KR102221370B1 - A method and apparatus for detecting awakening and respiration rate based on force-sensor - Google Patents

Abstract

The present invention relates to a method and apparatus for detecting arousal and respiration rate based on a force sensor. A method of operating a bio-signal measuring apparatus according to an embodiment of the present invention includes performing pre-filtering on a force signal detected from a user's motion; Calculating an arousal section using the standard deviation of the force signal for each first time section; Performing filtering post-processing on the force signal based on the awakening period; And calculating a respiration rate by using the maximum power spectral density of the force signal for each second time interval.

Description

A method and apparatus for detecting awakening and respiration rate based on force-sensor.

The present invention relates to a method and apparatus for detecting arousal and respiration rate, and more particularly, to a method and apparatus for detecting arousal and respiration rate based on a force-sensor.

Mechanical movements such as breathing during movement of the human body generate force or pressure according to the movement. Breathing, for example, expands and contracts the rib cage, thus exerting pressure on the surface it abuts.

If the breathing detection sensor is placed under the chest, a change in force such as pressure due to breathing occurs, and by measuring it, arousal and respiration can be detected. The sensors may be arranged in various forms.

A number of technologies for detecting arousal and respiration through vibrations generated by the human body are under research and development, and a pressure or force sensor is placed on the cushion or back of a chair to detect arousal and respiration through vibration measurement, or the driver's seat or safety It can be applied in various ways, such as measuring arousal and respiration by detecting vibration by embedding a pressure sensor, force sensor, or acceleration sensor in the belt, or measuring a change in pressure or force by placing a sensor under the foot.

In addition, by attaching a sensor above the bed or under the mattress to measure breathing during sleep, a circular sensor is placed under the mattress to monitor the breathing of infants and toddlers, or a strip-type force sensor or pressure sensor is attached to the mattress to measure breathing during sleep. It can be applied in the form of

However, the conventional arousal/breathing monitoring device as described above has a high installation cost, causes user inconvenience because the user wears complex equipment, and has a problem that precise measurement is impossible because distortion occurs due to changes in the surrounding environment. have.

[Non-Patent Document 1] (CA Kushida, A. Chang, C. Gadkary, C. Guilleminault, O. Carrillo, and WC Dement, "Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients," (in eng), Sleep Med, vol. 2, no. 5, pp. 389-96, Sep 2001.)

The present invention has been created to solve the above-described problem, and an object thereof is to provide a method and apparatus for detecting arousal and respiration rate based on a force sensor.

In addition, an object of the present invention is to provide a method and apparatus for calculating an arousal section using the standard deviation of a force signal.

It is another object of the present invention to provide a method and apparatus for calculating a respiration rate by using the maximum power spectral density of a force signal.

The objects of the present invention are not limited to the objects mentioned above, and other objects not mentioned will be clearly understood from the following description.

In order to achieve the above objects, a method of operating a biosignal measuring apparatus according to an embodiment of the present invention includes performing filtering preprocessing on a force signal detected from a user's motion; Calculating an arousal section using the standard deviation of the force signal for each first time section; Performing filtering post-processing on the force signal based on the awakening period; And calculating a respiration rate by using the maximum power spectral density of the force signal for each second time interval.

In an embodiment, the performing of the filtering preprocess may include applying a force signal detected from the user's motion to a notch filter; And applying the force signal to which the notch filter is applied to a first bandpass filter.

In an embodiment, the calculating of the awakening period includes: calculating a standard deviation of the force signal for each of the first time periods; Calculating a standard deviation of a Gaussian function corresponding to the standard deviation of each force signal; Determining a threshold value based on the standard deviation of the Gaussian function; And classifying the first time interval corresponding to the standard deviation of the force signal into the awakening interval when the standard deviation of the force signal is greater than the threshold value.

In an embodiment, when the standard deviation of the force signal is less than the threshold value, classifying the first time period corresponding to the standard deviation of the force signal as a sleep period.

In an embodiment, the performing of the filtering post-processing may include interpolating the force signal for the awakening period; Applying the interpolated force signal to a second bandpass filter; And applying the force signal to which the second bandpass filter is applied to a moving average filter.

In an embodiment, the calculating of the respiration rate includes: determining a frequency having the maximum power for each second time period; And calculating the respiration rate by using the frequency.

In an embodiment, the biosignal measuring apparatus performs filtering preprocessing on the force signal from the user's movement, calculates an awakening section using the standard deviation of the force signal for each first time section, and calculates the awakening section based on the awakening section. It may include; a control unit that performs filtering post-processing on the force signal and calculates a respiration rate by using the maximum power spectral density of the force signal for each second time interval.

In an embodiment, the controller may apply the force signal detected from the user's motion to the notch filter, and apply the force signal to which the notch filter is applied to the first bandpass filter.

In an embodiment, the control unit calculates a standard deviation of the force signal for each of the first time intervals, calculates a standard deviation of a Gaussian function corresponding to the standard deviation of each force signal, and the standard of the Gaussian function A threshold value based on a deviation is determined, and when the standard deviation of the force signal is greater than the threshold value, the first time interval corresponding to the standard deviation of the force signal may be classified as the awakening interval.

In an embodiment, when the standard deviation of the force signal is less than the threshold value, the controller may classify the first time period corresponding to the standard deviation of the force signal as a sleep period.

In an embodiment, the control unit interpolates the force signal for the awakening section, applies the interpolated force signal to a second band pass filter, and moves the force signal to which the second band pass filter is applied. It can be applied to the average filter.

In an embodiment, the controller may determine a frequency having the maximum power for each of the second time intervals, and calculate the respiration rate using the frequency.

Specific matters for achieving the above objects will become apparent with reference to embodiments to be described later in detail together with the accompanying drawings.

However, the present invention is not limited to the embodiments disclosed below, but may be configured in various different forms, so that the disclosure of the present invention is complete and those of ordinary skill in the technical field to which the present invention belongs ( Hereinafter, it is provided in order to completely inform the scope of the invention to the "common engineer").

According to an embodiment of the present invention, it is possible to efficiently detect arousal state and respiration rate while solving physical constraints and user management needs.

In addition, according to an embodiment of the present invention, it can be used for a central sleep apnea test in which a patient has an abnormally low respiratory rate during sleep.

In addition, according to an embodiment of the present invention, it is possible to overcome the disadvantages of a wearable device in which a sensor must be directly worn during sleep, and to perform periodic and long-term sleep monitoring easily and conveniently.

The effects of the present invention are not limited to the above-described effects, and the potential effects expected by the technical features of the present invention will be clearly understood from the following description.

1A to 1C are diagrams illustrating a biosignal measuring apparatus according to an embodiment of the present invention.
2A to 2C are views showing a force sensor unit according to an embodiment of the present invention.
3 is a diagram showing a functional configuration of an analog front-end according to an embodiment of the present invention.
4 is a diagram showing a functional configuration of a data acquisition unit according to an embodiment of the present invention.
5 is a diagram illustrating a method of operating a bio-signal measuring apparatus according to an embodiment of the present invention.
6 is a diagram illustrating another method of operating a biosignal measuring apparatus according to an embodiment of the present invention.
7A to 7C are diagrams showing a graph of a preprocessing process according to an embodiment of the present invention.
8 is a diagram illustrating an awakening state detection graph according to an embodiment of the present invention.
9A and 9B are diagrams illustrating a respiration rate detection spectrogram according to an embodiment of the present invention.
10 is a diagram showing a respiratory rate detection graph according to an embodiment of the present invention.
11 is a diagram showing a comparison graph of detection of respiration rate according to an embodiment of the present invention.

In the present invention, various modifications may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and described in detail.

The various features of the invention disclosed in the claims may be better understood in view of the drawings and detailed description. The apparatus, method, preparation method, and various embodiments disclosed in the specification are provided for illustration purposes. The disclosed structural and functional features are intended to enable a person skilled in the art to specifically implement various embodiments, and are not intended to limit the scope of the invention. The disclosed terms and sentences are intended to describe various features of the disclosed invention in an easy to understand manner, and are not intended to limit the scope of the invention.

In describing the present invention, if it is determined that a detailed description of related known technologies may unnecessarily obscure the subject matter of the present invention, a detailed description thereof will be omitted.

Hereinafter, a method and apparatus for detecting arousal and respiration rate based on a force sensor according to an embodiment of the present invention will be described.

1A to 1C are diagrams illustrating a biosignal measuring apparatus 100 according to an embodiment of the present invention.

Referring to FIGS. 1A to 1C, the biosignal measuring apparatus 100 may include a force sensor unit 110, an analog front-end 120, and a data acquisition unit 130.

The force sensor unit 110 may measure a force (or pressure) signal according to a mechanical movement of a user's human body movement (eg, breathing). For example, the force signal can be measured at a sampling frequency of 1 kHz. In one embodiment, the force sensor unit 110 may be configured in a strip-type. As the force sensor unit 110 has a very thin and flexible characteristic, it may be configured so that there is almost no sense of foreignness when installed under the user's chest.

The analog front-end 120 may pre-process the force signal detected by the force sensor unit 110. In an embodiment, the analog front-end 120 may output and amplify the force signal detected by the force sensor unit 110 in the form of electric charge, and amplify a voltage corresponding to the amplified electric charge.

The data acquisition unit 130 may measure whether awakening and a respiration rate from a signal preprocessed by the analog front-end 120. In one embodiment, the data acquisition unit 130 may be designed in an assembly type with the analog front-end 120 for future expansion. Each of the analog front-end 120 and the data acquisition unit 130 may be configured to be detachably accommodated. That is, since the analog front-end 120 and the data acquisition unit 130 according to an embodiment of the present invention have a connector-separated structure, extensibility for configuring a multi-channel sensor may be facilitated.

In one embodiment, the bio-signal measuring apparatus 100 is installed between the bed mattress and the mattress cover and may be attached with an adhesive tape. In this case, the biosignal measuring apparatus 100 may be installed across the chest of the subject in order to measure a change in force caused by the subject's movement during sleep.

2A to 2C are views showing the force sensor unit 110 according to an embodiment of the present invention.

2A to 2C, the force sensor unit 110 may include an electrode unit 201 and an interface unit 203.

The electrode unit 201 may be manufactured in the form of a bipolar electrode using screen printing. In this case, the electrode unit 201 may include a conductive upper electrode and a conductive lower electrode so that patterns of the anodes configured at one end of the electrode unit 201 alternate with each other in consideration of capacitive noise.

In one embodiment, the electrode unit 201 is configured by packaging a bipolar electrode configured in a pattern that is alternated with each other with a two-channel sensor using a PET (polyethylene terephthalate) material, and a piezoelectric film is provided between the bipolar electrodes 903 Can be. For example, the electrode unit 201 may be packaged with a polymer material composed of any one of PET, PVC, PP, or PE. In this case, the packaging according to an embodiment of the present invention is not necessarily limited to two channels, and may be packaged with a plurality of channels other than two channels.

As the force sensor unit 110 has a very thin and flexible characteristic, it can be configured so that there is almost no sense of foreignness when installed under the user's chest, but it is difficult to manufacture a contact part for acquiring a signal from the sensor and easily becomes unstable. there is a problem. In order to solve this problem, the interface unit 203 may be configured using a ring terminal, an eyelet, and an insulating tape.

3 is a diagram showing a functional configuration of an analog front-end 120 according to an embodiment of the present invention.

Referring to FIG. 3, the analog front-end 120 may include a charge amplifier 301 and a voltage amplifier 301. For example, the gain of the analog front-end 120 may be 11. The analog front-end 120 may be designed to pre-process the signal measured by the force sensor unit 110. In one embodiment, the analog front-end 120 may further include a reference voltage generation circuit to measure a negative signal. For example, the voltage value of the _{negative signal V ref may be 670 mV.}

In an embodiment, the analog front-end 120 may have various resistor or capacitor values depending on the gain of the charge amplifier. In one embodiment, the analog front-end 120 may be referred to as a preprocessing circuit or a component that performs an equivalent function.

4 is a diagram showing a functional configuration of the data acquisition unit 130 according to an embodiment of the present invention.

Referring to FIG. 4, the data acquisition unit 130 includes a control unit 401, a battery 403, a real-time clock (RTC) 405, a communication unit 407, a USB interface unit 409, and a storage unit 411. ) Can be included.

The controller 401 may receive a 24-channel analog signal for low power operation. In an embodiment, the control unit 401 may include an analog-to-digital converter (ADC) 413 to convert a 24-channel analog signal into a digital signal. At this time, the ADC 413 may be composed of 14-bit, and is configured to input a 24-channel analog signal, but the ADC 413 of the present invention is not limited to 14-bit and can be extended, and channel input It is desirable to understand that N channels can be input in addition to 24 channels.

In an embodiment, the controller 401 may include at least one processor or a micro processor, or may be a part of a processor. Also, the control unit 401 may be referred to as a communication processor (CP). The controller 401 may control the overall operation of the biosignal measuring apparatus 100.

Since the data acquisition unit 130 has a battery 403 therein, it is possible to prevent the measurement of biosignal data from being stopped due to power loss. When the AC power is lost after being driven by an external AC power source normally It may be driven by power charged in the battery 403.

The data acquisition unit 130 is configured to obtain and transmit a bio-signal using the RTC 405 provided for signal acquisition, and is designed in consideration of reduction in circuit area and securing mechanical stability.

The biosignal obtained from the force sensor unit 110 may be transmitted to a remote location through a communication unit 407 or a USB interface unit 409 that provides wireless communication functions (eg, Bluetooth and Wi-Fi), and may be configured to be monitored. .

In an embodiment, the communication unit 407 may perform 1:N communication instead of 1:1 communication using only conventional Bluetooth as communication using Wi-Fi having a high bandwidth in addition to Bluetooth communication is possible.

The storage unit 411 may store at least one of a biosignal, arousal status, and respiration rate data acquired from the force sensor unit 110. The storage unit 411 may be composed of a volatile memory, a nonvolatile memory, or a combination of a volatile memory and a nonvolatile memory. In addition, the storage unit 411 may provide stored data according to the request of the control unit 401.

In FIG. 4, the data acquisition unit 130 includes a control unit 401, a battery 403, a real-time clock (RTC) 405, a communication unit 407, a USB port 409, and a storage unit 411. Although illustrated, in various embodiments of the present invention, the data acquisition unit 130 has more configurations than the configurations described in FIG. 4, or has fewer configurations, since the configurations described in FIG. 4 are not essential. Can be implemented as

5 is a diagram illustrating a method of operating the biosignal measuring apparatus 100 according to an embodiment of the present invention.

Referring to FIG. 5, step S501 is a step of performing filtering pre-processing on the force signal detected from the user's motion. In an embodiment, a force signal detected from a user movement may be applied to a notch filter, and a force signal to which the notch filter is applied may be applied to the first bandpass filter.

Step S503 is a step of calculating the awakening section by using the standard deviation of the force signal for each first time section. In one embodiment, the standard deviation of the force signal is calculated for each first time interval, the standard deviation of a Gaussian function corresponding to the standard deviation of each force signal is calculated, and a threshold value based on the standard deviation of the Gaussian function is calculated. You can decide.

If the standard deviation of the force signal is greater than the threshold value, a first time interval corresponding to the standard deviation of the force signal may be classified as the awakening interval. On the other hand, when the standard deviation of the force signal is less than the threshold value, the first time period corresponding to the standard deviation of the force signal may be classified as a sleep period.

Step S505 is a step of performing filtering post-processing on the force signal based on the awakening section. In one embodiment, the force signal is interpolated for the awakening period, the interpolated force signal is applied to the second bandpass filter, and the force signal to which the second bandpass filter is applied may be applied to the moving average filter. have.

Step S507 is a step of calculating a respiration rate using the maximum power spectral density of the force signal. In an embodiment, a frequency having a maximum power may be determined for each second time period, and a respiration rate may be calculated using the frequency. In an embodiment, the first time interval and the second time interval may mean time windows having different lengths.

6 is a diagram illustrating another method of operating the biosignal measuring apparatus 100 according to an embodiment of the present invention.

Referring to FIG. 6, a signal _strip may be detected from a user movement. For example, the detected force signal may have a waveform as shown in FIG. 7A.

Step S601 is a step of applying a second-order IIR notch filter to the force signal to remove 60Hz power line interference. For example, the force signal to which the second-order IIR notch filter is applied may have a waveform as shown in FIG. 7B.

Step S603 is a step of applying a third-order IIR bandpass filter (BPF) having a passband of 0.4-1 Hz to the force signal to which the second-order IIR notch filter is applied to improve the motion component. For example, a force signal to which a third-order IIR bandpass filter is applied may have a waveform as shown in FIG. 7C.

That is, the force signal detected from the user's motion may be noise removed and a motion component may be improved through the preprocessing of steps S601 to S603.

Step S605 is a step of iteratively calculating the standard deviation (SDsignal) of the force signal for each overlapped time window of 7 seconds.

Step S607 is a step of calculating a histogram of the standard deviation (SDsignal) of the force signal. In step S609, a Gaussian function is calculated using bins smaller than the maximum value of the histogram.

)에 기반하여 각성 상태를 분류하는 단계이다. 일 실시예에서, 시간 윈도우의 길이(예: 7초)와 임계값은 시스템 설정에 의해 결정될 수 있다. 여기서,

는 가우스 함수의 표준편차를 나타낸다. 예를 들어, 가우스 함수와 가우스 함수로부터 결정된 임계값(예: 5

)은 도 8과 같이 표현될 수 있다. Step S611 is the threshold of the positive side of the histogram (e.g. 5

This is the step of classifying the arousal state based on ). In one embodiment, the length of the time window (eg, 7 seconds) and the threshold value may be determined by system settings. here,

Represents the standard deviation of the Gaussian function. For example, a Gaussian function and a threshold determined from the Gaussian function (e.g. 5

) Can be expressed as shown in FIG. 8.

In an embodiment, as shown in Equation 1 _{below, when the SD signal} is greater than or equal to a threshold, the corresponding time window may be classified as an awake section (awake _{sampling time} = 1). . On the other hand, when the SD _signal is less than the threshold value, the corresponding time window can be classified as a sleep section (awake _{sampling time} = 0).

Here, the notation “sampling time” of the arousal state may mean a unit time for determining whether awakening or a unit time at which the force signal is sampled. For example,'sampling time' may be 5ms. In this case, '5ms' may mean that the force signal was sampled every 5ms because the force signal was recorded at a 1kHz sampling frequency, but it was downsampled to 200Hz to match the sampling frequency of the polysomnography (PSG) equipment.

In one embodiment, for comparison with PSG, awakening may be determined every 30 seconds. Here, 30 seconds may mean a reference epoch of sleep diagnosis of PSG. In this case, referring to the following <Equation 2>, the awakening determination result obtained previously for 30 seconds (awake _5ms = 1) is averaged, and if the result is 0.5 or more, the corresponding time window can be classified as an awakening interval. Yes (awake _30s =1). On the other hand, if the result is less than 0.5, the corresponding time window can be classified as a sleep period (awake _30s = 0). Here, N _30s means the total number of instances _{of awake 5ms} for 30 seconds.

Step S613 is a step of _{removing an awakening section (awake 5ms} = 1) including motion artifacts, and interpolating the removed section with respect to the force signal using neighboring data.

Step S615 is a step of applying a third-order IIR band pass filter having a pass band of 0.1 to 0.5 Hz to the interpolated force signal to extract the respiratory component.

In step S617, for smoothing, a moving average filter (MAF) is applied to a force signal to which a third-order IIR bandpass filter is applied for a time window of 2 seconds.

Step S619 is a step of calculating a spectrogram in which a time window of 120 seconds and an overlap of 60 seconds are set. This is because the spectrogram is useful for analyzing frequency components over time.

Step S621 is a step of determining a frequency having a maximum power spectral density for each time window, and calculating a respiration rate per minute using the frequency. Here, when the power expressed as a time function is converted into a frequency function through a Fourier transform through the power spectral density, the magnitude of the power for each frequency may be indicated.

In one embodiment, performance may be evaluated by comparing the biometric device according to the present invention and the PSG device. In this case, although the measurement using the biometric device and the PSG device according to the present invention was performed simultaneously, a difference in measurement timing between the two devices may occur.

Therefore, post-synchronization is required for accurate evaluation, and in order to compensate for the measurement timing difference, we calculate a time lag that maximizes the cross correlation, and Adjust the timing. In one embodiment, when time synchronization cannot be performed as described above, the timing difference may be manually corrected.

In one embodiment, the performance of the awakening state detection algorithm of the biosignal measuring apparatus 100 according to the present invention may be compared with a result of a previous study focusing on actigraphy as a conventional motion-based sleep monitoring method. In this case, the accuracy, sensitivity, specificity, and kappa coefficient of the awakening state detection algorithm of the biosignal measuring apparatus 100 according to the present invention may be 79.4%, 48.3%, 86.9%, and 0.6, respectively. In addition, the average sleep efficiency values were 82.3% and 84.0%, respectively, in the bio-signal measuring apparatus 100 and PSG according to the present invention, and the mean absolute error and the root mean square error were 12.9% and 17.7%, respectively.

Non-Patent Document 1 developed an arousal state detection algorithm based on actigraphy and compared it with PSG for 100 patients with sleep disorders. When compared with the results of Non-Patent Document 1, it can be seen that the average accuracy and average sensitivity of the biosignal measuring apparatus 100 according to the present invention are high. This means that the performance of the awakening state detection algorithm of the biosignal measuring apparatus 100 according to the present invention achieves a performance comparable to that of actigraphy.

9A and 9B are diagrams illustrating a respiration rate detection spectrogram according to an embodiment of the present invention.

Referring to FIG. 9A, the spectrogram and the respiration rate calculated by the biosignal measuring apparatus 100 according to the present invention can be checked. Referring to FIG. 9B, the spectrogram and respiration rate calculated by PSG can be confirmed. In this case, an abdominal breathing motion signal, which is one of the measured quantities of PSG, may be used as a reference breathing signal.

9A and 9B, it can be seen that the result of using the bio-signal measuring apparatus 100 according to the present invention to detect the respiration rate during sleep follows the same trend as the respiration rate measured by PSG.

10 is a diagram showing a respiratory rate detection graph according to an embodiment of the present invention.

_Referring to FIG. 10, RR strip is an average respiration rate calculated by the apparatus 100 for measuring a biological signal according to the present invention, and RR _PSG represents an average respiration rate of PSG. In this case, it can be confirmed that the result of using the biosignal measuring apparatus 100 according to the present invention to detect the respiration rate during sleep follows the same trend as the respiration rate measured by PSG.

11 is a diagram showing a comparison graph of detection of respiration rate according to an embodiment of the present invention.

_Referring to FIG. 11, RR strip is an average respiration rate calculated by the biosignal measuring apparatus 100 according to the present invention, RR _PSG is an average respiration rate of PSG, SD is a standard deviation, and bpm represents respiration per minute. A Bland-Altman plot indicating the difference between the respiration rate calculated by the biosignal measuring apparatus 100 according to the present invention and the respiration rate calculated by PSG can be confirmed. Looking at the Bland-Altman plot, it can be seen that most of the respiration rates detected by the bio-signal measuring apparatus 100 according to the present invention are within a 95% confidence interval.

In one embodiment, the accuracy of detecting the respiration rate of the biosignal measuring apparatus 100 according to the present invention may be expressed as shown in Table 1 below. That is, in each of the respiration rate detection errors of less than 1, 2, and 3 bpm, the accuracy may be 76.4%, 97.2%, and 99.4%.

Detection error accuracy(%)

1 bpm

1 bpm 76.4

2 bpm 97.2

3 bpm 99.4

The above description is merely illustrative of the technical idea of the present invention, and various changes and modifications may be made to those skilled in the art without departing from the essential characteristics of the present invention.

Accordingly, the embodiments disclosed in the present specification are not intended to limit the technical idea of the present invention, but are intended to be described, and the scope of the present invention is not limited by these embodiments.

The scope of protection of the present invention should be interpreted by the claims, and all technical ideas within the scope equivalent thereto should be understood as being included in the scope of the present invention.

100: bio-signal measuring device
110: force sensor unit
120: analog front-end
130: data acquisition unit
201: electrode part
203: interface unit
301: charge amplifier
303: voltage amplifier
401: control unit
403: battery
405: RTC
407: communication department
409: USB interface unit
411: storage unit
413: ADC

Claims (12)

Performing filtering pre-processing on the force signal detected from the user's motion by a control unit of the bio-signal measuring apparatus;
Calculating, by the control unit, an awakening section by using the standard deviation of the force signal for each first time section;
Removing, by the control unit, the arousal section including motion artifacts, and interpolating the removed section with respect to the force signal using neighboring data;
Applying, by the control unit, the interpolated force signal to a second bandpass filter;
Applying, by the control unit, a force signal to which the second band pass filter is applied to a moving average filter; And
Calculating, by the control unit, a respiration rate using the maximum power spectral density of the force signal for each second time interval;
Containing,
How to operate the bio-signal measuring device.
The method of claim 1,
The step of performing the filtering preprocessing,
Applying, by the control unit, a force signal detected from the user movement to a notch filter; And
Applying, by the control unit, a force signal to which the notch filter is applied to a first bandpass filter;
Containing,
How to operate the bio-signal measuring device.
The method of claim 1,
The step of calculating the awakening section,
Calculating, by the control unit, a standard deviation of the force signal for each of the first time intervals;
Calculating, by the control unit, a standard deviation of a Gaussian function corresponding to the standard deviation of each force signal;
Determining, by the control unit, a threshold value based on a standard deviation of the Gaussian function; And
Classifying, by the control unit, the first time section corresponding to the standard deviation of the force signal as the awakening section when the standard deviation of the force signal is greater than the threshold value;
Containing,
How to operate the bio-signal measuring device.
The method of claim 3,
The step of calculating the awakening section,
Classifying, by the control unit, the first time section corresponding to the standard deviation of the force signal as a sleep section when the standard deviation of the force signal is less than the threshold value;
Containing,
How to operate the bio-signal measuring device.
delete The method of claim 1,
The step of calculating the respiration rate,
Determining, by the control unit, a frequency having the maximum power for each second time period; And
Calculating the respiration rate using the frequency by the control unit;
Containing,
How to operate the bio-signal measuring device.
Perform filtering pre-processing on force signals from user movement,
The awakening section is calculated using the standard deviation of the force signal for each first time section,
The arousal section including motion artifact is removed, and the section removed for the force signal is interpolated using neighboring data,
Applying the interpolated force signal to a second bandpass filter,
Applying the force signal to which the second bandpass filter is applied to a moving average filter,
A control unit for calculating a respiration rate using the maximum power spectral density of the force signal for each second time interval;
Containing,
Bio-signal measurement device.
The method of claim 7,
The control unit,
Apply the force signal detected from the user movement to the notch filter,
Applying the force signal to which the notch filter is applied to the first bandpass filter,
Bio-signal measurement device.
The method of claim 7,
The control unit,
Calculate the standard deviation of the force signal for each of the first time intervals,
Calculate the standard deviation of the Gaussian function corresponding to the standard deviation of each force signal,
Determine a threshold value based on the standard deviation of the Gaussian function,
When the standard deviation of the force signal is greater than the threshold value, classifying the first time period corresponding to the standard deviation of the force signal as the awakening period,
Bio-signal measurement device.
The method of claim 9,
The control unit,
When the standard deviation of the force signal is less than the threshold value, classifying the first time period corresponding to the standard deviation of the force signal as a sleep period,
Bio-signal measurement device.
delete The method of claim 7,
The control unit,
Determining a frequency having the maximum power for each of the second time intervals,
Using the frequency to calculate the respiration rate,
Bio-signal measurement device.

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