JP2014023550A - Method and device for measuring respiration - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method and a device for measuring respiration by accurately extracting only a respiratory waveform in non-contact respiration measurement during a pedalling exercise in a bicycle.SOLUTION: A method for measuring respiration in a non-contact manner in which respiration of a person who operates a bicycle ergometer is measured by calculating a distance variation distribution in the chest and abdomen of the person comprises: a first step for dividing an area corresponding to the chest and abdomen of the person into a plurality of lattice areas; a second step for analyzing a frequency of a distance variation in each of the areas obtained by the division in the first step; a third step for calculating a main frequency in each of the areas from a result of the frequency analysis in the second step; a fourth step for extracting only a respiration main area in which a main frequency having been calculated in each of the areas in the third step is a respiration frequency; and a fifth step for calculating an average respiratory waveform in entire respiration main areas by extracting respiration waveforms through band pass filter processing of a respiration frequency band to a distance variation waveform in each of the respiration main areas obtained by the extraction in the fourth step.

Description

  The present invention relates to a respiration measurement method and apparatus for measuring respiration during pedaling exercise by a bicycle ergometer in a non-contact manner.

  The exercise load test is a physical fitness measurement / exercise that is performed in order to confirm physiological changes in the body from medical aspects such as heartbeat response, blood pressure, or electrocardiogram during exercise, and to perform exercise more safely and effectively. It is a capability measurement.

  As one of the indexes calculated in the exercise load test, an anaerobic work threshold (AT) is known. AT is used as a physical strength index for whole body endurance (stamina) as well as maximum oxygen intake, and can be calculated without exercising to the maximum, so health promotion and prevention / improvement of lifestyle-related diseases It is widely used as a measure of strength in exercise aimed at. The exercise intensity in the AT corresponds to an exercise intensity of about 50 to 60% of the maximum exercise, and is an exercise that can be performed without difficulty to the extent that it does not feel tight. Since there is no rapid increase in lactic acid in the blood, there is an advantage that exercise can be continued for a long time, shortness of breath does not occur, and the burden on the heart is small.

  Since this AT is a conceptual index, a ventilatory work threshold (VT) or a lactate work threshold (LT) is used as a more specific index (non-indicating). Patent Document 1)

In the exercise load test, the combined use of an exhalation gas analyzer can objectively measure systemic endurance, physical fitness limits, etc. non-invasively. In particular, the linear incremental load method (lamp load method) is considered to be an effective method for measuring VT that is effective in both safety and effectiveness. The ramp load method is generally performed using a bicycle ergometer, and advantages of the measurement by the ramp load method include that the intensity of exercise can be quantified and the load can be set finely.
VT is an exercise intensity that is a changing point for transition from a state where oxygen supply to the muscle is sufficient to a state where deficiency occurs, and this changing point appears as the following physiological phenomenon as the exercise load gradually increases. .
1) The increase in carbon dioxide emissions exceeds the increase in oxygen intake.
2) Increase rate of ventilation increases.

  The breath gas analyzer used in the VT calculation includes a measurement part composed of a flow meter, an oxygen concentration meter, and a carbon dioxide concentration meter, a calculation unit that calculates basic parameters such as VO2, VCO2, and VE from those measured values, It consists of an analysis unit for adding the heart rate, blood pressure, etc. to these data and displaying them on the monitor screen, or determining AT and the like. The Breath-by-breath method is widely used as a measurement mode using a combination of a gas analyzer and a flow meter. In the Breath-by-breath method, VO2 and VCO2 are obtained from the difference in gas concentration between exhaled air and inspired gas. In addition, a method called a mixing chamber method is known, but since the error is large in the non-steady state and the reliability of the measured value is extremely lowered, the Breath-by-breath method is suitable for the incremental load test. (Non-Patent Document 2).

However, since the breath gas analyzer is generally very expensive, it is currently used only in medical institutions and research institutions and cannot be used easily in sports clubs. At the time of measurement by the breath gas analyzer, it is necessary to wear a mask covering the mouth and nose, so it is difficult to say that breathing during exercise is in a natural state. In addition, the mask needs to be cleaned after the measurement is completed. For this reason, there is a drawback that it is difficult to carry out simple measurement with little sense of restraint.
One of the inventors of the present invention pays attention to the fact that VT appears as a point where the rate of increase in ventilation increases with the gradual increase in exercise load, and applied a non-contact respiration measurement method using image engineering technology. A calculation method is proposed (Non-patent Document 3). This non-contact respiration measurement method realizes non-contact respiration measurement by projecting on the chest and abdomen, photographing pattern light, and analyzing moving images, and was made by one of the inventors of the present invention. This is based on the non-contact respiratory measurement method shown in the invention (Patent Document 1).

  Non-Patent Document 3 reveals that non-contact respiration measurement during pedaling exercise by a recumbent bicycle ergometer can be realized, and further, it is shown that VT calculation can be performed with high accuracy. A VT calculation method to which the non-contact respiration measurement method shown in Non-Patent Document 3 is applied will be described below.

  10 and 11 show an outline of the system configuration. FIG. 10 shows a configuration when a recumbent bicycle ergometer is used, and FIG. 11 shows a configuration when an upright bicycle ergometer is used.

  In the system, the pattern light projection device 101 and the imaging device 102 are installed in front of the subject 104 who performs a pedaling motion with the bicycle ergometer 103. Then, the pattern light 105 is projected from the pattern light projector 101 onto the chest and abdomen of the subject 104. The pattern light is photographed by the imaging device 102 and taken into the image processing device 106 as a moving image. The subject's chest, abdomen, and base of the foot are photographed in the photographed image. The subject performs a pedaling exercise during the measurement.

  Based on the principle of triangulation, the coordinates of the pattern light in the image correspond to the coordinates on which the pattern light is projected in real space. That is, the distribution of pattern light in the image reflects the three-dimensional shape of the subject's thoracoabdominal region. This method can be said to be a kind of active stereo method in which a three-dimensional shape is restored by projecting pattern light and analyzing the distribution of the image.

The pattern light in the moving image periodically moves in the image as the distance between the chest and abdomen of the subject changes, that is, as the breath moves up and down. The direction in which the pattern light in the moving image moves is the direction connecting the pattern light projector and the imaging device. In the optical arrangement shown in FIG. 12, the following mathematical relationship is established between the vertical movement ΔZ of the thorax of the subject 121 and the movement amount ΔP of each pattern light 123 on the image sensor 122 (that is, in the image).
(1)

Here, L is the distance between the lens center 124 of the pattern light projector and the lens center 125 of the imaging device, Z is the distance between the portion 126 on which the pattern light is projected and the line segment L, and ΔZ is the pattern light projected. The variation distance delta P of the part 126 indicates the movement distance of the pattern light 123 in the image. Formula (1) is based on the principle of triangulation. Since Z >> ΔZ, it can be said that the movement distance of the pattern light 123 in the image is proportional to the magnitude of the movement of the portion 126 onto which the pattern light is projected, that is, the magnitude of the subject's movement.

  In order to measure respiration, first, the amount of movement of the pattern between frames is calculated. Then, the sum of the movement amount between frames of each pattern is calculated for all patterns. As described above, the amount of movement of the pattern between frames corresponds to a change in the distance between the body surface and the imaging device based on the principle of triangulation, and therefore the total amount of movement of the pattern between frames corresponds to a change in volume.

  In a state where the subject is still without pedaling (resting state), the movement that appears in the chest and abdomen is due to breathing. Therefore, a respiratory waveform can be obtained by arranging the total amount of movement of the pattern between frames in time series. The sign of the waveform indicates the state of breathing, and the sign is reversed between the expiration state and the inspiration state.

  As described above, since this method is a measurement method based on the principle of triangulation, the integrated value of the respiration waveform is an amount corresponding to the volume change of the thoracoabdominal region accompanying respiration. Each integrated value is defined as quasi-tidal volume (QTV). Since this QTV is based on the tidal volume TV which is the actual respiratory flow rate, the product of the QTV and the respiratory rate per minute can be considered to correspond to the minute ventilation (VE). Here, the product of QTV and the respiration rate per minute is referred to as quasi-minute ventilation (QVE). In this method, the exercise intensity corresponding to the point at which the increasing rate of QVE accompanying the increase in exercise intensity changes is calculated as VT.

  When the subject is pedaling, the chest and abdomen include movement due to pedaling in addition to movement due to breathing, so the waveform obtained by arranging the movement amount between frames in time series is a combination of breathing movement and pedaling movement It is a waveform. In the above QVE calculation, the pedal movement component becomes a noise component, so it is necessary to remove the pedal movement component.

  In this method, the pedal rotation speed of the subject's pedal pad is determined to be 60 rotations / minute (1 Hz), which is a pedal rotation speed generally used in exercise by a bicycle ergometer. By extracting the frequency component higher than the frequency (1 Hz) corresponding to the pedal rotation speed from the waveform calculated while the subject is pedaling, only the respiratory motion frequency component is extracted. To do. The respiratory motion component waveform extracted by the low-pass filter processing indicates the periodic fluctuation of respiration. In general, in a bicycle ergometer, the number of pedal rotations is managed by a metronome sound. However, since an error is actually included, a frequency component higher than the respiration frequency is cut.

  The thin line in the graph of FIG. 13 is a waveform actually measured when the exercise intensity is 100 to 140 W. By extracting a low frequency component of 0.916 Hz or less from this measured waveform, it is possible to extract only a respiratory motion component as shown by a thin line.

  FIG. 14 is a graph showing the QVE calculation result of the non-contact respiratory measurement method in the lamp load method. FIG. 14 (1) shows the results obtained using the recumbent bicycle ergometer, and FIG. 14 (2) shows the results obtained using the upright bicycle ergometer. As a result of simultaneous measurement, VE obtained by direct measurement by the breath gas analyzer is also shown. From this result, it can be seen that the changes in QVE and VE accompanying the gradual increase in exercise intensity coincide with each other as trends. That is, this result shows that the non-contact breath measurement method can capture the change in the expiratory volume accompanying the gradual increase of the exercise intensity as in the expiratory gas analyzer.

On the other hand, there is a partial difference between the two values, and it can be seen that the difference increases as the exercise intensity increases. In particular, in the upright bicycle ergometer, the degree of deviation is large. This was thought to be due to the fact that body motion increased with increasing exercise intensity, so that the body motion component was not accurately cut in the non-contact respiratory measurement technique.
For this reason, it was considered necessary to realize more accurate non-contact respiration measurement during exercise for accurate VT calculation.

Japanese Patent No. 3477166

Omiya Hitoshi: Myocardial infarction. Clinical Sports Medicine, 16 (7), pp. 763-769, 1999 Haruki Ito, Koichi Taniguchi: Anaerobic Threshold (AT), Cardiovascular load test method, Yasushi Mizuno, Fukuda City, Ed. 256-294, 1991 Hiroaki Aoki, Shiro Ichimura, Toyoki Fujiwara, Satoshi Kiyooka, Koji Koshiji, Takayuki Seo, Hidetoshi Nakamura, Hideo Fujimoto: Proposal of ventilatory work threshold calculation using non-contact respiratory measurement by pattern light projection, IEEJ Transactions C, Vol. 131-C, no. 1, pp. 152-159, 2011

  As described above, in the non-contact breathing measurement method during the pedaling exercise that has been studied so far, the body movement increases with the increase in exercise intensity, and the body movement component is not accurately cut, The problem that accurate respiratory measurement could not be carried out remained. For this reason, for accurate VT calculation, it is considered necessary to realize non-contact breath measurement during exercise more accurately.

  The problem to be solved by the present invention is to separate the pedaling motion and the respiration and accurately extract only the respiration waveform in the non-contact respiration measurement during the pedaling motion by the bicycle ergometer.

  The present invention has been made to solve the above-mentioned problems. First, a respiration measurement method for measuring respiration in a non-contact manner by calculating a distance fluctuation distribution of the chest and abdomen of a person driving a bicycle ergometer. A first step of dividing a region corresponding to the person's thoracoabdominal region into a plurality of lattice-shaped regions, and a second step of performing frequency analysis of distance variation of each region divided in the first step; A third step of calculating a main frequency of each region from the result of frequency analysis of the second step, and a respiratory main region in which the main frequency calculated in each region in the third step is a respiration frequency A fourth step of extracting only the respiratory waveform, and by performing bandpass filter processing of the respiratory frequency band on the distance fluctuation waveform in each respiratory main region extracted in the fourth step to extract the respiratory waveform It provides a respirometry method characterized by comprising a fifth step of calculating an average respiration waveform in key region.

  Secondly, the present invention is a respiration measurement device that measures the respiration in a non-contact manner by measuring a distance fluctuation distribution of the chest abdomen of a person who operates a bicycle ergometer. A distance distribution acquisition means for acquiring distribution information, a distance fluctuation distribution acquisition means for calculating a distance fluctuation distribution by time-differing the distance distribution acquired by the distance distribution acquisition means, and the distance fluctuation distribution acquisition means. A first step of dividing an area corresponding to the person's chest and abdomen in the acquired distance fluctuation distribution into a plurality of grid-like areas, and frequency analysis of distance fluctuation of each area divided in the first step The second step, the third step for calculating the main frequency of each region from the result of the frequency analysis of the second step, and the main frequency calculated in each region in the third step are the respiratory frequencies. A fourth step of extracting only a certain breathing main region, and a breathing waveform is extracted by performing a bandpass filter process of the breathing frequency band on the distance fluctuation waveform in each breathing main region extracted in the fourth step. And a respiratory waveform acquisition unit that acquires a respiratory waveform by executing a fifth step of calculating an average respiratory waveform in the entire respiratory main region.

  In the respiration measurement method that is the first problem solving means and the respiration measurement device that is the second problem solving means, only the region in which the distance fluctuation accompanying the respiration movement is the main component is used for calculating the respiration waveform. It has the effect of efficiently removing the influence of exercise and realizing accurate respiration measurement.

FIG. 1 is a flowchart showing each step of the respiration measurement method of the present invention. FIG. 2 is an explanatory diagram showing processing in the first step of the respiration measurement method of the present invention. FIG. 3 is an explanatory diagram showing the power spectrum obtained in the second step of the respiration measurement method of the present invention. FIG. 4 is an explanatory diagram showing the configuration of the respiratory measurement device of the present invention. FIG. 5 is a drawing substitute photograph showing distance distribution information acquired by the distance distribution acquisition means of the prototype system. Example 1 FIG. 6 is a drawing-substituting photograph showing the thoracoabdominal region divided into grid-like regions by the respiratory waveform acquisition means of the prototype system. Example 1 FIG. 7 is a drawing-substituting photograph showing a region where the main frequency is the pedaling / respiration frequency band. Example 1 FIG. 8 is a graph showing a respiratory waveform obtained by the prototype system. Example 1 FIG. 9 is a graph showing changes in QVE calculated from the respiratory waveform obtained by the prototype system. Example 1 FIG. 10 is an explanatory diagram showing the configuration of the prior art. FIG. 10 is an explanatory diagram showing the configuration of the prior art. FIG. 12 is an explanatory diagram showing the measurement principle of the prior art. FIG. 13 is a graph showing measurement results of the prior art. FIG. 13 is a graph showing measurement results of the prior art.

  The respiration measurement method of the present invention measures the respiration of a person driving a bicycle ergometer in a non-contact manner, and a process composed of five steps is performed as shown in FIG. The distance fluctuation distribution of the chest and abdomen of a person who drives the bicycle ergometer to be processed in the respiratory measurement method of the present invention is measured based on the active stereo method.

  First, in the first step, as shown in FIG. 2, a region 21 corresponding to a person's chest and abdomen is divided into a plurality of lattice-shaped regions 22. The number of divisions of the region 21 corresponding to the person's chest and abdomen or the lengths of the long sides / short sides of the plurality of lattice-like regions 22 are set as appropriate, but the length of one side of the lattice in real space is 5 cm or less is sufficient.

  Next, in the second step, frequency analysis is performed on the distance variation of each region divided in the first step. For frequency analysis, for example, fast Fourier transform is used. As a result of frequency analysis of each region, a power spectrum 31 as shown in FIG. 3 is obtained.

  In the third step, the main frequency in each region is calculated from the result of the frequency analysis in the second step. As shown in FIG. 3, in the power spectrum 31 calculated in each region, a peak 34 appears in the frequency band 32 of respiration and the frequency band 33 of pedaling motion. The frequency at which the size of the peak 34 is maximum can be considered as the main frequency in each region.

  In the fourth step, only the respiratory main region whose main frequency calculated in each region in the third step is the respiratory frequency is extracted. In the power spectrum 31 of FIG. 3, the region where the peak 34 appears in the respiration frequency band 32 is considered as a respiration main region in which respiration motion is dominant. In the fourth step, this region is defined as the main respiratory region and extracted from all regions.

    In the fifth step, only the respiratory waveform is extracted by performing the bandpass filter processing of the respiratory frequency band on the distance fluctuation waveform in each respiratory main region extracted in the fourth step. Then, the average of the respiratory waveform is obtained in the entire respiratory main region.

  Since this method is a measurement method based on the principle of triangulation, a value obtained by time-integrating a breath waveform for one breath or inspiration corresponds to a change in the distance between the chest and abdomen for one breath or one breath. Further, a value obtained by multiplying the value by the area of the main respiratory region corresponds to a change in the volume of the thoracoabdominal part for one breath or inspiration. Since this value is quasi-quantitatively equal to the tidal volume (TV), it is called quasi-tidal volume (QTV). Further, since the product of QTV and the respiration rate per minute is considered to be quasi-quantitatively equal to the minute ventilation (VE), it is called quasi-minute ventilation (QVE). QVE can be calculated as the product of QTV and respiratory rate per minute. Then, it is possible to calculate the human work ventilation threshold from the change in QVE.

  The respiration measurement device of the present invention measures a person's respiration in a non-contact manner by calculating a distance variation of the chest and abdomen of a person who operates a bicycle ergometer based on an active stereo method. As shown in FIG. 4, the respiratory measurement device of the present invention includes a distance distribution acquisition unit 41, a distance fluctuation distribution acquisition unit 42, and a respiratory waveform acquisition unit 43.

  In FIG. 4, the distance distribution acquisition means 41, the distance fluctuation distribution acquisition means 42, and the respiration waveform acquisition means 43 are shown as being provided in a part of the bicycle ergometer 44. The form of the measuring device is not limited to this. For example, a distance distribution acquisition means is provided in a bicycle ergometer to acquire distance distribution information, and the distance distribution information acquired by the distance distribution acquisition means is arranged at a position away from the bicycle ergometer using radio. Needless to say, the distance variation distribution acquisition means and the respiratory waveform acquisition means may be transmitted.

  In the distance distribution acquisition means 41, the distance distribution information of the thoracoabdominal part of the person 45 who drives the bicycle ergometer 44 is acquired based on the active stereo method. The distance distribution acquisition unit 41 includes a pattern light projection device 46 and an imaging device 47 for performing distance measurement by the active stereo method. The pattern light is projected onto the chest and abdomen of the person 45 from the pattern light projector 46, and the distribution of the pattern light imaged by the imaging device 46 is subjected to image analysis, so that the three-dimensional coordinates (imaging image) in the real space where the pattern light is projected It is possible to calculate the distance to the device.

In the distance fluctuation distribution acquisition means 42, the distance fluctuation distribution is calculated by subtracting the distance distribution acquired by the distance distribution acquisition means 41 in time series.
In the respiration waveform acquisition means 43, the respiration measurement method is executed. That is, the respiration waveform is calculated based on the following five steps.

  In the first step, an area corresponding to a person's chest / abdomen is divided into a plurality of grid-like areas in the distance fluctuation distribution acquired by the distance fluctuation distribution acquisition means. Next, in the second step, a frequency analysis is performed on the distance variation of each region divided in the first step. Next, in the third step, the main frequency in each region is calculated from the result of the frequency analysis in the second step. In the fourth step, only the breathing main region in which the main frequency calculated in each region in the third step is the breathing frequency is extracted. Finally, in the fifth step, a respiratory waveform is calculated by obtaining an average value of distance fluctuations in the main respiratory region extracted in the fourth step.

The calculated respiration waveform is used for QVE calculation as described above, and it is also possible to calculate the human work ventilation threshold (VT) from the change in QVE.
Needless to say, the present invention is not limited to the embodiment described above.

In order to verify the effectiveness of the present invention, a prototype system was developed. The following describes the respiratory measurement method of the present invention implemented in a prototype system.
FIG. 5 shows distance distribution information acquired by an active stereo sensor which is a distance distribution acquisition means of the prototype system. We obtained distance distribution information centered on the chest and abdomen of a person who performs pedaling exercises with an upright bicycle ergometer. And distance change distribution was acquired by performing the difference between frames of distance distribution information.

  FIG. 6 shows a result of dividing an area corresponding to a person's chest and abdomen into a plurality of grid-like areas. Then, frequency analysis was performed on the distance variation of each divided region, and the main frequency of each region was calculated from the result of frequency analysis.

  FIG. 7 shows a region where the main frequency in each region is a frequency range of pedaling motion and a region where it is a respiratory frequency band. Thus, it can be seen that the main frequency varies depending on the body part. The arms and legs are areas where pedaling movements appear significantly as distance fluctuations, and it is clear that distance fluctuations due to breathing movements are dominant in the chest wall and abdominal wall areas.

  Only the breathing main region whose main frequency is the breathing frequency is extracted, and the bandpass filter processing of the breathing frequency band is performed on the distance fluctuation waveform in each breathing main region. FIG. 8 shows a respiratory waveform obtained by averaging the waveform extracted by the bandpass filter processing in the entire main respiratory region. In addition, the test subject (person) used as measurement object is implementing the pedaling exercise by the ramp load method in which exercise intensity increases gradually at 30W / min.

  FIG. 9 shows the value of QVE obtained from the waveform. As a comparison result, a simultaneous measurement result using an expiratory gas analyzer which is a direct flow rate measuring means is shown. In addition, QVE calculated from a respiratory waveform (a method according to the aforementioned Non-Patent Document 3) obtained from the entire region corresponding to the thoracoabdominal region without extracting the main respiratory region is also shown. The vertical axis is normalized based on the average value of QVE for the first 30 seconds.

  From FIG. 9, the QVE calculated by the present invention is more consistent with the change trend of the QVE by the breath gas analyzer than the QVE calculated from the respiration waveform obtained from the entire region corresponding to the thoracoabdominal region. I understand. In addition, the QVE calculated from the respiratory waveform obtained from the entire region corresponding to the thoracoabdominal region may deviate from the QVE value obtained by the flow meter, but no deviation occurs in the QVE calculated according to the present invention. . Therefore, the usefulness of the respiration measurement according to the present invention was shown.

  The respiration measurement method and respiration measurement apparatus of the present invention realizes respiration measurement during pedaling exercise, which has been conventionally performed by an exhalation gas analyzer, in a non-contact and unconstrained manner. Since it does not require maintenance such as wearing a mask or cleaning, it can be expected to be implemented and used as a breathing measurement device for a simple exercise load test. Since it can be expected to be applied to the calculation of workability ventilation threshold, simple metabolic function measurement is realized. As a result, efficient exercise training can be implemented, which is expected to contribute to the promotion of national health.

21 Region corresponding to human chest 22 A plurality of lattice-shaped regions 31 Power spectrum 32 Respiration frequency band 33 Pedal motion frequency band 34 Peak 41 Distance distribution acquisition means 42 Distance fluctuation distribution acquisition means 43 Respiration waveform acquisition means 44 Bicycle ergometer 45 Driving person 46 Pattern light projection device 47 Imaging device 101 Pattern light projection device 102 Imaging device 103 Bicycle ergometer 104 Subject 105 Pattern light 106 Image processing device 121 Subject 122 Imaging element 123 Pattern light 124 Lens center of pattern light projection device 125 Lens center of the imaging device 126 Part where pattern light is projected

Claims (2)

In a respiration measurement method that measures the respiration in a non-contact manner by calculating the distance fluctuation distribution of the chest and abdomen of a person driving a bicycle ergometer,
Dividing the region corresponding to the person's chest and abdomen into a plurality of lattice-shaped regions;
A second step of performing frequency analysis on the distance variation of each region divided in the first step;
A third step of calculating a main frequency of each region from the result of the frequency analysis of the second step;
A fourth step of extracting only a respiratory main region in which the main frequency calculated in each region in the third step is a respiratory frequency;
A respiration waveform is extracted by performing a bandpass filter process of the respiration frequency band on the distance variation waveform in each respiration main region extracted in the fourth step, and an average respiration waveform in all respiration main regions is calculated. Steps,
A respiration measurement method comprising: A respiratory measurement device that measures the respiration in a non-contact manner by measuring the distance fluctuation distribution of the chest and abdomen of a person driving a bicycle ergometer,
Distance distribution acquisition means for acquiring distance distribution information of the chest and abdomen of the person;
Distance fluctuation distribution acquisition means for calculating the distance fluctuation distribution by subtracting the distance distribution acquired by the distance distribution acquisition means in time series; and
A first step of dividing a region corresponding to the person's thoracoabdominal region into a plurality of lattice-shaped regions in the distance variation distribution acquired by the distance variation distribution acquisition means; and each region divided in the first step A second step of frequency analysis of the distance variation of the first, a third step of calculating a main frequency of each region from the result of the frequency analysis of the second step, and a calculation within each region in the third step A fourth step of extracting only the breathing main region whose breathing frequency is the breathing frequency, and a bandpass filter processing of the breathing frequency band for the distance fluctuation waveform in each breathing main region extracted in the fourth step Respiration waveform acquisition means for acquiring a respiration waveform by executing a fifth step of extracting a respiration waveform and calculating an average respiration waveform in the entire respiration main region by performing,
A respiratory measurement device comprising: