal using a KZ (Kolmogorov-Zurbenko) filter and removes the baseline component from the biological signal, thereby removing noise from the biological signal while ensuring that the signal to be analyzed is not removed. Prior art literature

[0008] Published Patent Application No. 10-2021-0155148 (December 22, 2021) The problem to be solved

[0009] The present invention aims to solve all the problems of the aforementioned prior art.

[0010] In addition, the present invention has another objective of determining attribute information of a KZ filter, extracting a baseline component from a biological signal using a KZ filter, and removing the extracted baseline component from the biological signal.

[0011] In addition, another objective of the present invention is to prevent the loss of the signal to be analyzed (e.g., QRS signal) by dynamically determining the attribute information of the KZ filter during the process of removing noise from a biological signal.

[0012] In addition, another objective of the present invention is to prevent distortion of the biosignal during the process of removing noise from the biosignal. means of solving the problem

[0013] A representative configuration of the present invention for achieving the above objective is as follows.

[0014] According to one aspect of the present invention, a method is provided comprising the steps of determining attribute information of a KZ (Kolmogorov-Zurbenko) filter, extracting a baseline component from a biological signal using the KZ filter, and removing the extracted baseline component from the biological signal.

[0015] According to another aspect of the present invention, a system is provided comprising: an attribute information determining unit for determining attribute information of a KZ (Kolmogorov-Zurbenko) filter; and a signal management unit for extracting a baseline component from a biological signal using the KZ filter and removing the extracted baseline component from the biological signal.

[0016] In addition to this, other methods for implementing the present invention, other systems, and non-transient computer-readable recording media for recording a computer program for executing said methods are further provided. Effects of the invention

[0017] According to the present invention, attribute information of a KZ filter is determined, a baseline component is extracted from a biological signal using a KZ filter, and the extracted baseline component can be removed from the biological signal.

[0018] In addition, according to the present invention, by dynamically determining the attribute information of the KZ filter during the process of removing noise from a biological signal, it is possible to prevent the signal to be analyzed (e.g., QRS signal) from being lost.

[0019] In addition, according to the present invention, it is possible to prevent distortion of the biosignal during the process of removing noise from the biosignal. Brief explanation of the drawing

[0020] FIG. 1 is a diagram showing the schematic configuration of an overall system for removing noise from a biological signal according to one embodiment of the present invention. FIG. 2 is a drawing illustrating in detail the internal configuration of a signal processing system according to one embodiment of the present invention. FIG. 3 is a diagram exemplarily illustrating the process of removing noise from a biosignal according to one embodiment of the present invention. FIG. 4 is a diagram exemplarily illustrating the process of removing noise from a biological signal according to one embodiment of the present invention. Specific details for implementing the invention

[0021] The following detailed description of the invention refers to the accompanying drawings, which illustrate specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that various embodiments of the invention are different but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be modified from one embodiment to another without departing from the spirit and scope of the invention. It should also be understood that the location or arrangement of individual components within each embodiment may be modified without departing from the spirit and scope of the invention. Accordingly, the following detailed description is not meant to be limiting, and the scope of the invention should be understood to encompass the scope claimed by the claims and all equivalents thereof. Similar reference numerals in the drawings indicate identical or similar components across various aspects.

[0022] Hereinafter, in order to enable a person skilled in the art to easily practice the present invention, various preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0023] Configuration of the entire system

[0024] FIG. 1 is a diagram showing the schematic configuration of an overall system for removing noise from a biological signal according to one embodiment of the present invention.

[0025] As illustrated in FIG. 1, the entire system according to one embodiment of the present invention may include a communication network (100), a signal processing system (200), and a device (300).

[0026] First, a communication network (100) according to one embodiment of the present invention can be configured regardless of the mode of communication, such as wired communication or wireless communication, and can be configured as various communication networks such as a Local Area Network (LAN), a Metropolitan Area Network (MAN), or a Wide Area Network (WAN). Preferably, the communication network (100) referred to in this specification may be the known Internet or the World Wide Web (WWW). However, the communication network (100) may include at least a known wired / wireless data communication network, a known telephone network, or a known wired / wireless television communication network, without being limited thereto.

[0027] For example, the communication network (100) may be a wireless data communication network and may implement conventional communication methods such as WiFi communication, WiFi-Direct communication, Long Term Evolution (LTE) communication, 5G communication, Bluetooth communication (including Bluetooth Low Energy (BLE) communication), infrared communication, ultrasonic communication, etc., in at least a part thereof. As another example, the communication network (100) may be an optical communication network and may implement conventional communication methods such as Light Fidelity (LiFi), etc., in at least a part thereof.

[0028] Next, a signal processing system (200) according to one embodiment of the present invention can determine attribute information of a KZ filter, extract a baseline component from a biological signal using a KZ filter, and perform the function of removing the extracted baseline component from the biological signal.

[0029] The configuration and function of the signal processing system (200) according to the present invention will be examined in detail through the following detailed description.

[0030] Next, the device (300) according to one embodiment of the present invention is a digital device that includes a function to communicate after connecting to a signal processing system (200), and any digital device equipped with memory means and equipped with a microprocessor to have computational capabilities, such as a smart patch, smartphone, tablet, smart watch, smart band, smart glasses, desktop computer, laptop computer, workstation, PDA, web pad, mobile phone, etc., can be adopted as the device (300) according to the present invention.

[0031] For example, a device (300) according to one embodiment of the present invention may be a wearable monitoring device comprising a sensing means (e.g., contact electrode, imaging device, etc.) for measuring a predetermined biosignal (e.g., electrocardiogram (ECG), electromyogram (EMG), electroencephalogram (EEG), photoplethysmogram (PPG), etc.) from a human body and a display means for providing various information regarding the measurement of the biosignal to a user.

[0032] In particular, the device (300) may include an application (not shown) that enables a user to receive functions according to the present invention from the signal processing system (200). Such an application may be downloaded from the signal processing system (200) or an external application distribution server (not shown). Meanwhile, the nature of such an application may generally be similar to the attribute information determination unit (210), signal management unit (220), communication unit (230), and control unit (240) of the signal processing system (200) as described below. Here, at least a part of the application may be replaced with a hardware device or firmware device capable of performing substantially the same or equivalent functions as needed.

[0033] Configuration of a signal processing system

[0034] Below, we will examine the internal configuration of the signal processing system (200) that performs important functions for the implementation of the present invention and the functions of each component.

[0035] FIG. 2 is a drawing illustrating in detail the internal configuration of a signal processing system (200) according to one embodiment of the present invention.

[0036] As illustrated in FIG. 2, a signal processing system (200) according to one embodiment of the present invention may be configured to include an attribute information determination unit (210), a signal management unit (220), a communication unit (230), and a control unit (240). According to one embodiment of the present invention, the attribute information determination unit (210), the signal management unit (220), the communication unit (230), and the control unit (240) may be program modules, at least some of which communicate with an external system (not shown). Such program modules may be included in the signal processing system (200) in the form of an operating system, an application program module, or other program modules, and may be physically stored in various known storage devices. Additionally, such program modules may be stored in a remote storage device capable of communicating with the signal processing system (200). Meanwhile, such program modules encompass, but are not limited to, routines, subroutines, programs, objects, components, data structures, etc., that perform specific tasks or execute specific abstract data types as described below according to the present invention.

[0037] Meanwhile, although the signal processing system (200) has been described as above, this description is exemplary, and it is obvious to those skilled in the art that at least some of the components or functions of the signal processing system (200) may be realized within a device (300) or server (not shown) or included within an external system (not shown) as needed.

[0038] First, the attribute information determining unit (210) according to one embodiment of the present invention can perform the function of determining attribute information of a KZ (Kolmogorov-Zurbenko) filter.

[0039] Specifically, a KZ filter according to one embodiment of the present invention may include a filter that can be implemented by connecting (or repeating) R moving average filters having a length (i.e., the length of the interval to be calculated for the moving average) of L.

[0040] For example, a KZ filter according to one embodiment of the present invention may be specified by the length of the filter and the number of connected moving average filters. Here, a KZ filter according to one embodiment of the present invention may be expressed by a polynomial relating the length L of the moving average filter and the number R of the moving average filters. Additionally, a KZ filter according to one embodiment of the present invention may be implemented by generating moving average filters R times in a manner such as generating a moving average filter having length L and generating another moving average filter by applying a moving average operation to the said moving average filter.

[0041] In addition, the attribute information of the KZ filter according to one embodiment of the present invention may include at least one of phase information and order information.

[0042] For example, a KZ filter according to one embodiment of the present invention can be specified by the length of the moving average filter (e.g., L=77) and the number of moving average filters (e.g., R=6). Here, the attribute information determining unit (210) according to one embodiment of the present invention can determine the phase information of the KZ filter (e.g., information that the phase delay value is 230) and the order information of the KZ filter (e.g., information that the order R is 6) by referring to the length of the moving average filter and the number of moving average filters.

[0043] As another example, an attribute information determining unit (210) according to one embodiment of the present invention may determine the attribute information of a KZ filter as first phase information and first order information. Here, the length of the moving average filter and the number of moving average filters of the KZ filter are determined to correspond to the first phase information and the first order information, thereby determining the KZ filter.

[0044] Next, a signal management unit (220) according to one embodiment of the present invention can perform the function of extracting a baseline component from a biological signal using a KZ filter.

[0045] Specifically, the biosignals according to one embodiment of the present invention may include various biosignals such as electrocardiogram signals (e.g., ECG signals), blood oxygen saturation, heart rate, body temperature, brain waves (e.g., EEG signals), and pulse waves (e.g., PPG signals).

[0046] In addition, the baseline component according to one embodiment of the present invention may include components that may be generated from the movement of the subject (e.g., patient) or from various factors that may affect the biosignal other than the movement of the subject.

[0047] According to the present invention, the waveform (or location of occurrence) of the QRS signal may be important information during the analysis (or monitoring) of the electrocardiogram signal. However, according to one embodiment of the present invention, as described below, the signal management unit (220) may remove the baseline component from the biosignal. If the baseline component includes the QRS signal, the QRS signal may be removed from the biosignal, making it difficult (or impossible) to properly monitor the electrocardiogram signal.

[0048] In addition, according to one embodiment of the present invention, when the biological signal is an electrocardiogram signal, the attribute information of the KZ filter can be dynamically determined by referring to whether the baseline component includes a QRS signal. Here, the QRS signal according to one embodiment of the present invention is an electrocardiogram signal generated by the depolarization of the left and right ventricles, and may include an electrocardiogram signal that appears prior to ventricular contraction.

[0049] According to the present invention, by utilizing the R wave, which has the largest amplitude among the P, Q, R, S, and T waves constituting the electrocardiogram signal, and the adjacent Q and S waves (i.e., utilizing the QRS signal), it becomes easy to determine whether the electrocardiogram signal to be analyzed (i.e., the QRS signal) is included in the baseline component. In other words, according to the present invention, by determining the attribute information of the KZ filter by referring to whether the QRS signal is included in the baseline component, it becomes easy to determine whether the electrocardiogram signal to be analyzed is included in the baseline component (i.e., since the QRS signal has a relatively large amplitude, it is easy to determine whether the QRS signal is included in the baseline component).

[0050] For example, an attribute information determining unit (210) according to one embodiment of the present invention can update the order information of a KZ filter (e.g., sequentially updating the order information in a direction in which the order increases) in response to a determination that a QRS signal is included in the baseline component, and a signal management unit (220) can extract the baseline component again from the biosignal using the updated KZ filter in response to the updated order information.

[0051] For a specific example, if the attribute information determining unit (210) according to one embodiment of the present invention determines the attribute information of the KZ filter as first-order information (e.g., R=1) and the baseline component contains a QRS signal, the attribute information determining unit (210) may update the attribute information of the KZ filter to second-order information (e.g., R=2), and the signal management unit (220) may extract the baseline component again from the biological signal using the KZ filter updated in correspondence with the updated second-order information. If the baseline component is extracted by the KZ filter updated with the attribute information including the second-order information according to one embodiment of the present invention, and the QRS signal is still included in the baseline component, the attribute information determining unit (210) may update the attribute information of the KZ filter to third-order information (e.g., R=3), and the signal management unit (220) may extract the baseline component again from the biological signal. Furthermore, the attribute information determining unit (210) according to one embodiment of the present invention can update the order information (e.g., by increasing the R value) until the QRS signal is not included in the baseline component.

[0052] Accordingly, according to the present invention, as the order information is updated (e.g., by increasing the R value from R=1), the QRS signal in the baseline component is effectively removed, while the baseline component can track the baseline wander, and as described below, noise in the biosignal can be effectively removed.

[0053] Meanwhile, according to one embodiment of the present invention, when the biological signal is an electrocardiogram signal, it will be obvious to those skilled in the art that the attribute information of the KZ filter may be dynamically determined by further referring to whether the baseline component includes not only the QRS signal but also P-wave and T-wave signals.

[0054] Next, the signal management unit (220) according to one embodiment of the present invention may further perform the function of removing the extracted baseline component from the biosignal.

[0055] Specifically, the signal management unit (220) according to one embodiment of the present invention removes baseline components that do not include QRS signals from the biosignal, thereby enabling the removal of noise without loss of the biosignal to be analyzed.

[0056] Meanwhile, a signal management unit (220) according to one embodiment of the present invention can correct a baseline component based on the phase information of a KZ filter and remove the corrected baseline component from the biosignal.

[0057] For example, if the attribute information determining unit (210) according to one embodiment of the present invention determines the attribute information of the KZ filter as a first phase information and a first order information (wherein, a first length of the moving average filter and a first number of iterations of the moving average filter corresponding to the first phase information and the first order information, respectively, may be determined together), the signal management unit (220) corrects the baseline component based on the first phase information (for example, corrects the baseline component by shifting it by the delay phase of the first phase information), and can remove the corrected baseline component from the biosignal.

[0058] As another example, according to one embodiment of the present invention, the attribute information determining unit (210) determines the attribute information of the KZ filter as first phase information and first order information, and the signal management unit (220) extracts a first baseline component, and it can be assumed that the first baseline component contains a QRS signal. Here, according to one embodiment of the present invention, the attribute information determining unit (210) updates the attribute information of the KZ filter as second phase information and second order information, and the signal management unit (220) can extract a second baseline component, and if the second baseline component does not contain a QRS signal, the signal management unit (220) can correct the baseline component based on the first phase information.

[0059] According to the present invention, since the baseline component can be extracted by sequentially generating a moving average filter to track baseline fluctuations of the biosignal, the baseline component may be delayed in phase compared to the biosignal, and as described above, by correcting the baseline component based on phase information, noise can be effectively removed from the biosignal.

[0060] Next, a communication unit (230) according to one embodiment of the present invention can perform the function of enabling data transmission and reception from / to the attribute information determination unit (210) and the signal management unit (220).

[0061] Finally, the control unit (240) according to one embodiment of the present invention can perform the function of controlling the flow of data between the attribute information determination unit (210), the signal management unit (220), and the communication unit (230). That is, the control unit (240) according to one embodiment of the present invention can control the attribute information determination unit (210), the signal management unit (220), and the communication unit (230) to perform their respective unique functions by controlling the flow of data from / to / from the outside of the signal processing system (200) or the flow of data between each component of the signal processing system (200).

[0062] Hereinafter, details regarding the removal of noise from a biological signal according to one embodiment of the present invention will be described in detail with reference to FIGS. 3 and FIGS. 4.

[0063] Examples

[0064] FIG. 3 is a diagram exemplarily illustrating the process of removing noise from a biosignal according to one embodiment of the present invention, and FIG. 4 is a diagram exemplarily illustrating the process of removing noise from a biosignal according to one embodiment of the present invention.

[0065] According to one embodiment of the present invention, the attribute information determining unit (210) can determine the attribute information of the KZ filter as first order information (e.g., R=1).

[0066] Next, referring to FIG. 3, the signal management unit (220) can extract a baseline component (410) from a biosignal (400) (e.g., an electrocardiogram signal) using a KZ filter.

[0067] Then, referring to FIG. 3, in response to the determination that QRS signals (411a, 411b and 411c) are included in the baseline component (410), the attribute information determining unit (210) can update the order information of the KZ filter to the second order information (e.g., R=2).

[0068] Then, the signal management unit (220) can extract the baseline component from the biosignal again using a KZ filter that is updated in response to the second order information, and the order information can be updated until the biosignal does not contain a signal to be analyzed (e.g., a QRS signal) (e.g., updated by increasing the order by 1 until the baseline component does not contain a QRS signal).

[0069] Next, the signal management unit (220) can remove the corresponding baseline component from the biosignal in response to the determination that the baseline component does not contain a QRS signal.

[0070] Referring to FIG. 4(a), the baseline component (410) extracted from the biosignal (400) may be determined to be one that does not contain a QRS signal (e.g., one that does not leave a trace of an electrocardiogram waveform). Here, the signal management unit (220) can remove the baseline component (410) from the biosignal (400).

[0071] Referring to FIG. 4(b), the signal management unit (220) can extract (or derive) a noise-removed biosignal (500) by removing the baseline component from a biosignal (400) that contained noise.

[0072] Accordingly, according to the present invention, by using the finally extracted noise-removed biosignal (500), accurate analysis (or monitoring) of the biosignal can be performed.

[0073] The embodiments according to the present invention described above may be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable recording medium. The computer-readable recording medium may include program instructions, data files, data structures, etc., either individually or in combination. The program instructions recorded on the computer-readable recording medium may be those specifically designed and configured for the present invention or those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. Hardware devices may be modified into one or more software modules to perform processing according to the present invention, and vice versa.

[0074] Although the present invention has been described above with reference to specific details such as specific components, limited embodiments, and drawings, this is provided only to aid in a more comprehensive understanding of the invention, and the invention is not limited to the above embodiments, and a person skilled in the art to which the invention belongs can make various modifications and changes from this description.

[0075] Accordingly, the scope of the present invention should not be limited to the embodiments described above, and all scopes equivalent to or equivalently modified from the claims set forth below, as well as the claims set forth below, shall be considered to fall within the scope of the concept of the present invention. Explanation of the symbols

[0076] 100: Communication network 200: Signal Processing System 210: Attribute Information Determination Unit 220: Signal Management Department 230: Communications Department 240: Control unit 300: Device 400: Biosignal 410: Baseline component 411: QRS signal 500: Noise-removed biosignal

Claims

Claim 1 A method for removing noise from a biological signal comprises: a step of determining attribute information of a KZ (Kolmogorov-Zurbenko) filter; a step of extracting a baseline component from the biological signal using the KZ filter; and a step of removing the extracted baseline component from the biological signal, wherein the biological signal includes an electrocardiogram signal; wherein, in the determining step, order information included in the attribute information of the KZ filter is updated in response to a determination that the baseline component contains a QRS signal; wherein, in the extraction step, the baseline component is extracted again from the biological signal using the KZ filter updated in response to the updated order information; and wherein, in the removal step, the baseline component extracted again is removed from the biological signal in response to a determination that the baseline component extracted again does not contain a QRS signal. Claim 2 delete Claim 3 In claim 1, the attribute information of the KZ filter further includes phase information. Claim 4 A method according to paragraph 3, wherein in the extraction step, the baseline component is corrected based on the phase information of the KZ filter, and in the removal step, the corrected baseline component is removed from the biosignal. Claim 5 A method in which the attribute information of the KZ filter in claim 1 is dynamically determined by referring to whether the baseline component contains a QRS signal. Claim 6 delete Claim 7 A non-transient computer-readable recording medium for recording a computer program for executing the method according to paragraph 1. Claim 8 A system for removing noise from a biological signal, comprising: an attribute information determining unit for determining attribute information of a KZ (Kolmogorov-Zurbenko) filter; and a signal management unit for extracting a baseline component from a biological signal using the KZ filter and removing the extracted baseline component from the biological signal, wherein the biological signal includes an electrocardiogram signal; wherein the attribute information determining unit updates order information included in the attribute information of the KZ filter in response to a determination that the baseline component contains a QRS signal; wherein the signal management unit extracts the baseline component again from the biological signal using the updated KZ filter in response to the updated order information; and wherein the signal management unit removes the again extracted baseline component from the biological signal in response to a determination that the again extracted baseline component does not contain a QRS signal. Claim 9 delete Claim 10 In paragraph 8, the attribute information of the above KZ filter further includes phase information in the system. Claim 11 In item 10, the signal management unit corrects the baseline component based on the phase information of the KZ filter and removes the corrected baseline component from the biosignal. Claim 12 In claim 8, the attribute information of the above KZ filter is dynamically determined by referring to whether the baseline component contains a QRS signal. Claim 13 delete

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