KR101572179B1 - Method and system for measuring Resonance Frequency of Respiration and Apparatus for leading Resonance Respiration - Google Patents

Abstract

A method for detecting a respiratory resonance frequency and an apparatus for applying the method are disclosed.
A method for detecting a resonance frequency includes: presenting a plurality of visual stimuli to a user with different breathing conditions; Obtaining an ECG (electrocardiogram) signal responsive to the plurality of visual stimuli from the user; Extracting HRV (Heart Rate Variability) data having a plurality of peak powers in a predetermined frequency band from the ECG signal; Selecting a frequency representing the largest peak power from the HRV data as a resonance frequency for a user's optimum breathing; .

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and apparatus for measuring respiratory resonance frequency, and a respiratory apparatus using the same.

The present invention relates to a method of controlling blood pressure through respiratory resonance which is a characteristic of a user and a method of applying the same.

Considering the effect of respiration on the vital organs of the body, the importance of breathing to all life forms is not overestimated. However, the consciousness level is low. Through respiratory control, cases of various symptomatic symptoms have been reported. For example, pulmonary gas exchange, fibromyalgia, sympathetic and autonomic balance have been reported (Karavidas and Lehrer, 2006; Giardino, et al., 2003) Acharya et al., 2006). In addition, studies that have positive effects on major organs of living organisms have been reported, and studies on them have been greatly increased.

Respiration is an important factor in controlling the rhythm of the heartbeat, which affects blood pressure (Vaschillo, et al., 2006). This reflects that heart rhythm, blood pressure, and respiration interact with each other physiologically in the living body. Hypertension is a pain in life, which causes cramps, seizures, and even death. In addition, there is no way to cure hypertension, but there is only the technology to maintain the blood pressure level through medication. However, adverse drug reactions have been reported, and various efforts have been made to improve them.

AA Charya, U., Joseph, K., Kannathal, N., Lim, C., Suri, J. (2006). Heart Rate Variability: A Review. International Federation for Medical and Biological Engineering. Giardino, H., Glenny, R., Borson, W., Chan, L. (2003). Respiratory sinus arrhythmia is associated with efficiency of pulmonary gas exchange in healthy humans. American Journal of Physiology (Heart and Circulatory Physiology, 284), H1585-H1591. Karavidas, M., Lehrer, P. (2006). A pilot study of heart rate variability (HRV) Biological Psychology, 234-235. Pan, J., Tomplins, W. J. (1985) "A real-time QRS detection algorithm," Biomedical Engineering, IEEE Transactions on, vol. 32, no. 3, 230-236. Vaschillo, E. G., Vaschillo, B., Lehrer, P. M. (2006). Characteristics of Resonance in Heart Rate Variability Stimulated by Biofeedback. Applied Psychophysiology and Biofeedback, Vol. 31, No. 2, 129-142.

The present invention relates to a method for determining the respiratory characteristics of each living body, a method for obtaining a resonance frequency of respiration associated with the control of the blood pressure of each user or subject, and a method for inducing the blood pressure of the user to an appropriate range through resonance breathing And a system for applying the method.

Method for Determining Respiratory Resonance Frequency According to the Present Invention:

Presenting a plurality of visual stimuli to the user with different frequencies;

Obtaining an ECG (electrocardiogram) signal responsive to the plurality of visual stimuli from the user;

Extracting HRV (Heart Rate Variability) data having a plurality of peak powers in a predetermined frequency band from the ECG signal; And

Selecting a frequency representing the largest peak power from the HRV data as a resonance frequency for a user's optimal breathing; .

 The breath control apparatus according to the present invention comprises:

And a visual stimulus that induces a quick sucking according to the respiratory resonance frequency determined by the above method through a display device.

The respiration induction system according to the present invention performs the blood pressure control method;

A display device for presenting a visual stimulus to a user;

A biological signal detecting device for detecting an ECG signal from a user; And

An analysis system for extracting HRV data from the ECG signal and selecting a resonant frequency therefrom; Respectively.

The present invention provides a method for controlling blood pressure by visual stimulation. This method is based on extraction of the resonance frequency representing the user's own characteristics and visual stimulation synchronized with the resonance frequency. The present invention regulates an abnormal blood pressure to a normal blood pressure without depending on a drug or the like, and is highly utilized from the viewpoint of so-called U-healthcare based on information communication technology.

Figure 1 illustrates an interface screen displayed on the display for breathing guidance.
2 is a diagram for explaining the procedure of the experiment.
3 is a flowchart of HRV analysis according to the present invention.
Figure 4 illustrates the respiratory resonance frequency according to the HRV analysis.
Figure 5 compares systolic blood pressure at free breath and resonant respiratory conditions according to the present invention.
FIG. 6 shows a comparison of diastolic blood pressures under free breathing and resonance breathing conditions according to the present invention.
Figure 7 compares the normal range of systolic blood pressure under free breath and resonant respiratory conditions according to the present invention.
Figure 8 compares the normal range of diastolic blood pressure under free and respiratory respiratory conditions according to the present invention.
Figure 9 shows the algorithm of the system for respiratory resonance frequency and accordingly induction of breathing according to the present invention.
10 is a data processing flowchart in the algorithm according to the present invention.
Figure 11 shows a graphical user interface (GUI) in a training session in a real-time respiratory resonance frequency determination system used in an experiment of the present invention.
Figure 12 shows a GUI in a practice session in a real-time blood pressure control system.

The present invention basically requires an amplifier for detecting and amplifying the ECG signal, a digitizer for digitizing the amplified ECG signal, and an analysis system for analyzing the digitized ECG signal. The analysis system includes a computer-based hardware having an input device such as a keyboard and a mouse and a display for displaying the result, and a software system for performing an actual ECG signal analysis and the like.

The experimental (research) method of the present invention will be described first.

end. Subject

Eleven students (6 males, 5 females, mean age: 26.7 ± 3.24) participated in this study. All subjects had no abnormality or history of cardiovascular system and had enough sleep the day before. In addition, caffeine, smoking, and drinking, which may affect cardiovascular response, were prohibited on the day before the experiment. Before the experiment, all subjects participating in the experiment were explained about the experiment except for the purpose of the study, and then the experiment was carried out and a predetermined amount was paid for the experiment.

I. Experimental stimulus

As an experiment stimulus, a pump gauge image (interface screen) is presented through a display as shown in FIG. The pump gauge image is presented according to the number of breaths per minute, and it moves according to the time of inspiration and exhalation. A detailed description of the stimulus is shown in Figure 1. The respiratory conditions were 4.5, 5.0, 5.5, 6.0, and 6.5. The condition of respiration presented above means the number of breaths per minute. For example, a pump image of 4.5 breaths / min is given, and the total breathing time (including inspiration and exhalation) is 13.34 seconds. Accordingly, the presented pump image induces the subject to breathe for 6.67 seconds in the inhale and 6.67 seconds in the expiration. In the drawing, the right direction is the inspiration direction and the left direction is the expiration direction.

All. Experimental Method

Subjects participated in the experiment were presented with stimulation on a 40 "LED TV sitting on a comfortable chair.The subject was asked to perform six conditions of respiration as shown in Figure 2. Six breathing conditions (TASK-1 to TASK The rest of the stimulus presentation was done randomly and three minutes before and after the start of the stimulus presentation, and a rest (rest) After performing tasks corresponding to each respiratory condition, blood pressure was measured, and an ECG (Electro Cardio Gram) sensor was attached to measure the signal during the task, and each task was presented for 3 minutes. The rest of the minute was suggested.

la. Analysis method

The signal processing is performed along the flow as shown in FIG. HRV (Heart Rate Variability) was analyzed through ECG signal during task to identify respiratory resonance frequency of each subject. The ECG signal was sampled at 500 Hz through the lead-I method (S31). R-peaks were extracted from the ECG signal by a 'QRS detection algorithm' and R-RRI (R-peak to R-peak intervals) was calculated through the difference of normal R-peak intervals (S32) (Pan and Tomplins, RRI is required to convert to time-series data for FFT (Fast Fourier Transform) analysis, which is re-sampled at 2 Hz. (HRV) spectra obtained by FFT analysis are shown in Figure 4. Figure 4 shows HRV spectra obtained by FFT analysis, and HRV spectral results analyzed according to each breathing condition are compared, and the largest The respiration representing the peak was set to the respon- sion respiration frequency.

For the experiment of the present invention, the ECG signal was amplified through an ECG 100C amplifier (BIOPAC system Inc., USA), and the MP100 amplifier system (BIOPAC System Inc., USA) and NI-DAQ-Pad 9205 (National Instrument in USA). Blood pressure was measured using a HEM-780 (OMRON system Inc., Japan). All software for signal processing and analysis was used with acknowledge data acquisition and analysis software v4.1 (BIOPAC system Inc., USA) and labVIEW 2010 (National Instrument in USA).

In the following, experimental (research) results and analysis will be discussed.

Resonance respiration of each subject was compared with free condition breathing. Changes in blood pressure when respiration was performed with systolic and diastolic blood pressure and respiratory resonance frequency before and after free breathing were statistically compared and statistical techniques were used by T-test. Statistical analysis program was SPSS v17.0.

end. Resonance Respiration

The respiratory resonance frequency of each individual was confirmed by HRV spectrum analysis according to the respiratory conditions (TASK-1 ~ 6) of each subject, and the results are shown in Table 1. In the HRV spectrum analysis of each respiratory condition, the power value of the frequency showing the largest peak was derived and the respiratory resonance frequency was selected by comparing it with other respiratory conditions. Experiments have shown that respiration (resonance breathing) in synchronization with the resonance frequency can lower or stabilize the user's blood pressure.

I. Blood Pressure

Table 2 shows the blood pressure measurements before and after breathing (free respiration) and before and after the respiration (resonance breathing) at resonance frequency.

The results of the comparison of systolic blood pressure according to free breathing and resonance breathing are shown in FIG. The systolic blood pressures before and after free breathing did not show any significant difference, but the systolic blood pressures before and after resonance respiration were significantly decreased after resonance breathing and stabilized. In addition, a statistically significant difference was observed between the two breaths ( t = 3.196, p = .005).

< t = 3.196, p = .005 -> Need to explain what it means>

The results of the comparison of diastolic blood pressure according to free breathing and resonance breathing are shown in FIG. As a result, there was no significant difference in systolic blood pressure before and after free breathing, but systolic blood pressure before and after resonance breathing decreased significantly after respiration. In addition, a statistically significant difference was found between the two breaths ( t = 2.864, p = .014).

Another important result is that when respiration is performed at the resonance frequency, not only the blood pressure is reduced, but also most subjects experience normal blood pressure recovery in both systolic and diastolic blood pressures. FIGS. 7 and 8 show the results of comparing the normal range of the systolic blood pressure of the free and the resonance condition with the normal range of the diastolic blood pressure.

Hereinafter, embodiments of a real-time blood pressure control method and system using a resonance frequency will be described in detail. The result of the experiment (study) according to the present invention shows that the systolic and diastolic blood pressure is adjusted to the normal blood pressure range when the respiratory resonance frequency of the individual is extracted through HRV analysis and respiration is performed through the HRV analysis. Based on the above experimental results, the present invention proposes a method and system capable of adjusting an individual's blood pressure in real time through a resonance frequency.

The system proposed in the present invention, that is, the blood pressure control apparatus and method, is divided into a training session and a test session as shown in FIG. In the training session, the respiratory resonance frequency suitable for the user is detected. Specifically, the following five steps are followed.

1. Sensor Attachment: Attaches the ECG signal to the user as Lead-I type and acquires the signal.

2. Respiration Task: Respiration is performed according to the presented respiratory cycle. The conditions of the respiratory cycle are given as Free, 4.5, 5.0, 5.5, 6.0, 6.5.

3. Data Analysis: Calculate the HRV spectrum by analyzing the acquired ECG signal for each breathing cycle.

4. Compare Data: Compares the dominant peak value of the analyzed HRV spectrum according to each breathing cycle.

5. Detecting Resonance Frequency: Select the respiratory cycle with the highest peak value as the respiratory resonance frequency.

 In the experimental session (Test Session), a guide for breathing is provided so that the user can breathe at the detected respiratory resonance frequency. The following three steps are followed.

1. Respiration using resonance frequency: Provides a breathing guide through the pump image so that you can breathe in the detected respiratory resonance frequency band.

2. Verification: Verify the autonomic balance (VLF / HF ratio) and blood pressure using the ECG signal measured in real time.

3. Compare: feedback to maintain respiration until autonomic nervousness ratio and blood pressure return to normal range. 9 is described above. A data analysis of a training session and a verification of a test session are shown. On the other hand, the processing of the above data analysis is shown in detail in FIG.

Referring to FIG. 10, a data analysis process is as follows.

S11: The ECG signal of the user is sampled (extracted) at 500 Hz.

S12: The R-peak is extracted from the ECG data (signal) through the QRS detection algorithm and the R-RI (R-peak to R-peak intervals) is calculated.

S13: RRI is sampled at 2 Hz and converted to time-series data.

S14, S15: Time-series data is FFT-analyzed from 0.0033 Hz to very low frequency to high frequency band, from which HRV spectra from 0.0033 Hz to 0.4 Hz are extracted.

S16: A dominant peak is selected as the resonance frequency from the HRV spectrum.

11 shows a graphical user interface (GUI) in a training session in a real-time blood pressure control system used in an experiment of the present invention, and Fig. 12 shows a GUI in a practice session in a real-time blood pressure control system.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the scope of the present invention. Therefore, the true scope of protection of the present invention should be defined only by the appended claims.

Claims (10)

Presenting a plurality of visual stimuli to the user with different breathing conditions;
Obtaining an ECG (electrocardiogram) signal responsive to the plurality of visual stimuli from the user;
The R-peak is detected through the QRS detection algorithm in the ECG signal, the R-RI (R-peak to R-peak intervals) is calculated through the difference between the R peaks, and a plurality of peak powers Extracting heart rate variability (HRV) data having peak power; And
Selecting a frequency representing the largest peak power from the HRV data as a resonance frequency for a user's optimal breathing; / RTI &gt; The method according to claim 1,
Wherein the visual stimulus is presented with a certain resting time when the respiratory condition presents another visual stimulus. 3. The method according to claim 1 or 2,
Wherein the respiratory conditions include different respiratory frequencies. delete Wherein the visual stimulation according to the respiratory resonance frequency determined by the method according to claim 1 or 2 is presented through the display device. 6. The method of claim 5,
Wherein the respiratory conditions include different respiratory frequencies. delete An apparatus for carrying out the method according to claim 1 or 2,
A display device for presenting a visual stimulus to a user;
A biological signal detecting device for detecting an ECG signal from the user; And
An analysis system for extracting HRV data from the ECG signal and selecting a resonant frequency therefrom; And a respiratory resonance frequency measuring device. 9. The method of claim 8,
Wherein the visual stimulus is presented with a certain resting time when the breathing condition presents another visual stimulus. delete

Images