Method and apparatus for respiratory measurement

Abstract

To provide a method for performing pulmonary function test.SOLUTION: A method for measuring changes in respiration uses measurement data representing a plurality of measured respiration cycles in the form of flow and volume of respiration, or flow and time of respiration, or time and volume of respiration, over a duration of time, wherein such measurement data pertains to at least the expiration phase measurement of the respiration cycles, analyzing variability of the expiration phases of flow-volume, flow-time or time-volume measurements of the respiration cycles, the measurements are measurements over a duration of time, the variability between the expiration phases of the respiration cycles is analyzed from the measurement data in a range of the first half of expired volume in the expiration phase of the respiration cycles. A corresponding device and a computer program product are also presented.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] Generally, the present invention relates to respiratory measurement. Specifically, but not exclusively, the present invention relates to a method for measuring and detecting changes in human respiration.

Background Art

[0002] Pulmonary function measurement is the basis for the monitoring and diagnosis of multiple lung diseases. However, subjects with limited ability to cooperate due to developmental stage or mental or physical constraints are unable to perform the demanding breathing maneuvers required for normal pulmonary function tests. For example, the diagnosis of asthma in preschool children is difficult because conventional pulmonary function tests are not suitable.

[0003] Measurements during spontaneous periodic breathing (TB) require minimal cooperation and are therefore suitable for young children and infants. There are large-scale studies suggesting that parameters derived from the TB flow curve or flow-volume (TBFV) curve change in a decisive way in obstructive respiratory diseases in young patients. Studies have shown, for example, that TB parameters are related to forced expiratory volume in one second (FEV1), airway resistance, bronchial dilation response, and methacholine challenge and can be used to distinguish pathological respiratory states.

[0004] Current techniques and devices for measuring and analyzing TB patterns are hampered by the need for direct access to the airway. Sedatives can often be used to overcome the psychological aspects of measurement, but physical face contact and increased dead space still distort the breathing pattern. In particular, the analysis of the temporal variability of periodic breathing would benefit from longer TB recordings that are not possible with instruments that require direct airway access.

Summary of the Invention

[0005] An object of an embodiment of the present invention is to at least mitigate one or more of the aforementioned drawbacks found in prior art devices, particularly in relation to methods and devices for respiratory measurement. The object is generally achieved by using a method, a device, and a computer program product according to the present disclosure.

[0006] An advantage of the present invention is a method that can be used to detect changes in a person's breathing, enabling the measurement of a person's breathing. Such detected changes in breathing may then be used to diagnose the cause of the detected changes in breathing.

[0007] According to one aspect of the present invention, a method for measuring changes in breathing using measurement data corresponding to a plurality of measured breathing cycles in the form of breathing flow rate and volume, or breathing flow rate and time, or breathing time and volume over a period of time, such measurement data belonging at least to measurements of the exhalation phase of the breathing cycle, analyzing the variation in the exhalation phase of the flow rate-volume, flow rate-time, or time-volume measurement of the breathing cycle, the measurement being a measurement over a period of time, wherein the variation between the exhalation phases of the breathing cycle is analyzed from measurement data in the range of the first half of the exhalation volume of the exhalation phase of the breathing cycle.

[0008] According to another aspect of the present invention, an apparatus for measuring changes in breathing, comprising measuring means for measuring breathing flow rate and volume, or breathing flow rate and time, or breathing time and volume over a period of time, such measurements belonging at least to measurements of the exhalation phase of the breathing cycle, analyzing the variation in the exhalation phase of the flow rate-volume, flow rate-time, or time-volume measurement of the breathing cycle, the measurement being a measurement taken over a period of time and further comprising computing means arranged such that the variation between the exhalation phases of the breathing cycle is analyzed from measurement data in the range of the first half of the exhalation volume of the exhalation phase of the breathing cycle.

[0009] According to another aspect of the present invention, a computer program product embodied on a non-transitory computer-readable medium including computer code for causing a computer to execute the method according to claim 1.

[0010] As briefly described above, the usefulness of the different aspects of the present invention results from a plurality of problems according to each specific embodiment.

[0011] As used herein, the expression "some" may refer to any positive integer starting from one (1). The expression "a plurality of" may each refer to any positive integer starting from two (2).

[0012] As used herein, the term "exemplary" refers to an example or a feature like an example and is not the only or sole preferred option.

[0013] The expression "tidal volume" is an amount corresponding to the amount of air replaced during one normal inhalation or exhalation. Thus, the expression "periodic breathing" is used to refer to normal breathing where the tidal volume is the tidal volume.

[0014] The expression "breathing cycle" is used to refer to a cycle of breathing including both exhalation and inhalation. The expression "expiratory phase" is used to refer to the exhalation of the breathing cycle excluding the inhalation of the breathing cycle.

[0015] Different embodiments of the present invention are also disclosed in the appended dependent patent claims.

[0016] Some exemplary embodiments of the present invention will be described in more detail with reference to the accompanying drawings.

Brief Description of the Drawings

[0017]

Figure 1

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Embodiments for Carrying Out the Invention

[0018] Figure 1 depicts an embodiment of a measuring means device suitable for the method according to the present invention. The impedance respiration recording device 30 is connected via a connector interface 31 to a sensor 11 attached to the right arm 2 of the human body 1 and a sensor 12 attached to the left arm 3. Sensors 21, 23 are attached to the side chest or midaxillary line on both sides of the human body 1. The sensor elements include electrodes and cables 13, 14, 15, 16 that transmit electrical signals to the connector interface 31. The midaxillary line is defined as the coronal line on the torso between the anterior axillary line and the posterior axillary line. The sensor placement may vary by several centimeters from the midaxillary line.

[0019] Sensors 11, 12, 21, 22, cables 13, 14, 15, 16, interface 31, and device 30 are components of an impedance respiratory recording measurement system. Sensors 11, 12, 21, 22 may include letters, colors, or other displays that assist a person using the impedance respiratory recording system in connecting the sensors to the correct positions on the human body 1. Sleeves 41, 41 may include displays that distinguish the left arm 2 from the right arm 3. The size or shape of sleeves 41, 42 may also prevent the user from installing sensors 11, 12 in incorrect positions.

[0020] In one embodiment of the device, interface 31 configured for device 30 is arranged to include a display of the correct installation procedure, such as color coding or letters. Device 30 may also include a display for notifying the user about the procedure. The software implemented on device 30 may also include code for providing assistance information to the user, for verifying the correct installation procedure, or for notifying if there are errors during installation or operation. An example of an error state is that the measurement data is outside a predetermined range.

[0021] Device 30 may include an interface for transmitting impedance respiratory recording information to another device, such as a computer or another medical device. In one embodiment, device 30 is arranged to convert the change in chest impedance caused by respiration into a high-level respiratory signal that can be used for other applications. Device 30 may be integrated with another medical device.

[0022] Figure 2 depicts another embodiment of a measuring means device suitable for the method according to the invention, in which sensors 11, 12 are arranged such that they are part of sleeves 41, 42. The sleeves 41, 42 are made of an electrically resistive material that prevents direct skin contact between the arms 2, 3 and the torso. This prevents current from passing through the skin and thus contributing to false values. The bioimpedance value is measured through the upper axillary line or from a preferred path in the upper part of the lungs. The sleeve may be part of a shirt or jacket 43 arranged as used in an impedance pneumography system. The sleeve may be in the form of an armband. In one embodiment, the thickness of the armband maintains the distance between the body and the arm. The sleeve may include electrodes configured as fiber electrodes made of a suitable material such as silver or platinum.

[0023] Sensors 11, 12, 21, 22 may be arranged in different configurations. In four - electrode bioimpedance measurements, four electrodes are used, two for supplying an alternating current of constant amplitude and two for voltage sensing. Also, a constant voltage may be used while the current is being measured. The electrodes may, for example, measure the voltage difference measured from both arms, or the electrodes may supply a current to enable the measurement of impedance. The electrode pairs for the same parameter are always positioned at a distance from each other. The supply of current and the measurement of voltage may be combined in a single sensor as an electrode pair.

[0024] In impedance pneumography, a small high - frequency current passes through a pair of skin electrodes, and another pair of electrodes is used to record the generated voltage that is proportional to the impedance and furthermore proportional to the lung volume. Cardiac oscillations can be removed by the filtering technique described in Finnish patent application FI20115110, which is incorporated herein by reference.

[0025] The arrangement of electrodes 11 and 12 on arms 2 and 3 significantly improves the linearity of the measurement results of impedance with respect to lung volume, particularly on a low lung volume scale. One exemplary electrode arrangement is between the biceps brachii and the triceps brachii. This arrangement of the electrodes on the arm can be said to be an arrangement on the suprascapular line. By preventing skin contact between the arm and the body side, since skin contact does not contribute to the bioimpedance value, the measured value is improved.

[0026] Examples of methods for filtering cardiogenic oscillations from a thoracic impedance signal are presented herein.

[0027] Suppression of the oscillation signal Sosc is performed by providing a composite signal S including the oscillation signal Sosc and the modulation signal Smod, high-pass filtering the composite signal S with a high-pass filter to generate an estimated value of the oscillation signal Sosc and an estimated value of the modulation signal Smod, the estimated value of the oscillation signal Sosc including a first oscillation during a first state of the modulation signal Smod and a second oscillation during a second state of the modulation signal Smod, determining a first bin associated with the first state and a second bin associated with the second state, assigning the first bin to the first oscillation according to the state determined from the estimated value of the modulation signal Smod, assigning the second bin to the second oscillation according to the state determined from the estimated value of the modulation signal Smod, forming a first average waveform of the first oscillation in the first bin and a second average waveform of the second oscillation in the second bin, and using the first and second average waveforms to suppress the oscillation signal Sosc from the composite signal S in each state of the first and second average waveforms.

[0028] In other words, the vibration signal Sosc can be suppressed from the composite signal S including the vibration signal Sosc and the modulation signal Smod without removing the portion of the modulation signal Smod. The composite signal S is high-pass filtered to generate an estimated value of the vibration signal Sosc and an estimated value of the modulation signal Smod. The estimated value of the vibration signal Sosc includes at least a first vibration during a first state of the modulation signal Smod and a second vibration during a second state of the modulation signal Smod. A first bin associated with the first state and a second bin associated with the second state are defined, and the first bin is assigned to the first vibration according to the state determined from the estimated value of the modulation signal Smod, and the second bin is assigned to the second vibration according to the state determined from the estimated value of the modulation signal Smod. A first average waveform of the first vibration in the first bin and a second average waveform of the second vibration in the second bin are formed. Then, these first and second average waveforms are subtracted from the composite signal S in each state of the first and second average waveforms to form the modulation signal Smod. The method may be applied, for example, to suppress cardiogenic vibrations in an impedance respiration recording signal, and the cardiogenic vibrations and the impedance respiration recording signal form a transthoracic impedance signal.

[0029] Figure 3 depicts an embodiment of the method according to the present invention.

[0030] At 302, a measuring means device may be used or configured to collect measurement data belonging to a respiration measurement, or an information source such as a database including measurement data belonging to a respiration measurement may be accessed to obtain the measurement data.

[0031] At 304, respiratory measurement data corresponding to a plurality of respiratory cycles are obtained. Such respiratory data may include volume and respiratory flow rate measurement data corresponding to the flow rate and volume of respiration, or respiratory flow rate and time measurement data corresponding to respiratory flow rate and respiratory time, or volume and time measurement data corresponding to the volume over the period of respiration, and such data includes measurement data of measurements from a plurality of respiratory cycles over a period of time. The respiratory measurement data may include respiratory cycles over a period of at least several minutes, several hours such as 5 hours or more, or a period such as nighttime sleep time, and the measurement of respiratory cycles over a period of time is preferably continuous and consecutive within a preferred time window such as at least a specific sleep stage. The respiratory measurement data to be analyzed must belong to only a single person, and preferably, the respiratory cycles are composed of continuous respiratory cycles over a continuous period such as overnight sleep or other such sufficient periods of sleep at any time during the day. In addition, respiratory measurements belonging to respiratory cycles during different sleep stages may be used, and the use of respiratory measurement data belonging to a plurality of respiratory cycles over a plurality of sleep stages may result in a more robust data quality method. Alternatively, respiratory measurement values belonging to one or more preferred specific sleep stages may be obtained and used. Alternatively, the respiratory measurement data may belong to continuous respiratory cycles over a continuous period during a non-sleep stage such as the awake state. Different people, or even the same person at different times, may have different variations in their periodic breathing, and thus the method is preferably performed using respiratory measurement data belonging to respiratory measurements performed on a person within a certain time frame, such that the measurements are essentially continuous or the respiratory cycles include continuous respiratory cycles with respect to time.

[0032] Although respiratory measurements are generally referred to herein, the respiratory measurement data can be obtained from measurement data belonging only to the exhalation phase of the respiratory cycle.

[0033] Obtaining respiratory measurement data may also include a threshold of the amount of respiratory cycle measurements required, i.e., the amount of measurement data of respiratory cycles and / or a sufficient time span necessary for the respiratory measurement data to be considered analyzable or sufficient for analysis by a method. For example, such a threshold may include tidal breath phase flow-volume, flow-time, or time-volume measurements of respiratory cycles over a period of at least 5 hours. An increase in the amount of measurement data can increase the accuracy of the analysis of the variability of periodic breathing over time, but the sufficiency of the data as well as the type of data (e.g., whether it belongs to respiratory cycles during some sleep stages and / or whether it belongs to respiratory cycles during the waking state) may vary, for example, considering the use of the method, as well as the quality or type of the measurement data, and further the desired accuracy of the method, which those skilled in the art will understand.

[0034] Respiratory measurement data of tidal breath phase flow-volume, flow-time, or time-volume measurements of respiratory cycles may be measured by impedance respiratory recording measurement means as described above. Several other realizable measurement means and techniques for measuring respiratory volume, time, and / or flow rate data typically include sensor measurement devices arranged on a bed, mattress, blanket, etc., based on volume measurements such as electrocardiography. Some further realizable measurement devices include wearable devices such as clothes or straps that measure elongation, and as an example, inductance plethysmography (RIP) may be mentioned. Further, Doppler radar sensor devices (described, for example, in DOI: 10.1109 / TMTT.2013.2256924), photoelectric plethysmography (by, for example, PneumaCare), electromagnetic induction plethysmography (by, for example, VoluSense), and devices based on accelerometers may be used. Clearly, other suitable means for obtaining flow-volume, flow-time, or time-volume measurement values of respiratory cycles from periodic breathing may also be used.

[0035] The measurement data preferably includes TB respiratory cycle measurements performed on a single person at rest, such as a person during sleep, regardless of whether it is at night or during the day. The method may be performed on an existing dataset, such as by obtaining the measurement data for using the method from a database, cloud, or other such information source. Therefore, the method does not necessarily include performing actual measurements to collect the measurement data. Also, the respiratory measurement data may be obtained from a dataset belonging only to the measurement of the exhalation phase of a person. Clearly, respiratory measurement data belonging to multiple respiratory cycles may also be obtained from a dataset corresponding to the respiratory measurement data of multiple persons, and the data is filtered so that only the relevant respiratory cycle data belonging to a single person is selected.

[0036] The measurement data may also be pre-processed or processed at this point, for example, considering signal filtering, to remove cardiogenic oscillations from the composite signal of flow-volume, flow-time, or time-volume respiratory measurements. The measurement data may also be pre-processed or processed at this point to discard data portions distorted by movement, conversation, crying, coughing, etc. that may have occurred during the measurement. Further, the measurement data may be processed or pre-processed to improve measurement accuracy by applying one or more calibration coefficients or calibration models to the composite signal or filtered signal of flow-volume, flow-time, or time-volume respiratory measurements.

[0037] At 306, data corresponding to the inhalation phase of the respiratory cycle may be excluded. This item of the method is not essential when the measurement data includes only exhalation phase measurement data, for example, when the inhalation phase is not measured and omitted, or when the respiratory measurement data is provided to the method such that the respiratory measurement data includes only exhalation phase measurement data.

[0038] At 308, the measurement data may be normalized such that the exhaled volume or time is normalized to a fixed range such as 0 to 100%. Further, the measurement data is normalized such that the time integral of the expiratory flow rate is normalized such that it is equal to the time integral of the exhaled volume. Optionally, the measurement data may already be in a normalized form, in which case this item of the method is not essential. However, normalization of the data is not essential, and the measurement data may include measurement data that does not pertain to absolute measurements of respiratory volume or the flow rate of air from the lungs. The measurement data is, for example, calculated from the measured respiratory flow rate and time, t ptef / t e (t ptef = time to maximum periodic expiratory flow rate, t e = total duration of exhalation) ratio, or calculated from the measured respiratory flow rate and volume, V ptef / V e (V ptef = volume at maximum periodic expiratory flow rate, V e = volume at maximum periodic expiratory flow rate) ratio, and may be in a relative form. The ratios t ptef / t e and V ptef / V e are described in the prior art, for example, in the publication “An Official American Thoracic Society / European Respiratory Society Statement: Pulmonary Function Testing in Preschool Children.” American Journal of Respiratory and Critical Care Medicine, 175(12), pp. 1304 - 1345.

[0039] At 310, a moving average window may be used to calculate the average value of the respiratory cycle and its expiratory phase. This is an optional item of the method, but it has the benefit of making the calculation of the correlation between respiratory cycles more efficient, because the correlation can be calculated from a plurality of averaged respiratory cycles rather than all individual respiratory cycles, and the individual respiratory cycles may be much more numerous. An example of an averaging scheme may include calculating the average of 20 consecutive individual respiratory cycles and representing them as one averaged respiratory cycle.

[0040] At 312, calculate the variation in the first half of the exhaled volume between individual or averaged respiratory cycles over time. The variation may be calculated, for example, from the correlation between individual or averaged expiratory phases of the flow-volume, flow-time, or time-volume measurements of the respiratory cycle corresponding to a period of respiratory cycles. Also, other means may be used to calculate the variation between individual and / or averaged expiratory phases of the flow-volume, flow-time, or time-volume measurements of the respiratory cycle. Examples of the variation between averaged expiratory phases of the respiratory cycle on the flow-volume scale are shown in FIGS. 5 to 7.

[0041] At 314, the calculated correlation and / or the calculated variation may be used to determine the variation in exhalation during periodic breathing. The level of variation in the first half of the exhaled volume of the expiratory phase has been shown to be related to the presence of airway obstruction. For example, a lower level of variation in the expiratory phase indicates the presence of some airway obstruction, while a higher level of variation in the expiratory phase indicates healthy periodic breathing. Thus, this may be used as a basis for diagnosing lung diseases such as asthma. Similarly, the determined level of variation in the expiratory phase may be used to determine drug or treatment efficiency. Clearly, this step of the method is not essential to the method, but provides examples of some practical applications of the present invention.

[0042] The method of the present invention is preferably a computer-implemented method and may be performed by a computer, a computer network, or similar computing means. The apparatus of the present invention may use impedance pneumography measurement means according to FIG. 1 or FIG. 2, or other such described measurement means for measuring the flow rate and volume of respiration, or the flow rate and time of respiration, or the time and volume of respiration over a period of time, and uses computing means such as a computer, a computer network, etc., at least functionally connected to the measurement means, to collect measurement data from the measurement means and perform an analysis of the variation in the expiratory phase of the flow rate-volume, flow rate-time, or time-volume measurement of the respiratory cycle. The variation between the expiratory phases of the respiratory cycle is analyzed from the measurement data in the range of the first half of the expiratory volume of the expiratory phase of the respiratory cycle. The signal analysis as described may also be performed by computing means, a computer network, etc.

[0043] FIG. 4 depicts a figure illustrating the p-values of the comparison between the measurements of two groups of samples. The first group included 70 patients aged 2.5 years (0. - 5.7 years, median and range) with lower airway obstruction in the presence of at least 3 emergency physicians, from which a sample of 60 measurements of people in the group who had discontinued ICS medication for 4 weeks was obtained. The second group, against which the samples of the first group were compared, included 39 healthy controls aged 4.3 years (1.5 - 6.0 years, median and range), with a total of 80 measurements. Linear correlations were calculated between all TB flow rate-volume measurements over different ranges. The variation was evaluated as the interquartile range (r15 - 45IQR) of the correlation values for each overnight record. The p-values were calculated using the Wilcoxon rank sum test between the two groups. From the different ranges calculated herein, it is clear that the variation in the correlation of the measurements in the range of 15 - 45% significantly indicates the difference between the measured values of the samples of the first group and the second group, as indicated by the p-values.

[0044] The measured values include TBFV measured values obtained over time from multiple people during sleep, regardless of sleep stage. As described, measured values in the range of 15 - 45% of the exhaled volume best show the difference between the healthy group and the asthma patient group, although significant differences can also be found in the range of 10 - 50% or 20 - 40%. Therefore, the first half of the volume or time of exhalation in the respiratory cycle may also refer to other ranges, with the range not exceeding about 60% at most.

[0045] Clinical evidence shows that the variability inherently present in periodic breathing decreases in the presence of obstructive airway diseases such as asthma or chronic obstructive pulmonary disease (COPD). This change results from the response of the respiratory neural control center that integrates complex sensory information (pulmonary stretch receptors, chemoreceptors, etc.) modulated by dyspnea. As shown in Figure 7, the small variability in the expiratory phase in the presence of asthma is clearly more prominent in the initial part than the latter part of the expiratory flow - volume curve, compared to the initial parts of the expiratory flow - volume curves in Figures 5 and 6. This is probably due to the fact that at the start of exhalation, the activation of the inspiratory muscles (diaphragm, intercostal muscles) does not suddenly end. Instead, the activity of the inspiratory muscles continues, decreases during the first part of exhalation, and in the latter part of exhalation, exhalation becomes completely passive, driven only by the mechanical recoil of the lungs and chest wall. This means that the initial exhalation is affected by respiratory neural control sensitive to airway obstruction, and thus, when aiming to detect the presence of airway obstruction, the initial exhalation is better for evaluating the variability of periodic breathing.

[0046] Figures 5 - 7 illustrate TB measurements obtained from several people during sleep, presented as flow - volume curves, regardless of sleep stage. The measurement data can also be presented as flow - time or volume - time curves. For clarity, the expiratory phase curve of the depicted respiratory cycle includes the averaged expiratory phase of the respiratory cycle.

[0047] In the figure, the preferred range of the first half, specifically 15 - 45% of the exhaled volume in the expiratory phase of the respiratory cycle, is marked with two vertical lines to emphasize the relatively large amount of variability of the respiratory cycle in that range compared to the expiratory phase at rest.

[0048] Figure 5 depicts a graph illustrating a plurality of expiratory flow-volume curves (i.e., excluding inhalation) obtained from a single person during continuous sleep measurements over a certain time frame. In this case, the samples include asthmatic patients during inhalation corticosteroid (ICS) dosing. From the data, significant respiratory variability over time can be detected in the range of the first half of the expiratory volume of exhalation.

[0049] Figure 6 depicts another graph illustrating a plurality of expiratory flow-volume curves (excluding inhalation) obtained from a single person during continuous sleep measurements over a certain time frame. In this case, the samples include healthy subjects without lung disease. From the data, significant respiratory variability over time can be detected in the range of the first half of the expiratory volume of exhalation.

[0050] Figure 7 depicts another graph illustrating a plurality of expiratory flow-volume curves (excluding inhalation) obtained from a single person during continuous sleep measurements over a certain time frame. In this case, the samples include asthmatic patients who have discontinued ICS dosing for 4 weeks. From the data, very little respiratory variability over time can be detected in the range of the first half of the expiratory volume of exhalation.

[0051] The scope of the present invention is determined by the appended claims and their equivalents. The disclosed embodiments are constructed only for illustrative purposes, and those skilled in the art will again understand the fact that the innovative pivot points described herein will encompass further embodiments, combinations of embodiments, variations, and equivalents that are better suited to each specific use case of the invention.

Claims

1. A method for measuring respiratory changes using measurement data corresponding to a plurality of measured respiratory cycles in the form of respiratory flow rate and volume over a period of time, or respiratory flow rate and time, or respiratory time and volume, wherein the measurement data belongs to at least the measurement of the expiratory phase of the respiratory cycle, the method comprises analyzing the variation in the expiratory phase of the flow-volume, flow-time, or time-volume measurement of the respiratory cycle, and the measurement is a measurement over a period of time, the variation between the expiratory phases of the respiratory cycle is analyzed from the measurement data in the range of the first half of the expiratory volume of the expiratory phase of the respiratory cycle, the variation is used to detect the presence of airway obstruction, the measured respiratory cycle is analyzed from the measurement data in the range of 15-45% of the expiratory volume of the expiratory phase of the respiratory cycle. A method.

2. The method according to claim 1, wherein the respiratory cycles of the measurement data are time-averaged using a moving average window.

3. The method according to claim 1 or 2, wherein the method includes signal processing for removing cardiogenic oscillations from some of the measurement signals of the measurement data.

4. The method according to any one of claims 1 to 3, wherein the measurement data is processed to discard data portions distorted by exercise, conversation, crying, coughing, or the like.

5. The method according to any one of claims 1 to 4, wherein the method includes improving measurement accuracy by applying one or more calibration coefficients or calibration models to some of the measurement signals of the measurement data.

6. The method according to any one of claims 1 to 5, wherein the respiratory cycle includes continuous respiratory cycles over a period of time.

7. The method according to any one of claims 1 to 6, wherein the respiratory cycles corresponding to respiratory flow rate and volume, or respiratory flow rate and time, or respiratory time and volume belong to the measurement from continuous respiratory measurements.

8. The method according to any one of claims 1 to 7, wherein the period includes at least several minutes, several hours, or nighttime sleep time.

9. The method according to any one of claims 1 to 8, wherein the measurement data is normalized such that the expiratory volume or time is normalized to a certain range such as 0-100%.

10. The method according to any one of claims 1 to 9, wherein the measurement data is normalized such that the time integral of the expiratory flow rate is equal to the time integral of the expiratory volume, and the expiratory flow rate is normalized.

11. An apparatus for measuring respiratory changes, comprising measurement means for measuring a plurality of respiratory cycles in the form of respiratory flow rate and volume, or respiratory flow rate and time, or respiratory time and volume, over a period of time, such measurements belonging at least to the measurement of the expiratory phase of said respiratory cycles, The apparatus further comprises computing means arranged to analyze the variation in the expiratory phase of the flow rate-volume, flow rate-time, or time-volume measurements of said respiratory cycles, said measurements being measurements over a period of time, The variation between the expiratory phases of said respiratory cycles is analyzed from measurement data in the range of the first half of the expiratory volume of the expiratory phase of said respiratory cycles, Said variation is used to detect the presence of airway obstruction, An apparatus, wherein the measured respiratory cycles are analyzed from measurement data in the range of 15% to 45% of the expiratory volume of the expiratory phase of said respiratory cycles.

12. The apparatus according to claim 11, wherein said measurement means comprises impedance respiratory recording means.

13. The impedance respiratory recording means according to claim 12, comprising using at least one electrode configured to contact the arm of a human body and at least one electrode configured to contact the chest of a human body, and determining an impedance signal change related to a change in respiratory volume or a time derivative impedance signal change related to respiratory flow rate.

14. A computer program product embodied in a non-transitory computer-readable medium, comprising computer code for causing a computer to execute the method according to claim 1.

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