JP6432970B2 - Respiration monitoring apparatus and respiration monitoring method - Google Patents

Description

  The present invention relates to a respiratory monitoring device that monitors the breathing of a subject.

  Conventionally, oxygen therapy is known in which oxygen is supplied to a patient with respiratory disease using an oxygen supply device such as an oxygen concentrator (for example, Patent Document 1). In particular, Home Oxygen Therapy (HOT), which can install oxygen at home and supply oxygen to patients while at home, is useful for improving the prognosis of patients with chronic respiratory failure. ing.

Japanese Patent No. 4416251

  In particular, oxygen therapy is important for patients with chronic obstructive pulmonary disease (COPD), which is common in smokers. Factors affecting the life prognosis of patients with COPD are diverse, but the degree of dyspnea, in particular, reduces activities of daily living (ADL) and quality of life (QOL), It is one of the important life prognostic determinants because it significantly restricts life.

  However, the degree of dyspnea may be different from the conventional respiratory dynamics index, which is a COPD severity index, and it is difficult to objectively evaluate and predict dyspnea. The inventors have clarified through experiments that the disorder of resting breathing during arousal is significantly related to the index of dyspnea in COPD patients. That is, respiratory irregularity reflects a feeling of dyspnea, suggesting that respiratory irregularity can predict the prognosis of chronic COPD patients.

  Therefore, if non-invasive continuous monitoring of respiratory waveforms of COPD patients with chronic respiratory failure who are undergoing HOT and the respiratory dynamics of subjects such as sequential respiratory irregularities can be evaluated, COPD acute hatred and life prognosis can be predicted. It will be possible.

  The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to propose a new technique for correctly evaluating a subject's disease state / pathology and respiratory dynamics.

The first invention for solving the above problems is:
Acquisition means (for example, the pressure sensor 10 of FIG. 2) that acquires a respiration waveform that is time-series data of the respiration of the subject including supplied oxygen supplied to the subject from an oxygen supply (for example, the oxygen concentrator 3 in FIG. 1). )When,
Based on the acquisition result of the acquisition means, an estimation means (for example, the offset estimation unit 31 in FIG. 2) that estimates an error component that fluctuates with time and is superimposed on the respiratory waveform when oxygen is supplied from the oxygen supplier. )When,
Using the estimation result of the estimation means, calculation means for calculating an error compensated respiratory waveform that is time series data of respiration in which the error component superimposed on the respiratory waveform is compensated (for example, the error compensated respiratory waveform of FIG. Calculation unit 32),
Based on the error-compensated respiratory waveform calculated by the calculation means, calculation means for calculating the respiratory dynamic index value of the subject (for example, the respiratory dynamic index value calculation unit 33 in FIG. 2);
A respiratory monitoring device (for example, the respiratory monitoring device 1 of FIGS. 1, 2, and 8).

As another invention,
Obtaining a respiratory waveform that is time-series data of the subject's breathing including oxygen supplied to the subject from an oxygen concentrator (eg, step A1 in FIG. 3);
Based on the result of the acquisition, estimating an error component that fluctuates with time when oxygen is supplied by the oxygen supply device and is superimposed on the respiratory waveform (for example, step A7 in FIG. 3);
Calculating an error-compensated respiration waveform that is time-series data of respiration compensated for the error component superimposed on the respiration waveform using the estimation result (for example, step A9 in FIG. 3);
Calculating a respiratory dynamic index value of the subject based on the calculated error-compensated respiratory waveform (for example, step B5 in FIG. 4);
It is good also as comprising the respiratory monitoring method containing these.

  According to this 1st invention etc., the respiration waveform which is the time series data of the said test subject's respiration including the supply oxygen supplied to a test subject is acquired. However, when oxygen is supplied to the subject by the oxygen supply device, various error components can be superimposed on the respiration waveform due to the physical configuration and design of the oxygen concentrator. Specifically, error components such as an error component caused by fluctuations in the discharge pressure of the oxygen supply device and an error component caused by a change in the setting of the flow rate of oxygen supplied from the oxygen supply device can be superimposed on the respiratory waveform. Therefore, using the acquired respiratory waveform, an error component that varies with time when oxygen is supplied from the oxygen supply device and is superimposed on the respiratory waveform is estimated. Then, using this estimation result, an error-compensated respiration waveform, which is time-series data of respiration in which the error component superimposed on the respiration waveform is compensated, is calculated. Thereby, the respiration information (breathing pattern) reflecting the correct breathing state of the subject can be obtained.

  Also, the respiratory dynamic index value of the subject is calculated based on the calculated error compensated respiratory waveform. Here, the respiratory dynamic index value includes an index value such as a respiratory fluctuation coefficient of a tidal volume (including an inspiratory tidal volume and an exhaled tidal volume) and a respiratory fluctuation coefficient of a minute ventilation. Correctly evaluate the patient's condition / pathology and respiratory dynamics by calculating the error compensated respiratory waveform with the error component compensated from the respiratory waveform and calculating the respiratory dynamic index value of the subject based on the error compensated respiratory waveform. Is possible.

As a second invention, the respiratory monitoring device of the first invention,
The acquisition means includes pressure detection means (for example, the pressure sensor 10 in FIG. 2),
The pressure detection means detects a change in the respiratory pressure of the subject as the respiratory waveform,
The estimation means estimates the error component including a drift component of the pressure detection means based on a change in respiratory pressure detected by the pressure detection means;
A respiratory monitoring device may be configured.

  According to the second aspect of the invention, the change in the respiratory pressure of the subject can be easily acquired as a respiratory waveform by using the pressure detection means. When detecting a change in respiratory pressure using the pressure detection means, a drift component can be superimposed on the detected change in respiratory pressure due to the characteristics of the pressure detection means. Here, the drift component includes, for example, a temperature drift due to the temperature characteristics of the pressure detecting means and a time-dependent drift that changes with time. Therefore, the error component including these drift components is estimated based on the change in the respiratory pressure detected by the pressure detection means. By using this estimated error component, it is possible to obtain an error compensated respiratory waveform in which the error component due to the characteristics of the pressure detecting means is compensated.

Moreover, as 3rd invention, it is the respiration monitoring apparatus of 2nd invention,
The oxygen supply is supplied to the subject via a nostril cannula (eg, nostril cannula 5 in FIG. 1),
The pressure detection means is configured to detect a change in the respiratory pressure by conducting to the nostril cannula,
The estimating means estimates the error component including a back pressure fluctuation component of the nostril cannula;
A respiratory monitoring device may be configured.

  According to the third aspect of the invention, oxygen is supplied from the oxygen supply device to the subject through the nostril cannula. However, since the pressure detection means is connected to the nostril cannula, the respiratory pressure of the subject through the nostril cannula Can be detected as a respiratory waveform. When a change in the respiratory pressure of the subject is detected via the nostril cannula, an error component due to the shape of the nostril cannula or the wearing state can be superimposed on the respiratory pressure. Specifically, for example, a back pressure fluctuation component caused by bending of the nostril cannula, and a back pressure fluctuation component caused by deviation of the wearing mode and the wearing position when the subject wears the nostril cannula are included. Therefore, the estimation means estimates an error component including a back pressure fluctuation component of the nostril cannula based on the change in the respiratory pressure detected by the pressure detection means. By using the estimated error component, it is possible to obtain an error compensated respiratory waveform in which the error component due to the characteristics of the nostril cannula is compensated.

Further, as a fourth invention, the respiratory monitoring device according to any one of the first to third inventions,
Evaluation means for evaluating the respiratory dynamics of the subject based on the respiratory dynamic index value calculated by the calculation means (for example, the respiratory dynamic evaluation unit 35 in FIG. 2);
Notification means (for example, at least one of the display 50, the lamp 55, and the speaker 60 in FIG. 2) that performs predetermined notification based on the result of evaluation by the evaluation means;
Further comprising
A respiratory monitoring device may be configured.

  According to the fourth aspect of the invention, the evaluation unit evaluates the respiratory dynamics of the subject based on the respiratory dynamic index value calculated by the calculation unit, and the notification unit performs the predetermined notification based on the evaluation result by the evaluation unit. I do. For this reason, the test subject can know the evaluation about his / her respiratory dynamics and can easily grasp the test subject's disease state and condition.

Further, as a fifth invention, the respiratory monitoring device of the fourth invention,
The calculation means calculates the respiratory variation coefficient of the subject as the respiratory dynamic index value (for example, step B5 in FIG. 4),
The evaluation means evaluates the respiratory dynamics of the subject based on the respiratory variation coefficient (for example, steps B7 to B9 in FIG. 4),
A respiratory monitoring device may be configured.

  According to the fifth aspect of the invention, the calculating means calculates the respiratory fluctuation coefficient of the subject as a respiratory dynamic index value, and the evaluating means evaluates the respiratory dynamics of the subject based on the respiratory fluctuation coefficient. Here, the respiratory variation coefficient is an index value indicating the degree of variation of the subject's respiration, and is defined as, for example, a variation coefficient of tidal volume. Based on this respiratory variation coefficient, it is possible to accurately evaluate the respiratory dynamics of the subject.

Further, as a sixth invention, the respiratory monitoring device of the fifth invention,
The calculating means calculates a respiratory variation coefficient related to the subject's ventilation (tidal volume (including inspiratory tidal volume and exhaled tidal volume) and minute ventilation) as the respiratory dynamic index value. (For example, step B5 in FIG. 4)
A respiratory monitoring device may be configured.

  According to the sixth aspect of the invention, the calculating means can appropriately detect acute exacerbation by calculating the respiratory variation coefficient related to the subject's ventilation as the respiratory dynamic index value.

As a seventh invention, the respiratory monitoring device of the fifth or sixth invention,
The evaluation means determines whether or not the respiratory variation coefficient satisfies a predetermined high threshold condition (for example, step B7 in FIG. 4), and when the determination result is affirmative determination (for example, in FIG. 4). Step B7; Yes) and evaluate that the subject is in a state of difficulty breathing (for example, Step B9 in FIG. 4),
When the evaluation means evaluates that the subject is in a dyspnea state (for example, step A15 in FIG. 3), the notification means notifies the subject (for example, step A17 in FIG. 3). ),
A respiratory monitoring device may be configured.

  The knowledge based on the results of prior research conducted by the inventors of the present application has revealed that when the respiratory variation coefficient reaches a certain level, it may be considered that the subject is in a difficult breathing state. Therefore, according to the seventh invention, the evaluation means determines whether or not the respiratory variation coefficient satisfies a predetermined high threshold condition, and when the determination result is affirmative determination, the subject is in a state of difficulty in breathing It is evaluated that it is in. Then, when the evaluation means evaluates that the subject is in a difficult breathing state, the notification means notifies the subject to that effect. Thereby, after evaluating appropriately whether a subject is in the state of dyspnea, when evaluating that it is in the state of dyspnea, it can alert | report to that subject.

Moreover, as an eighth invention, the respiratory monitoring device according to any one of the first to seventh inventions,
The estimation means estimates the error component by performing a predetermined error estimation process using respiration data of the respiration waveform for a predetermined period with reference to one reference timing of the respiration waveform (for example, FIG. 3). Step A7, Steps C11 to C15 in FIG. 6),
A respiratory monitoring device may be configured.

  According to the eighth aspect of the invention, the estimation means performs the predetermined error estimation process using the respiration data of the respiration waveform for a predetermined period with reference to one reference timing of the respiration waveform, so that the error component is correctly corrected. Can be estimated.

More specifically, as in the ninth invention, the respiratory monitoring device of the eighth invention,
The error estimation process includes a process of averaging the respiration data for a predetermined period retroactive from the reference timing (for example, step A7 in FIG. 3),
It is preferable to configure a respiratory monitoring device.

  According to the ninth aspect of the present invention, the error component can be correctly estimated by performing the process of averaging the respiration data for a predetermined period going back from the reference timing. As the average calculation in this case, for example, a moving average calculation can be applied.

Further, instead of the ninth invention, as in the tenth invention, the respiratory monitoring device of the eighth invention,
The error estimation process includes a process of performing integral approximation on the respiration data for a predetermined period retroactive from the reference timing (for example, step C11 in FIG. 6).
It is also possible to configure a respiratory monitoring device.

  According to the tenth aspect of the present invention, the error component can be correctly estimated by performing the integral approximation calculation of the respiration data for a predetermined period retroactive from the reference timing.

Further, instead of the ninth invention, as in the eleventh invention, the respiratory monitoring device of the eighth invention,
The error estimation process includes:
A first integral approximation calculation process (for example, step C11 in FIG. 6) for integrating and calculating the respiration data for a first predetermined period retroactive from the reference timing, and a second predetermined period after the reference timing. A second integral approximation calculation process (for example, step C13 in FIG. 6) for integrating and calculating the respiration data;
And the error component is estimated using the result of the first integral approximation calculation process and the result of the second integral approximation calculation process (for example, step C15 in FIG. 6).
It is also possible to configure a respiratory monitoring device.

  According to the eleventh aspect of the invention, the first integral calculation process for performing integral approximation on the respiratory data for the first predetermined period that goes back from the reference timing is performed. In addition, a second integral approximation calculation process is performed in which the integral approximation calculation is performed on the respiration data for the second predetermined period after the reference timing. Then, the error component is estimated using the result of the first integral approximation calculation process and the result of the second integral approximation calculation process. By integrating and approximating the respiration data of the respiration waveform for a predetermined period before and after the reference timing, and using these results, the accuracy of the error component estimation can be further improved.

The twelfth invention is the respiratory monitoring device of the ninth or tenth invention,
Reference timing setting means for setting and updating the reference timing in real time (for example, a reference timing setting unit 39 in FIG. 2) is further provided.
A respiratory monitoring device may be configured.

  According to the twelfth aspect, since the reference timing setting means updates and sets the reference timing in real time, it is possible to estimate the error component in real time and calculate an appropriate error compensated respiratory waveform as needed.

The thirteenth invention is the respiratory monitoring device of any of the ninth to twelfth inventions,
Determination means for determining a waveform portion showing a similar change tendency from the respiratory waveform;
A period setting means for variably setting the predetermined period based on the waveform portion determined by the determination means;
Further comprising
A respiratory monitoring device may be configured.

  Since the flow rate of oxygen supplied from the oxygen supply device is not necessarily constant and can change with time, it is assumed that the shape of the respiratory waveform changes at any time. Therefore, according to the thirteenth aspect, the determining means determines a waveform portion showing a similar change tendency from the respiratory waveform. Then, the period setting means variably sets the predetermined period used for estimation of the error component based on the waveform portion determined by the determination means. This makes it possible to correctly estimate the error component regardless of the change in the flow rate of the supplied oxygen.

The figure which shows an example of the system configuration | structure of a respiration monitoring system. The figure which shows an example of a function structure of a respiration monitoring apparatus. The flowchart which shows the flow of a respiration analysis process. The flowchart which shows the flow of a respiratory dynamics evaluation process. (1) The figure which shows an example of the actual detection result of a respiration waveform. (2) The figure which shows an example of the actual calculation result of an error compensation respiratory waveform. The flowchart which shows the flow of a 2nd respiration analysis process. (1) The figure which shows an example of the actual detection result of a respiration waveform. (2) The figure which shows an example of the actual calculation result of an approximate straight line. (3) The figure which shows an example of the actual calculation result of an error compensation respiratory waveform. The figure which shows the structural example of the nostril cannula in a modification.

  Hereinafter, an example of a preferred embodiment to which the present invention is applied will be described with reference to the drawings. However, it is needless to say that embodiments to which the present invention is applicable are not limited to the embodiments described below.

1. System Configuration FIG. 1 is a diagram illustrating an example of a system configuration of a respiratory monitoring system 100 in the present embodiment. The respiratory monitoring system 100 includes a respiratory monitoring device 1, an oxygen concentrator 3, and a nostril cannula 5.

  The respiratory monitoring apparatus 1 is an apparatus that evaluates the respiratory dynamics of a subject by monitoring the subject's breathing and analyzing the respiratory pattern of the subject. It can also be called a respiratory analysis device or a respiratory pattern analysis device. Further, according to the knowledge of the present inventor, it has been clarified that irregular breathing is considered to contribute to the subject's dyspnea feeling and prognosis. For this reason, it can be said that the respiratory monitoring device 1 is a respiratory irregularity analysis device that analyzes a subject's respiratory irregularity.

  The respiration monitoring apparatus 1 detects and acquires a respiration waveform, which is a change in the respiration pressure of the subject including oxygen supplied and noise components supplied from the oxygen concentrator 3 to the subject using the pressure sensor 10. And based on the change of the respiratory pressure detected by the said pressure sensor 10, the offset superimposed on a respiration waveform is estimated. Then, using the estimated offset, an error compensated respiratory waveform in which the offset superimposed on the respiratory waveform is compensated is calculated. Then, the respiratory dynamic index value of the subject is calculated based on the calculated error compensated respiratory waveform, and the respiratory dynamics of the subject is evaluated based on the respiratory dynamic index value. Details will be described later.

  The oxygen concentrator 3 is a supply device that supplies concentrated oxygen to a subject, and is a kind of oxygen supply device. As this oxygen concentrator, for example, a known oxygen concentrator such as an adsorption type oxygen concentrator using an adsorbent that selectively adsorbs oxygen or a membrane type oxygen concentrator using an oxygen selective permeable membrane can be applied. is there.

  The nostril cannula 5 is a thin tube that is attached to the nasal cavity of the subject and feeds oxygen from the oxygen concentrator 3. In this embodiment, the oxygen supply tube 5a that conducts oxygen from the oxygen concentrator 3 to the subject's nasal cavity and the subject's nasal cavity branched from the oxygen supply tube 5a conducts to the respiratory monitoring device 1 and breathes the subject. It has two tubes including a respiratory pressure detection tube 5b for detecting pressure.

  The concentrated oxygen generated by the oxygen concentrator 3 is configured to flow into the nasal cavity of the subject through the oxygen supply tube 5a. Further, the breathing of the subject flows into the pressure sensor 10 of the respiratory monitoring device 1 through the breathing pressure detection tube 5b, and the breathing pressure of the subject is detected by the pressure sensor 10.

  In place of the nostril cannula 5 shown in FIG. 1, a dual lumen cannula may be applied. Dual lumen cannula is also called double lumen cannula. Specifically, as shown in FIG. 8, an oxygen supply tube 5 a that supplies oxygen from the oxygen concentrator 3 to the subject's nasal cavity, and a breathing device of the subject that conducts from the nasal cavity of the subject to the respiratory monitoring device 1. A dual lumen cannula configured with two tubes, a respiratory pressure detection tube 5c for detecting pressure, is configured as a nostril cannula 5.

  In this case, the concentrated oxygen generated by the oxygen concentrator 3 flows into the nasal cavity of the subject through the oxygen supply tube 5a. Further, the breathing of the subject flows into the pressure sensor 10 of the respiratory monitoring device 1 via the breathing pressure detection tube 5c, and the breathing pressure of the subject is detected by the pressure sensor 10.

2. Functional Configuration FIG. 2 is a diagram illustrating an example of a functional configuration of the respiratory monitoring device 1.
The respiratory monitoring device 1 includes a pressure sensor 10, an A / D (Analog Digital) converter 20, a CPU (Central Processing Unit) 30, an operation key 40, a display 50, a lamp 55, a speaker 60, and a ROM. (Read Only Memory) 80 and RAM (Random Access Memory) 90 are provided.

  The pressure sensor 10 is a sensor that detects the pressure due to breathing of the subject that has flowed from the respiratory pressure detection tube 5b. A change in respiration pressure flowing through the respiration pressure detection tube 5b is converted into an electrical signal (analog signal) by an internal pressure-sensitive element and output to the A / D converter 20 as a respiration waveform. As the pressure sensor 10, a silicon diaphragm type or a stainless diaphragm type pressure sensor can be applied. In the present embodiment, a pressure at a luer connector (not shown) provided in the casing of the respiratory monitoring device 1 is detected. By connecting the respiratory pressure detection tube 5b to the luer connector, the pressure sensor 10 can detect the respiratory pressure.

  The A / D converter 20 is a converter that converts an analog signal output from the pressure sensor 10 into a digital signal. In this embodiment, the A / D converter 20 is a semiconductor A / D converter, and samples (samples) an analog signal of a respiratory waveform output from the pressure sensor 10 at a predetermined sampling frequency (for example, 10 Hz). Quantization is performed, and digitized respiratory pressure data (hereinafter referred to as “respiration data” in the present embodiment) is output to the CPU 30. Respiratory pressure time-series data output from the A / D converter 20 is a respiratory waveform.

  The CPU 30 is a processor that comprehensively controls each unit of the respiratory monitoring device 1 according to various programs such as a system program stored in the ROM 80. Instead of the CPU 30, a processing unit having a microprocessor such as a DSP (Digital Signal Processor) or an electric / electronic element such as an ASIC (Application Specific Integrated Circuit) or an IC (Integrated Circuit) memory may be configured. Of course. The CPU 30 executes a breath analysis process by executing the breath analysis program 81 stored in the ROM 80 using the RAM 90 as a work area.

  The CPU 30 includes, as main functional units, an offset estimation unit 31, an error compensation respiratory waveform calculation unit 32, a respiratory dynamic index value calculation unit 33, a respiratory dynamic evaluation unit 35, a notification control unit 37, and a reference timing setting unit. 39. However, these functional units are described in an easy-to-understand manner to explain the functions of the CPU 30, and are merely described as an example. All of these functional units do not necessarily have to be essential components, and it is needless to say that other functional units may be added as essential components.

  The offset estimation unit 31 performs a predetermined offset estimation process based on the digitized time series data of the respiratory pressure output from the A / D converter 20 to estimate the offset. In this embodiment, the offset estimated by the offset estimation unit 31 includes a) a discharge pressure fluctuation component of the oxygen concentrator 3, b) a fluctuation pressure component generated when the set flow rate of the oxygen concentrator 3 is changed, and c) a pressure. Temperature drift component of the sensor 10, d) drift component of the pressure sensor 10 with time, e) back pressure fluctuation component generated by bending of the nostril cannula 5, f) back pressure fluctuation generated due to the wearing state of the nostril cannula 5, etc. Component at least. The fluctuating back pressure component of f) is, for example, a nostril cannula such as whether the tube of the nostril cannula 5 is inserted / shallowed deeply into the subject's nose or whether the subject is loosely / strongly hooked on the ear of the subject. 5 represents a back pressure fluctuation component generated due to the wearing state 5. This also occurs when the subject unconsciously touches the nostril cannula 5 during sleep. The offset estimated by the offset estimation unit 31 corresponds to an error component superimposed on the respiratory waveform.

  The error-compensated respiration waveform calculation unit 32 uses the digitized respiration waveform output from the A / D converter 20 and the offset estimated by the offset estimation unit 31 to superimpose on the respiration waveform. An error-compensated respiratory waveform that is time-series data of the respiratory pressure compensated for is calculated.

  The respiratory dynamic index value calculator 33 calculates the respiratory dynamic index value of the subject based on the error compensated respiratory waveform calculated by the error compensated respiratory waveform calculator 32. In the present embodiment, the respiratory dynamic index value includes index values such as tidal volume and minute ventilation, expiration time and inspiration time for each breath, tidal time, and respiratory variation coefficient.

  The respiratory dynamic evaluation unit 35 evaluates the respiratory dynamics of the subject based on the respiratory dynamic index value calculated by the respiratory dynamic index value calculation unit 33. Details will be described later.

  The notification control unit 37 controls the notification unit such as the display 50, the lamp 55, and the speaker 60 to perform predetermined notification based on the evaluation result of the respiratory dynamic evaluation unit 35.

  The reference timing setting unit 39 sets the reference timing used when the offset estimation unit 31 estimates the offset based on the sample timing when the A / D converter 20 samples the respiratory waveform.

  The operation key 40 is an operation means used when selecting measurement items and inputting subject information (information such as age, height, weight, etc.), and outputs a signal of a pressed button to the CPU 30. For example, it consists of 10 numeric keys from 0 to 9, direction keys for selecting measurement items, and the like. In addition, a print key operated when printing out data displayed on the display 50 is also included.

  The display 50 is configured to include an LCD (Liquid Crystal Display) or the like, and is a display unit that performs various displays based on display signals input from the CPU 30. The display 50 displays various information such as a respiratory waveform, an error compensated respiratory waveform, a respiratory dynamic index value, and a respiratory dynamic evaluation result.

  The lamp 55 includes a light emitting diode (LED) and the like, and is a light emitting device that lights or blinks based on a light emission signal output from the CPU 30. For example, the lamp 55 lights or blinks green when the evaluation result of respiratory dynamics is a positive evaluation, and lights or blinks red when the evaluation result of respiratory dynamics is a negative evaluation. To be controlled.

  The speaker 60 is sound output means for outputting various sounds based on the sound output signal input from the CPU 30. From the speaker 60, a voice for guiding to give various instructions to the subject for analyzing the breath, and a warning sound for warning when an abnormality or a failure occurs during the analysis of the breath A sound, a buzzer sound and the like for notifying the result of evaluation of respiratory dynamics are output.

  The ROM 80 is a non-volatile storage device (memory), and stores various programs such as a system program of the respiratory monitoring device 1. In the present embodiment, the ROM 80 stores a respiratory analysis program 81 that is read by the CPU 30 and executed as a respiratory analysis process (see FIG. 3) as a main program. The respiratory analysis program 81 includes a respiratory dynamics evaluation program 811 executed as a respiratory dynamics evaluation process (see FIG. 4) as a subroutine. Although not shown, the ROM 80 also stores audio data for guidance, and this audio data is output from the speaker 60 as audio for guidance. The respiratory analysis process will be described later in detail using a flowchart.

  The RAM 90 is a volatile storage device (memory), and forms a work area that temporarily stores a system program executed by the CPU 30, various processing programs, data being processed in various processing, processing results, and the like. In the present embodiment, the RAM 90 stores respiratory waveform data 91, offset data 93, error compensated respiratory waveform data 95, and respiratory dynamic index value data 97. In the present embodiment, the respiratory dynamic index value data 97 includes tidal volume data 971 and respiratory variation coefficient data 973.

3-1. First Embodiment (1) Process Flow FIG. 3 is a flowchart showing the flow of a respiration analysis process executed by the CPU 30 in accordance with a respiration analysis program 81 stored in the ROM 80.
First, the CPU 30 starts to acquire time-series data of the respiratory pressure digitized (digitized) from the A / D converter 20, and starts processing to store the respiratory waveform data 91 in the RAM 90 (step A1). . Thereafter, time-series respiratory data is stored in the respiratory waveform data 91 as needed.

  Next, the CPU 30 waits until data for a certain period (for example, one minute) is stored from the start of acquisition of respiratory data (step A3; No). If it is determined that data for a certain period has been stored (step A3; Yes), the reference timing setting unit 39 sets the timing corresponding to the latest time as the reference timing (step A5).

  After that, the offset estimation unit 31 performs respiration waveform respiration data for the past predetermined period (for example, for 10 seconds) retroactively from the reference timing set in step A5 (ie, by the A / D converter 20) as the offset estimation process. The sampling data is averaged to estimate the offset, and the offset data 93 is stored in the RAM 90 (step A7). Here, as the average calculation in step A7, for example, a moving average calculation can be applied. Specifically, the offset is estimated by performing a simple moving average calculation on the respiration data for a predetermined period in the past.

  Next, the error-compensated respiratory waveform calculation unit 32 calculates an error-compensated respiratory waveform using the respiratory waveform stored as the respiratory waveform data 91 in the RAM 90 and the offset stored as the offset data 93, and compensates for the error. The respiration waveform data 95 is stored in the RAM 90 (step A9).

  Next, the CPU 30 determines whether or not it is a respiratory dynamics evaluation timing (step A11). The evaluation timing of the respiratory dynamics can be set, for example, every time a time interval (for example, 5 minutes) corresponding to the length of a period predetermined as the evaluation period elapses.

  If it is determined in step A11 that it is not the evaluation timing of respiratory dynamics (step A11; No), the CPU 30 returns to step A3 and waits until data for a certain period is stored again.

  On the other hand, if it is determined that it is the respiratory dynamics evaluation timing (step A11; Yes), the CPU 30 performs a respiratory dynamics evaluation process according to the respiratory dynamics evaluation program 811 stored as a subroutine of the respiratory analysis program 81 in the ROM 90. (Step A13).

FIG. 4 is a flowchart showing the flow of the respiratory dynamics evaluation process.
First, the respiratory dynamic index value calculation unit 33 performs a tidal volume (i.e., a subject's tidal volume) in a predetermined evaluation period (for example, the latest period of 5 minutes) based on the error compensated respiratory waveform stored in the error compensated respiratory waveform data 95. Vt) is calculated as a respiratory dynamic index value and stored in the RAM 90 as tidal volume data 971 (step B1). Specifically, the inspiratory tidal volume (Vti) is calculated for the respiratory waveform for one cycle in the error compensated respiratory waveform, and is stored as the tidal volume data 971. In addition to the inspiratory tidal volume (Vti), the exhaled tidal volume (Vte) may be stored as the tidal volume data 971. A calculated value based on the inspiratory tidal volume (Vti) and the exhaled tidal volume (Vte), for example, (Vti + Vte) / 2 may be stored as the tidal volume data 971.

  Here, the inventors conducted an experiment to measure the number of breaths (RR) and the tidal volume (Vt) for 11 patients with COPD while acquiring breathing waveform data during rest breathing. During the experimental period, for 2 out of 11 cases, acute aversion was observed in the patient. At this time, the respiratory rate (RR) during rest breathing was stable in all 11 cases including acute exacerbations, but the tidal volume (Vt) was varied in two cases of acute exacerbations. Considering such an event, in step B1, a tidal volume (Vt) is calculated as a respiratory dynamic index value.

  Next, the respiratory dynamics evaluation unit 35 uses the tidal volume data 971 for the evaluation period stored in the RAM 90, and uses the average value of the subject's tidal volume during the evaluation period (hereinafter, “tidal volume average”). Value ”) and standard deviation (hereinafter referred to as“ tidal volume standard deviation ”) are calculated (step B3).

Thereafter, the respiratory dynamic evaluation unit 35 calculates a respiratory variation coefficient according to the following equation (1), and stores it in the RAM 90 as the respiratory variation coefficient data 973 (step B5). In the present embodiment, the respiratory variation coefficient is defined as the variation coefficient of the tidal volume.
Respiration coefficient = (Standard deviation of tidal volume ÷ Average tidal volume) x 100 (1)

  Next, the respiratory dynamics evaluation unit 35 determines whether or not the respiratory variation coefficient is equal to or greater than a predetermined threshold (step B7). The breathing variation coefficient being equal to or greater than a predetermined threshold is an example when the breathing variation coefficient satisfies a predetermined high threshold condition. According to the knowledge based on the results of the inventor's previous research, the subject has difficulty breathing if the respiratory variation coefficient shows a value of about 25 or more (that is, high threshold condition: respiratory variation coefficient ≧ about 25). It became clear that it may be evaluated that it is in the state of.

  Therefore, when the determination result in step B7 is affirmative (step B7; Yes), the respiratory dynamics evaluation unit 35 determines that the subject has difficulty breathing (step B9). On the other hand, when the determination result of step B7 is negative (step B7; No), the respiratory dynamics evaluation unit 35 determines that the subject has no dyspnea (step B11). After step B9 or B11, the CPU 30 ends the respiratory dynamics evaluation process.

  Returning to the respiration analysis process of FIG. 3, if the respiration dynamic evaluation process is performed, the CPU 30 determines whether or not the evaluation in the respiration dynamic evaluation process is “difficult to breathe” (step A15). If it is determined that this condition is satisfied (step A15; Yes), the notification control unit 37 performs notification processing (step A17). Specifically, control is performed to notify an informing means such as the display 50, the lamp 55, and the speaker 60 that the subject is estimated to be having difficulty breathing. For example, control for displaying a message indicating that breathing is difficult on the display 50, control for lighting or blinking the lamp 55 in red, and output of a predetermined buzzer sound from the speaker 60 are performed.

  After step A17 or if it is determined in step A15 that the condition is not satisfied (step A15; No), the CPU 30 determines whether or not to end the analysis (step A19). For example, when it is detected that the end of the analysis is instructed by the subject via the operation key 40, it is determined that the analysis is ended. If it is determined that the analysis is to be continued (step A19; No), the CPU 30 returns to step A3. Moreover, if it determines with complete | finishing an analysis (step A19; Yes), CPU30 will complete | finish a respiration analysis process.

(2) Experimental Results FIG. 5A is a diagram showing an example of experimental results obtained by actually measuring and calculating the respiratory waveform and the error compensated respiratory waveform. FIG. 5 (1) shows a respiratory waveform that is a waveform of the respiratory pressure detected by the pressure sensor 10, and FIG. 5 (2) shows an error-compensated respiratory waveform calculated using the method of this embodiment. In each figure, the horizontal axis is time t. The vertical axis represents the respiratory pressure. The respiratory pressure of the respiratory waveform in FIG. 5 (1) is P1 (t), and the respiratory pressure of the error compensated respiratory waveform in FIG. 5 (2) is P2 (t). To do. In this experiment, a predetermined period used for offset estimation was set as a period of “10 seconds”.

  In FIG. 5A, the sample timing t1 is set as the reference timing. Then, the offset Offset = ave (t1) was estimated by averaging the respiratory pressure data for the past 10 seconds from the reference timing t1. Then, the respiratory pressure P2 (t) = P1 (t) −Offset is calculated by subtracting the offset Offset from the respiratory pressure P1 (t) at each sample timing of the respiratory waveform in FIG. FIG. 5B shows the result obtained as the error compensated respiratory waveform.

(3) Effects In the respiratory monitoring device 1, the pressure sensor 10 detects a change in the respiratory pressure of the subject (time-series data of respiratory pressure) including the pressure due to the flow rate of supplied oxygen supplied from the oxygen concentrator 3 to the subject. To obtain a respiratory waveform. Based on the respiratory waveform detected by the pressure sensor 10, the offset estimation unit 31 estimates an offset that varies with time and is superimposed on the respiratory waveform when oxygen is supplied from the oxygen concentrator 3. Then, using the offset estimated by the offset estimation unit 31, the error compensation respiratory waveform calculation unit 32 calculates an error compensation respiratory waveform that is time-series data of the respiratory pressure compensated for the offset superimposed on the respiratory waveform. To do. Then, the respiratory dynamic index value calculation unit 33 calculates the respiratory dynamic index value of the subject based on the error compensated respiratory waveform calculated by the error compensated respiratory waveform calculation unit 32.

  More specifically, the offset estimation unit 31 estimates the offset by performing a process of averaging the respiration data (respiratory pressure data) of the respiration waveform for a predetermined period retroactive from one reference timing of the respiration waveform. From the oxygen concentrator 3, oxygen is supplied to the subject via the oxygen supply tube 5a, and the breath of the subject is input to the pressure sensor 10 via the pressure detection tube 5b. In this case, a) the discharge pressure fluctuation component of the oxygen concentrator 3, b) the fluctuation pressure component generated when the set flow rate of the oxygen concentrator 3 is changed, c) the temperature drift component of the pressure sensor 10, d) the pressure sensor 10 Offsets such as a drift component with time, e) a back pressure fluctuation component generated due to bending of the nostril cannula 5, and f) a back pressure fluctuation component generated due to the wearing state of the nostril cannula 5 are superimposed on the respiratory waveform as an error component. These error components are estimated by averaging the respiration data of the respiration waveform for a predetermined period going back from one reference timing of the respiration waveform. Then, by subtracting the estimated offset from the respiratory waveform, a correct respiratory waveform in which the offset superimposed on the respiratory waveform is compensated can be obtained.

  Here, when simply measuring the number of respirations (RR), it is not necessary to estimate the offset component included in the respiration waveform as described above, and after the obtained respiration waveform is smoothed, differential processing is performed. Thus, the number of breaths (RR) can be calculated easily and accurately. However, as described above, since it is difficult to detect acute aversion of a patient only by measuring the number of breaths (RR), it is important to measure the tidal volume (Vt). The tidal volume (Vt) relates to the inspiratory tidal volume (Vti) and the exhaled tidal volume (Vte), and these inspiratory tidal volume (Vti) and expiratory tidal volume ( Vte) is a measurement item affected by the offset component described above. Therefore, regarding the tidal volume (Vt), it is appropriate to first calculate an offset component and then calculate based on the error compensated respiratory waveform obtained by removing the offset component from the respiratory waveform.

  Further, the respiratory dynamic index value calculation unit 33 calculates the amount of breathing and the respiratory variation coefficient of the subject as the respiratory dynamic index value. Then, the respiratory dynamics evaluation unit 35 determines whether the respiratory variation coefficient calculated by the respiratory dynamics index value calculation unit 33 satisfies a predetermined high threshold condition, and when the determination result is affirmative determination, The subject is assessed as having difficulty breathing. In this case, the notification control unit 37 controls the notification means such as the display 50, the lamp 55, and the speaker 60 to notify that the subject has evaluated that the subject is in a difficult breathing state. Thus, the subject's condition / pathology and respiratory dynamics can be accurately evaluated, and the result of the evaluation can be notified to the subject. Therefore, the test subject can know whether or not he / she is in a difficult breathing state, and it becomes easy to grasp the medical condition and condition.

  Of course, the respiratory dynamic index value calculated by the respiratory dynamic index value calculation unit 33 is not limited to the respiratory fluctuation coefficient of the tidal volume, and the respiratory fluctuation coefficient of the minute ventilation (MV), etc. Other measurement items related to the ventilation amount may be calculated. And the respiratory dynamics evaluation part 35 may evaluate a subject's respiratory dynamics based on these respiratory dynamics index values. In this case, similarly to the above-described embodiment, the notification control unit 37 may control the notification unit 37 such as the display 50, the lamp 55, and the speaker 60 to notify the result of the evaluation by the respiratory dynamic evaluation unit 35.

3-2. Second Example The second example is an example in which the offset estimation unit 31 estimates an offset by performing an offset estimation process different from that of the first example. Although illustration is omitted, in the present embodiment, it is assumed that the second respiratory analysis program is stored in the ROM 80 of the respiratory monitoring device 1 in place of the respiratory analysis program 81.

(1) Process Flow FIG. 6 is a flowchart showing the flow of the second respiration analysis process executed by the CPU 30 in accordance with the second respiration analysis program stored in the ROM 80. Note that the same steps as those in the breath analysis process of FIG. 3 are denoted by the same reference numerals, and the description thereof will not be repeated.

  After starting the acquisition of the respiratory waveform in Step A1, the CPU 30 determines whether or not the respiratory waveform data for a certain period (for example, 3 to 6 hours) is stored in the RAM 90 (Step C3). The CPU 30 waits until data for a certain period is stored (step C3; No). If it is determined that data for a certain period has been stored in the RAM 90 (step C3; Yes), the CPU 30 starts from the certain period. An evaluation period for which respiratory dynamics is to be evaluated is set (step C5). In the present embodiment, description will be made assuming that the timing divided by the time of 5 minutes is set as the evaluation period.

Next, the CPU 30 performs a loop A process for each evaluation period set in step C5 (steps C7 to C17). In the process of loop A, the reference timing setting unit 39
A reference timing is set for the evaluation period (step C9). For example, a timing corresponding to the central time of the evaluation period is set as the reference timing.

  Subsequently, the offset estimation part 31 performs the process of following step C11-C15 as an offset estimation process. More specifically, the first offset is estimated by performing a first integral approximation calculation process for integrating and calculating data for a first predetermined period retroactively from the reference timing set in step C9 (step C11). . Specifically, a linear function that integrates the respiration data of the respiration waveform for the first predetermined period is calculated. This linear function is calculated based on the relationship between ΔX and ΔY, where ΔX is the first predetermined period and ΔY is an integrated value obtained by integrating the respiratory data in the period of ΔX. Then, the calculated slope of the linear function is estimated as the first offset.

  Similarly, the offset estimation unit 31 estimates a second offset by performing a second integral approximation calculation process that performs integral approximation calculation on data for a second predetermined period after the reference timing set in step C9 ( Step C13). Specifically, a linear function that integrates the respiration data of the respiration waveform for the second predetermined period is calculated. This linear function is calculated based on the relationship between ΔX and ΔY, where ΔX is the second predetermined period, and ΔY is an integrated value obtained by integrating the respiratory data in the period of ΔX. Then, the calculated slope of the linear function is estimated as the second offset. In the present embodiment, the first predetermined period and the second predetermined period will be described as being set as the same time period. Specifically, for example, the first predetermined period and the second predetermined period are set as a period of 5 seconds before and after the reference timing.

  Next, the offset estimation unit 31 uses the first offset estimated in the first integral approximation calculation process and the second offset estimated in the second integral approximation calculation process to calculate a final offset. Estimate (step C15). Specifically, for example, the first offset and the second offset are added and averaged, and the result is estimated as the final offset and stored in the RAM 90 as the offset data 93. Then, after calculating the error compensated respiratory waveform (step A9) and the respiratory dynamics evaluation process (step A13), the CPU 30 shifts the process to the next evaluation period.

  If the processes in steps C7 to C17 are performed for all the evaluation periods, the CPU 30 determines whether or not there is an evaluation period evaluated as having difficulty breathing (step C19), and determines that it has not existed. (Step C19; No), the process proceeds to Step A19. When it is determined that there is an evaluation period evaluated as having difficulty breathing (step C19; Yes), the notification control unit 37 performs notification processing (step A17), and then the process proceeds to step A19.

  In this second respiration analysis process, data on the respiration waveform of the subject over a relatively long period is acquired and stored in a memory, and thereafter, an error-compensated respiration waveform is calculated as post-processing and evaluation of respiration dynamics. It is a process to perform.

(2) Experimental Results FIG. 7 is a diagram illustrating an example of experimental results obtained by actually measuring and calculating the respiratory waveform and the error compensated respiratory waveform. FIG. 7 (1) shows the respiration waveform detected by the pressure sensor 10, FIG. 7 (2) shows an approximate straight line obtained by performing integral approximation processing, and FIG. 7 (3) is finally calculated. The error compensated breathing waveform is shown. In each figure, the horizontal axis is time t. The vertical axis represents the respiratory pressure. The respiratory pressure of the respiratory waveform in FIG. 7 (1) is P1 (t), and the respiratory pressure of the error compensated respiratory waveform in FIG. 7 (3) is P2 (t). To do. In this experiment, the first predetermined period and the second predetermined period used for offset estimation were set as the same period of “5 seconds”.

  In FIG. 7A, the sample timing t2 is set as the reference timing. Then, a first integral approximation calculation process for integrating and calculating the respiratory pressure P1 (t) data for 5 seconds traced back from the sample timing t2 is performed, and the respiratory pressure P1 (t) for 5 seconds after time t2. A second integral approximation calculation process for performing integral approximation calculation on the data was performed. As a result, an approximate straight line as shown in FIG. 7 (2) was obtained. A straight line indicated by a solid line in FIG. 7B indicates a first approximate straight line obtained by performing the first integral approximation calculation process. Further, the straight line indicated by a dotted line in FIG. 7B is a second approximate straight line obtained by performing the second integral approximation calculation process.

  Here, since the same value is always added as the average value of the offset, the slope of the first approximate line is set as the first offset Offset1, and the slope of the second approximate line is set as the second offset Offset2. A value obtained by averaging the first offset Offset1 and the second offset Offset2 was estimated as the offset Offset. Finally, the offset Offset is subtracted from the respiratory pressure P1 (t) at each sample timing of the respiratory waveform in FIG. 7 (1) to calculate the respiratory pressure P2 (t) = P1 (t) −Offset, and the time series data is obtained. FIG. 7 (3) shows the result obtained as the error compensated respiratory waveform.

(3) Effects In the respiratory monitoring device 1, the offset estimation unit 31 performs a first integral approximation calculation process that performs integral approximation calculation on the respiratory data of the respiratory waveform for the first predetermined period that goes back from the reference timing. Moreover, the offset estimation part 31 performs the 2nd integral approximation calculation process which carries out integral approximation calculation of the respiration data for the 2nd predetermined period after a reference | standard timing. Then, the offset is estimated using the first offset calculated in the first integral approximation calculation process and the second offset calculated in the second integral approximation calculation process. By integrating and approximating the respiration data of the respiration waveform for a predetermined period before and after the reference timing, and using these results, the accuracy of the error component estimation can be further improved.

4). Modifications Embodiments to which the present invention can be applied are not limited to the above-described embodiments, and can be changed as appropriate without departing from the spirit of the present invention. Hereinafter, although a modification is demonstrated, the same code | symbol is attached | subjected about the same step as the said Example and the same structure as said Example, and description for the second time is abbreviate | omitted.

4-1. Acquisition of Respiration Waveform In the above embodiment, it has been described that the respiration waveform of the subject is acquired using the pressure sensor 10, but instead of the pressure sensor 10, for example, the respiration waveform of the test subject is acquired using a differential pressure type flow meter. It is good also as acquiring.

  In the above embodiment, the pressure sensor 10 has been described as a pressure sensor that can detect the pressure at one luer connector. Instead, a differential pressure sensor that can detect a differential pressure between two luer connectors is used. You may do it. In this case, the respiratory pressure detection tube 5b is connected to one luer connector, and the other luer connector is opened to the atmosphere, so that in the differential pressure sensor, the atmospheric pressure and the pressure in the respiratory pressure detection tube 5b are detected. Is detected.

4-2. Evaluation of respiratory dynamics In the above embodiment, it has been described that the subject is evaluated whether or not the subject is in a state of difficulty in breathing based on the respiratory variation coefficient defined as the variation coefficient of the tidal volume. Of course, the method of evaluating respiratory dynamics is not limited to this. For example, the fluctuation coefficient of minute ventilation may be calculated as the respiratory fluctuation coefficient instead of the fluctuation coefficient of tidal volume, and this may be used to evaluate whether or not the subject is in a difficult breathing state. Moreover, it is good also as evaluating a test subject's pathological condition, a medical condition, and respiratory dynamics based on the respiratory dynamics index values, such as inhalation time for every breath, expiration time, and tidal time.

4-3. Notifying means The notifying means for notifying the evaluation result of the respiratory dynamics of the subject is not limited to the display 50, the lamp 55, and the speaker 60 described in the above embodiment. In addition, it is not always necessary to provide all of these notification means in the respiration monitoring device 1, and it is sufficient that at least one of these notification means is provided in the respiration monitoring device 1, and the design can be changed as appropriate. Needless to say.

4-4. Offset estimation process In the first embodiment described above, the offset estimation process is performed by performing a simple moving average calculation on the respiration data for a predetermined period, but the average calculation process for estimating the offset is performed here. It is not limited. For example, the offset may be estimated by performing a weighted moving average calculation instead of the simple moving average calculation. In this case, for example, a linear weighted moving average is applied as the weighted moving average, and weighting is performed on the respiration data so that the weight on the respiration data at the reference timing becomes the highest, and the weighted moving average calculation is performed. can do.
It should be noted that not only the above-mentioned simple moving average and weighted moving average but also exponential moving average may be performed, and the average calculation processing for estimating the offset can be appropriately changed.

  In the second embodiment, the value obtained by averaging the first offset and the second offset is estimated as the final offset. However, the offset estimation method is not limited to this. For example, instead of simply adding and averaging the first offset and the second offset, the offset may be estimated by weighted averaging the first offset and the second offset. In other words, the weight for the first offset is “α”, the weight for the second offset is “β” (where α + β = 1), the values of α and β are variably set, and the weighted average is performed. An offset may be estimated.

  In addition, the first offset and the second offset are not used to estimate the offset, but the first offset may be estimated as the final offset. Of course, the final offset may be estimated. In other words, the error component may be estimated by performing integral approximation calculation processing on respiration data for a predetermined period retroactive from the reference timing, or error by performing integral approximation calculation processing on respiration data for a predetermined period after the reference timing. Components may be estimated.

4-5. Although the reference timing setting unit 39 sets the latest time as the reference timing after the respiration data for a certain period has been stored in the first embodiment, the reference timing setting unit 39 has been described. The reference timing may be set and updated in real time. In other words, instead of waiting for breathing data for a certain period to be stored and setting the reference timing, a timing corresponding to the latest time may be set as the reference timing whenever breathing data is acquired. .

4-6. Setting of a predetermined period Since the amount of oxygen supplied from the oxygen concentrator 3 is not always constant, the offset, which is an error component corresponding to supplied oxygen and noise, can change over time. Therefore, it is also possible to determine a waveform portion showing a similar change tendency (hereinafter referred to as “similar change tendency waveform portion”) from the respiratory waveform and variably set the predetermined period based on the determined waveform portion. Good.

  In this case, although not shown in the figure, as a function unit of the CPU 30, a similar change tendency waveform portion determination unit that determines a waveform portion showing a similar change tendency from the respiratory waveform is configured. Moreover, the function setting part of CPU30 comprises the period setting part which sets the predetermined period used for offset estimation variably. The period setting unit variably sets the predetermined period based on the waveform portion determined by the similar change tendency waveform portion determination unit.

  The determination of the similar change tendency waveform portion is, for example, calculating the difference between the maximum value (maximum peak) and the minimum value (minimum peak) of the respiratory waveform, and the waveform portion where the difference is equal to or less than a predetermined threshold (or less than the threshold) Can be determined as a similar change tendency waveform portion. For each of exhalation and inspiration, for example, an approximate straight line is obtained by using the least square method for the respiration data of the respiration waveform, and the difference between the slopes of the approximate line for each of exhalation and inspiration is equal to or less than a predetermined threshold (or threshold value). May be determined as a similar change tendency waveform portion. Note that the above two methods may be used in combination, and in this case, the accuracy of determination of the similar change tendency waveform portion can be further improved.

  In these cases, for example, the reference timing setting unit 39 sets the latest timing among the sample timings corresponding to the similar change tendency waveform portion determined by the similar change tendency waveform portion determination unit as the reference timing. Then, the period setting unit sets a period corresponding to a part or all of the similar change tendency waveform portion as a predetermined period used for offset estimation. Since the time length of the similar change tendency waveform portion changes at any time, the predetermined period used for the offset is also set to be variable each time.

  In the second embodiment, the first predetermined period and the second predetermined period have been described as having the same length. However, it is not always necessary to have the same length. It is good also as setting as a period. In this case, the similar change tendency waveform portion may be determined using the same method as described above, and the first predetermined period and the second predetermined period may be variably set based on the determination result.

DESCRIPTION OF SYMBOLS 1 Respiration monitoring apparatus 3 Oxygen concentrator 5 Nostril cannula 5a Oxygen supply tube 5b, 5c Respiratory pressure detection tube 10 Pressure sensor 20 A / D converter 30 CPU
40 operation keys 50 display 55 lamp 60 speaker 80 ROM
90 RAM
100 Respiration monitoring system

Claims (7)

An acquisition means for acquiring a respiratory waveform in a state where oxygen is supplied to the subject from the oxygen supply device;
By performing the error estimation process using the respiration data for a predetermined period in the respiratory waveform, and estimating means for estimating a time fluctuating error component,
A computing means for computing an error-compensated respiratory waveform based on the error component estimated by the estimating means;
Calculation means for calculating the respiration dynamics index value based on the previous SL error compensation respiratory waveform,
A respiratory monitoring device. The error estimation process includes a process of averaging calculating the respiration data for a predetermined period going back from the reference timing in the respiratory waveform,
The respiratory monitoring device according to claim 1 . The error estimation process includes a process for integrating approximate calculation of respiration data for a predetermined period going back from the reference timing in the respiratory waveform,
The respiratory monitoring device according to claim 1 . The error estimation process includes:
A first integral approximation calculation process of the first integral approximation calculates respiration data for a predetermined period going back from the reference timing in the respiratory waveform,
A second integral approximation calculation processing for the integral approximation calculates a second respiration data for a predetermined period after the reference timing,
And using the result of the first integral approximation calculation process and the result of the second integral approximation calculation process to estimate the error component,
The respiratory monitoring device according to claim 1 . A reference timing setting means for setting and updating the reference timing in real time;
The respiratory monitoring device according to any one of claims 2 to 4 . Determination means for determining a waveform portion showing a similar change tendency from the respiratory waveform;
A period setting means for variably setting the predetermined period based on the waveform portion determined by the determination means;
Further comprising
The respiratory monitoring device according to any one of claims 1 to 5 . Acquiring a respiratory waveform in a state where oxygen is supplied to the subject from the oxygen supply device;
Estimating an error component that varies over time by performing an error estimation process using respiration data for a predetermined period in the respiration waveform ;
And computing the erroneous difference compensation respiratory waveform based on the estimated error component,
And calculating the respiration dynamics index value based on the previous SL error compensation respiratory waveform,
Respiratory monitoring method.