KR20230043435A - Method for detecting respiration rate using piezoelectric sensor - Google Patents

Abstract

The present invention relates to a respiratory rate detection method based on an electrical signal obtained through a piezoelectric sensor. The respiratory rate detection method using the piezoelectric sensor according to one embodiment of the present invention is characterized in comprising: a step of performing pre-filtering processing for the electrical signal generated from the piezoelectric sensor; a step of determining an awakening section using a standard deviation of the pre-processed electrical signal; a step of performing post-filtering processing for the electrical signal wherein the awakening section has been removed; and a step of calculating a respiratory rate by applying Fourier transform to the post-processed electrical signal. Therefore, the present invention is capable of having an advantage of being able to measure the respiratory rate in real life.

Description

Respiratory rate detection method using a piezoelectric sensor {METHOD FOR DETECTING RESPIRATION RATE USING PIEZOELECTRIC SENSOR}

The present invention relates to a method for detecting a respiratory rate based on an electrical signal obtained through a piezoelectric sensor.

Since breathing expands or contracts the chest of the human body, a pressure difference is generated on a surface in contact with the chest, and a respiration rate of the human body can be detected based on the pressure difference. Various pressure sensors are used to detect pressure due to movement of the chest, and various methods for detecting a respiratory rate of the human body based on outputs of the pressure sensors are being developed.

However, in the prior art, there is a problem in that it is impossible to measure the respiratory rate in real life because the user has to wear complicated and sensitive equipment for precise measurement of the respiratory rate. In addition, conventional methods being developed to simply measure the respiratory rate in real life have a problem in that it is difficult to accurately measure the noise when it interferes with the insignificant pressure signal generated due to respiration and cannot effectively remove it.

An object of the present invention is to provide a method of extracting only pure respiratory components by processing an electrical signal acquired through a piezoelectric sensor and detecting a respiratory rate through the same.

The objects of the present invention are not limited to the above-mentioned objects, and other objects and advantages of the present invention not mentioned above can be understood by the following description and will be more clearly understood by the examples of the present invention. It will also be readily apparent that the objects and advantages of the present invention may be realized by means of the instrumentalities and combinations indicated in the claims.

In order to achieve the above object, a method for detecting a respiratory rate using a piezoelectric sensor according to an embodiment of the present invention includes performing preprocessing of filtering on an electrical signal generated by the piezoelectric sensor, and using a standard deviation of the preprocessed electrical signal for an arousal interval. It is characterized in that it comprises the step of determining a step, the step of performing filtering post-processing on the electrical signal from which the arousal section has been removed, and the step of calculating a respiratory rate by applying a Fourier transform to the post-processed electrical signal. .

In one embodiment, the performing of the filtering preprocessing includes applying an electrical signal generated by the piezoelectric sensor to a notch filter, and applying the electrical signal to which the notch filter is applied to a bandpass filter. It is characterized by doing.

In one embodiment, the determining of the arousal interval includes calculating a standard deviation of the preprocessed electrical signal, calculating a standard deviation of a Gaussian function value corresponding to the standard deviation of the electrical signal, and calculating the standard deviation of the Gaussian function value. The method may include setting a threshold value based on a standard deviation of the function value, and determining an arousal section of the electrical signal according to a comparison result between the standard deviation of the electrical signal and the threshold value.

In one embodiment, the performing of the filtering post-processing may include interpolating the electrical signal from which the arousal section is removed, applying a band-pass filter to the interpolated electrical signal, and applying the band-pass filter to the interpolated electrical signal. and applying the applied electrical signal to a moving average filter.

In one embodiment, the calculating of the respiratory rate may include converting the post-processed electrical signal into a digital signal, calculating a frequency component of the electrical signal by Fourier transforming the digital signal, and calculating the frequency component of the electrical signal. Calculating the respiratory rate based on the frequency having the maximum magnitude of the.

In one embodiment, the step of applying a Fourier transform to the digital signal comprises applying a Fast Fourier Transform (FFT) to the digital signal to perform a Discrete Fourier Transform (DFT) on the digital signal.

In one embodiment, the piezoelectric sensor is provided on an object in contact with the human body and includes a signal sensing unit that detects a value in which internal charge characteristics change according to applied pressure and acquires a biosignal, and a signal amplification unit that amplifies the biosignal. and a signal conversion unit that converts the biosignal into a digital signal to generate biosignal data, and a control unit that outputs the biosignal data as a time-series value.

The present invention has the advantage of allowing the user to easily wear the piezoelectric sensor so that the respiratory rate can be measured in real life.

In addition, the present invention has the advantage of measuring the respiratory rate by efficiently removing noise even if the signal of the respiratory component generated due to breathing is insignificant.

In addition to the effects described above, specific effects of the present invention will be described together while explaining specific details for carrying out the present invention.

1 is a diagram showing a piezoelectric sensor according to an embodiment of the present invention;
2A and 2B are diagrams illustrating an example of a signal sensing unit constituting a piezoelectric sensor;
3 is a diagram showing an example of a signal amplifier constituting a piezoelectric sensor;
4 is a view showing a state in which a main body constituting a piezoelectric sensor has a signal amplification unit and a signal conversion unit built in;
5 illustrates one embodiment of a piezoelectric sensor;
6 is a flowchart illustrating a respiratory rate detection method using a piezoelectric sensor according to an embodiment of the present invention.
7 is a diagram showing an example of a detailed process of a method for detecting a respiratory rate using a piezoelectric sensor;
8A to 8C are views for explaining a preprocessing filtering process according to an embodiment of the present invention.
9 is a diagram for explaining a method of determining an arousal section;
10 is a graph showing a graph obtained by Fourier transforming an electrical signal;

The above objects, features and advantages will be described later in detail with reference to the accompanying drawings, and accordingly, those skilled in the art to which the present invention belongs will be able to easily implement the technical spirit of the present invention. In describing the present invention, if it is determined that the detailed description of the known technology related to the present invention may unnecessarily obscure the subject matter of the present invention, the detailed description will be omitted. Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings. In the drawings, the same reference numerals are used to indicate the same or similar components.

In this specification, first, second, etc. are used to describe various components, but these components are not limited by these terms, of course. These terms are only used to distinguish one component from another component, and unless otherwise stated, the first component may be the second component, of course.

In addition, in the present specification, "upper (or lower)" or "upper (or lower)" of a component means that an arbitrary component is disposed in contact with the upper (or lower) surface of the component. In addition, it may mean that other components may be interposed between the component and any component disposed on (or under) the component.

In addition, in the present specification, when a component is described as being “connected”, “coupled” or “connected” to another component, the components may be directly connected or connected to each other, but other components may be present between each component. It should be understood that elements may be “interposed,” or that each element may be “connected,” “coupled,” or “connected” through other elements.

Also, singular expressions used in this specification include plural expressions unless the context clearly indicates otherwise. In this application, terms such as "consisting of" or "comprising" should not be construed as necessarily including all of the various components or steps described in the specification, and some of the components or some of the steps It should be construed that it may not be included, or may further include additional components or steps.

In addition, in this specification, when "A and / or B", unless otherwise specified, it means A, B or A and B, and when "C to D", it means a special opposite Unless otherwise specified, it means more than C and less than D

The present invention relates to a method for detecting a respiratory rate based on an electrical signal obtained through a piezoelectric sensor. First, a piezoelectric sensor according to an embodiment of the present invention will be described with reference to FIGS. 1 to 5 , and then a respiratory rate detection method using the piezoelectric sensor will be described in detail with reference to FIGS. 6 to 10 .

1 is a diagram illustrating a piezoelectric sensor according to an embodiment of the present invention.

2A and 2B are diagrams illustrating an example of a signal sensing unit constituting the piezoelectric sensor, and FIG. 3 is a diagram illustrating an example of a signal amplifier constituting the piezoelectric sensor.

4 is a view showing a state in which a main body constituting a piezoelectric sensor has a signal amplification unit and a signal conversion unit embedded therein. Meanwhile, FIG. 5 is a diagram illustrating an implementation example of a piezoelectric sensor.

Referring to FIG. 1, a piezoelectric sensor 800 according to an embodiment of the present invention includes a signal detection unit 801, a signal amplifier 802, a signal conversion unit 803, a body 805, and a control unit. (807). However, the piezoelectric sensor 800 shown in FIG. 1 is according to an embodiment, and its components are not limited to the embodiment shown in FIG. 1, and some components may be added, changed, or deleted as necessary. can

The signal sensing unit 801 may acquire a biosignal by contacting a human body and detecting a value in which internal charge characteristics vary according to pressure applied from the human body. Here, the biosignal may include any one of heart rate, respiration, sleep, sleep awakening, sleep efficiency, and respiratory rate per minute, and may be a signal measured in an unconstrained state during sleep.

The signal sensing unit 801 may include a piezoelectric element 1005 whose internal charge characteristics change according to externally applied pressure, and the piezoelectric element 1005 is a strip-type material made of polyvinylidene fluoride (PVDF). It may be implemented as a device, but is not limited thereto.

Referring to FIGS. 2A and 2B, the piezoelectric element (eg, PVDF film, 1005) of the signal sensing unit 801 is a bipolar electrode, 1003 manufactured using screen printing, specifically the upper part. It may be provided between a (top) electrode and a bottom electrode. Meanwhile, when the bipolar electrode 1003 has a plurality of protrusion patterns, the bipolar electrode 1003 may be designed so that the protrusion patterns of both electrodes are crossed with each other in consideration of capacitive noise.

This signal sensing unit 801 is designed to be very thin and flexible, so that the user can reduce the sense of difference felt when installed under the user's chest. To this end, the ring terminal ( Ring terminals and eyelets are available.

The above-described signal sensing unit 801 may output a biosignal expressed as an amount of electric charge, and the signal amplifier 802 may amplify the biosignal.

Referring to FIG. 3, the signal amplifier 802 includes a charge amplifier for amplifying a small amount of charge and outputting a voltage signal proportional to the charge, and a voltage for amplifying the voltage signal output from the charge amplifier. A voltage amplifier may be included.

When the biosignal is amplified, the signal converter 803 can convert it into a digital signal to generate biosignal data.

The signal conversion unit 803 may convert the analog voltage signal output from the signal amplification unit 802 into digital to generate biosignal data. To this end, an analog digital converter (ADC), a voltage regulator, and an oscillator (oscillator) and the like.

Meanwhile, the aforementioned signal amplification unit 802 and signal conversion unit 803 may be separated and accommodated in the main body 805 so that they can be connected through connectors.

Referring to FIG. 4, the body 805 is composed of a first body accommodating the signal amplification unit 802 and a second body accommodating the signal conversion unit 803, and includes the signal amplification unit 802 and the signal conversion unit. As 803 is connected through a connector, the first body and the second body may be coupled. When the signal amplification unit 802 and the signal conversion unit 803 are configured separately as described above, there is an advantage in that biosignals can be collected through multiple channels in the future.

The control unit 807 may output bio-signal data output from the signal conversion unit 803 as time-series values. The controller 807 includes application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), and micro-controllers. , microprocessors (microprocessors) may include at least one physical element. For example, the control unit 807 may be implemented as a smart phone, tablet, laptop, PC, or the like.

Referring to FIG. 5, the signal detection unit 801 is connected to one end of the main body 805 accommodating the signal amplifying unit 802 and the signal conversion unit 803, and the other end of the main body 805 is connected to the control unit 807. ) can be associated with The controller 807 may store biosignal data in a memory in the form of a file and output the biosignal data in a time-sequential graph. To this end, an application for generating a graph may be loaded in the control unit 807 .

As described above, by designing the piezoelectric sensor 800 to be light, thin, and flexible, the present invention allows the user to easily wear the piezoelectric sensor 800, and through this, there is an advantage in that the respiratory rate can be measured in real life. .

Although an example of the piezoelectric sensor 800 applied to the present invention has been described above, any piezoelectric sensor 800 that outputs an electrical signal according to an externally applied pressure may be used in the respiratory rate detection method described below.

Hereinafter, a respiratory rate detection method using a piezoelectric sensor will be described in detail with reference to FIGS. 6 to 10 .

6 is a flowchart illustrating a method for detecting a respiratory rate using a piezoelectric sensor according to an embodiment of the present invention, and FIG. 7 is a diagram illustrating an example of detailed processes of the method for detecting a respiratory rate using a piezoelectric sensor.

8A to 8C are diagrams for explaining a preprocessing filtering process according to an embodiment of the present invention.

9 is a diagram for explaining a method of determining an arousal section. 10 is a graph showing a graph obtained by Fourier transforming an electrical signal.

Referring to FIG. 6 , a method for detecting a respiratory rate using a piezoelectric sensor (hereinafter, a method for detecting a respiratory rate) using a piezoelectric sensor according to an embodiment of the present invention performs filtering preprocessing on an electrical signal generated by a piezoelectric sensor 800 (S100), Determining an arousal section using the standard deviation of the electrical signal (S200), performing filtering post-processing on the electrical signal in the arousal section (S300), and calculating a respiratory rate by applying a Fourier transform to the electrical signal (S300). S400) may be included. However, the respiratory rate detection method shown in FIG. 6 is according to an embodiment, and each step constituting the invention is not limited to the embodiment shown in FIG. 6, and some steps may be added, changed, or deleted as necessary. there is.

Each of the steps shown in FIG. 6 may be performed by a processor or may be performed by the controller 807 of the piezoelectric sensor 800 described above. However, hereinafter, the processor will be described as a subject performing the present invention, and the processor includes ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs ( It may be implemented by including field programmable gate arrays), micro-controllers, and the like.

Meanwhile, a method for detecting a respiratory rate according to an embodiment of the present invention may be embodied as shown in FIG. 7, and the operation of the present invention will be described below with reference to FIG. 7 as an example.

The processor may perform filtering preprocessing on the electric signal generated by the piezoelectric sensor 800 (S100). Here, the electrical signal is an output signal of the piezoelectric sensor 800 and may include the aforementioned biosignal.

The piezoelectric sensor 800 may output an electrical signal (Signal _Strip ) generated by a user's motion, and the electrical signal may have a waveform as shown in FIG. 8A. Meanwhile, the electric signal shown in FIG. 8A may include power line interference (eg, frequency noise of 60 [Hz]).

To remove this, the processor may apply the electrical signal to a notch filter (S11). Specifically, the processor may apply an infinite impulse response (IIR) notch filter to the electrical signal, and accordingly, the electrical signal may be filtered as shown in the waveform shown in FIG. 8B.

Subsequently, the processor may apply the electrical signal to which the notch filter is applied to a band pass filter (BPF) in order to selectively obtain a motion component (S12). Specifically, the processor may apply the electrical signal to an IIR band pass filter having a pass band of 0.4 to 1 [Hz]. Accordingly, the electrical signal may be filtered as shown in the waveform shown in FIG. 8C.

In summary, noise is removed from the electrical signal generated by the user's motion through the preprocessing of steps S11 and S12, and only motion components can be extracted.

Subsequently, the processor may determine an awake section using the standard deviation of the preprocessed electrical signal (S200).

Referring back to FIG. 7 , the processor may calculate the standard deviation of the preprocessed electrical signal (S13). Specifically, the processor may repeatedly calculate the standard deviation (SD _signal ) of the electrical signal for an overlapping time window (eg, 7 seconds).

Subsequently, the processor may generate a histogram of the calculated standard deviation (S14), and may calculate a Gaussian function value by applying a Gaussian function to a bin smaller than the maximum value of the histogram (S15).

일 때, 그 배수 예컨대

를 임계값으로 설정할 수 있다.Then, the processor may calculate the standard deviation of the Gaussian function value, and based on this, a threshold value for determining the arousal section may be set. For example, a processor can determine that the standard deviation of the values of the Gaussian function is

When , the multiple e.g.

can be set as a threshold.

Subsequently, the processor may determine an arousal section of the electrical signal according to a comparison result between the standard deviation of the electrical signal and the threshold (S16).

Specifically, referring to FIG. 9 , the processor may determine a right area larger than a threshold value as an awake section and a left area smaller than the threshold value as a sleep section in the histogram for the standard deviation of the electrical signal. there is.

When the determination of the arousal interval is completed, the processor may remove the arousal interval from the electrical signal and perform filtering post-processing on the electrical signal from which the arousal interval is removed (S300).

Referring back to FIG. 7 , the processor may remove an arousal section including motion artifact from the electrical signal (S17), and may interpolate the removed section from the electrical signal using neighboring data. there is.

Subsequently, the processor may apply a band pass filter to the interpolated electrical signal (S18). Specifically, the processor may apply the interpolated electrical signal to an IIR bandpass filter having a pass band of 0.1 to 0.5 [Hz] to extract the respiratory component.

Next, the processor may apply the electrical signal filtered by the bandpass filter to a moving average filter (MAF) for smoothing (S19). For example, the processor may apply a moving average filter to the electrical signal over a time window of 2 seconds.

In summary, the electrical signal generated by the user's motion is removed from motion noise through the post-processing of steps S17 to S19, and only pure respiratory components can be extracted.

Subsequently, the processor may calculate a respiratory rate by applying a Fourier transform to the post-processed electrical signal (S400).

The processor may convert the post-processed electrical signal into a digital signal, and may calculate a frequency component of the electrical signal by Fourier transforming the digital signal (S20).

Specifically, referring to FIG. 7 again, the processor may generate a signal expressed by a magnitude according to a frequency component by Fourier transforming a digital electrical signal expressed by a magnitude according to time. That is, as shown in FIG. 10 , an electric signal expressed as an amplitude according to a slow-time index may be Fourier transformed and expressed as an amplitude according to a frequency component.

Meanwhile, in performing the Fourier transform, the processor may discrete Fourier transform the digital signal by applying the fast Fourier transform to the digital electrical signal. In other words, the processor may convert the discretized time electrical signal into the discretized frequency electrical signal, and may use fast Fourier transform to increase the conversion speed.

When the aforementioned Fourier transform is completed, the processor may calculate a respiratory rate based on a frequency having a maximum magnitude among frequency components of the Fourier transformed electrical signal (S21).

For example, when the Fourier-transformed electrical signal is as shown in FIG. 10 , the processor may identify a frequency having a maximum magnitude as 0.45 [Hz] among frequency components included in the electrical signal. The processor may calculate a respiratory rate of 27 times per minute based on the corresponding frequency.

As described above, the present invention has the advantage of measuring the respiratory rate by efficiently removing noise even if the signal of the respiratory component generated by breathing is insignificant.

As described above, the present invention has been described with reference to the drawings illustrated, but the present invention is not limited by the embodiments and drawings disclosed in this specification, and various modifications are made by those skilled in the art within the scope of the technical idea of the present invention. It is obvious that variations can be made. In addition, although the operational effects according to the configuration of the present invention have not been explicitly described and described while describing the embodiments of the present invention, it is natural that the effects predictable by the corresponding configuration should also be recognized.

Claims (7)

performing filtering pre-processing on the electric signal generated by the piezoelectric sensor;
determining an arousal section using a standard deviation of the preprocessed electrical signal;
performing post-filtering processing on the electrical signal from which the arousal section has been removed; and
Calculating a respiratory rate by applying a Fourier transform to the post-processed electrical signal
Respiratory rate detection method using piezoelectric sensor.
According to claim 1,
The step of performing the filtering preprocessing is
applying an electrical signal generated by the piezoelectric sensor to a notch filter;
Applying the notch filter-applied electrical signal to a band pass filter.
Respiratory rate detection method using piezoelectric sensor.
According to claim 1,
The step of determining the arousal section is
Calculating a standard deviation of the preprocessed electrical signal;
Calculating a standard deviation of a Gaussian function value corresponding to the standard deviation of the electrical signal;
setting a threshold value based on the standard deviation of the Gaussian function value;
Determining an arousal interval of the electrical signal according to a comparison result between the standard deviation of the electrical signal and the threshold
Respiratory rate detection method using piezoelectric sensor.
According to claim 1,
The step of performing the filtering post-processing is
interpolating the electrical signal from which the arousal section has been removed;
applying a band pass filter to the interpolated electrical signal;
Applying the band-pass filter-applied electrical signal to a moving average filter
Respiratory rate detection method using piezoelectric sensor.
According to claim 1,
Calculating the respiratory rate
converting the post-processed electrical signal into a digital signal;
Fourier transforming the digital signal to calculate a frequency component of the electrical signal;
Comprising the step of calculating the respiratory rate based on the frequency having the maximum magnitude among the frequency components
Respiratory rate detection method using piezoelectric sensor.
According to claim 5,
Applying a Fourier transform to the digital signal
Applying a Fast Fourier Transform (FFT) to the digital signal to perform a Discrete Fourier Transform (DFT) on the digital signal.
Respiratory rate detection method using piezoelectric sensor.
According to claim 1,
The piezoelectric sensor
a signal sensing unit provided on an object in contact with the human body and acquiring a biosignal by detecting a value in which internal charge characteristics change according to applied pressure;
a signal amplifier for amplifying the biosignal;
a signal conversion unit that converts the biosignal into a digital signal to generate biosignal data;
Including a control unit for outputting the biosignal data as a time-series value
Respiratory rate detection method using piezoelectric sensor.

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