Method and device 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 respiration measurement. Specifically, but not exclusively, the present invention relates to methods for measuring and detecting changes in a person's respiration. [Background technology]

[0002] Pulmonary function measurement is the basis for monitoring and diagnosing several lung diseases. However, subjects with limited ability to cooperate due to developmental stage or mental or physical limitations cannot perform regular pulmonary function tests, which require demanding breathing maneuvers. For example, diagnosing asthma in preschool children is difficult because traditional pulmonary function tests are not suitable.

[0003] Measurements during spontaneous periodic breathing (TB) require minimal cooperation and are therefore suitable for small children and infants. There is extensive research suggesting that parameters derived from the TB flow curve or flow velocity-volume (TBFV) curve are altered in a critical manner with obstructive respiratory disease in young patients. Studies have shown, for example, that TB parameters are related to forced expiratory volume in 1 second (FEV1), airway resistance, bronchodilator response, and methacholine challenge and can be used to differentiate pathological respiratory conditions.

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

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

[0006] An advantage of the present invention is that it enables one to measure a person's respiration in a manner that can be used to detect changes in the person's respiration that may then be used to diagnose the cause of the detected respiration changes.

[0007] According to one aspect of the invention, there is provided 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, or respiratory flow rate and time, or respiratory time and volume, over a period of time, said measurement data belonging to at least measurements of the expiratory phase of a respiratory cycle, analyzing the variability of the expiratory phase of a flow-volume, flow-time, or time-volume measurement of the respiratory cycle, the measurement being over a period of time; A method in which the variability during the expiratory phase of the respiratory cycle is analyzed from measurement data of the first half range of the expiratory volume of the expiratory phase of the respiratory cycle.

[0008] According to another aspect of the invention there is provided an apparatus for measuring changes in breathing, comprising measuring means for measuring respiratory flow and volume, or respiratory flow and time, or respiratory time and volume, over a period of time, such measurements belonging to at least the expiratory phase of the respiratory cycle; Analyze the variability of the expiratory phase of the respiratory cycle in flow-volume, flow-time, or time-volume measurements, where the measurements are taken over a period of time. and further comprising a computing means arranged so as to The variability during the expiratory phase of the respiratory cycle is analyzed from the measurement data of the first half range of the expiratory volume during the expiratory phase of the respiratory cycle.

[0009] According to another aspect of the invention, a computer program product embodied in a non-transitory computer readable medium comprising computer code for causing a computer to perform the method of claim 1.

[0010] As briefly described above, the usefulness of different aspects of the present invention stems from a number of issues that are dependent on each particular embodiment.

[0011] The term "several" as used herein may refer to any positive integer starting with one (1). The term "plurality" may refer to any positive integer starting with two (2), respectively.

[0012] The term "exemplary" is used herein to refer to an example or example feature and not the only or only preferred option.

[0013] The expression "tidal volume" is the volume that corresponds to the amount of air displaced during one normal inspiration or expiration. The expression "periodic breathing" is therefore used to refer to normal breathing in which the volume is the tidal volume.

[0014] The expression "respiratory cycle" is used to refer to a cycle of breathing that includes both expiration and inspiration. The expression "expiratory phase" is used to refer to the expiration phase of the respiratory cycle, excluding the inspiration phase of the respiratory cycle.

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

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

[0017] [Figure 1] 1 depicts an embodiment of a measurement means device suitable for the method according to the invention. [Diagram 2] 2 depicts another embodiment of a measuring means device suitable for the method according to the invention; [Diagram 3] 1 shows a flow diagram of an embodiment of a method according to the present invention; [Figure 4] 1 depicts a diagram illustrating the p-value from a Wilcoxon rank sum test between the variability of TBFV measurements of two groups, the first group including TBFV measurement data of asthmatic patients and the second group including TBFV measurement data of healthy individuals. [Diagram 5] 1 depicts a graph illustrating multiple flow-volume curves obtained from a person during continuous sleep monitoring over a period of time. [Figure 6] 1 depicts another graph illustrating multiple flow-volume curves obtained from a person during continuous sleep monitoring over a time frame. [Figure 7] 1 depicts another graph illustrating multiple flow-volume curves obtained from a person during continuous sleep monitoring over a time frame. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] Figure 1 depicts an embodiment of a measuring means device suitable for the method according to the invention. An impedance pneumotachography device 30 is connected to a sensor 11 attached to the right arm 2 and a sensor 12 attached to the left arm 3 of the human body 1 via a connector interface 31. The sensors 21, 23 are attached to the lateral chest or mid-axillary line on both sides of the human body 1. The sensor elements include electrodes and cables 13, 14, 15, 16 that convey electrical signals to the connector interface 31. The mid-axillary line is defined as a coronal line on the torso between the anterior and posterior axillary lines. The sensor placement may vary a few centimetres from the mid-axillary line.

[0019] The sensors 11, 12, 21, 22, the cables 13, 14, 15, 16, the interface 31, and the device 30 are components of an impedance pneumotachography measurement system. The sensors 11, 12, 21, 22 may include lettering, color, or other indicia to help a person using the impedance pneumotachography system connect the sensors to the correct position on the human body 1. The sleeves 41, 41 may include indicia to distinguish between the left arm 2 and the right arm 3. The size or shape of the sleeves 41, 42 may also prevent a user from placing the sensors 11, 12 in an incorrect position.

[0020] In one embodiment of the apparatus, the interface 31 configured for the instrument 30 is arranged to include indications of correct installation procedures, such as color coding or letters. The instrument 30 may also include a display to inform the user of the procedures. Software implemented in the instrument 30 may also include code to provide assistance information to the user, confirming correct installation procedures or indicating any errors during installation or operation. One example of an error condition is measurement data being outside of a predetermined range.

[0021] The device 30 may include an interface to transmit impedance pulmonary information to another device, such as a computer or other medical device. In one embodiment, the device 30 is arranged to convert the changes in thoracic impedance caused by breathing into a high-level respiratory signal that can be used for other applications. The device 30 may also be integrated into another medical device.

[0022] FIG. 2 depicts another embodiment of a measuring means device suitable for the method according to the invention, in which the sensors 11, 12 are arranged to be part of the 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 currents from passing through the skin and thus contributing to false values. The bioimpedance values ​​are measured through the upper axillary line or from the preferred route at the top of the lungs. The sleeve may be part of a shirt or jacket 43 arranged to be used in an impedance pneumotachography system. The sleeve may be in the form of an armband. In one embodiment, the thickness of the armband keeps 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] The sensors 11, 12, 21, 22 may be arranged in different configurations. In a 4-pole bioimpedance measurement, four electrodes are used, two for supplying a constant amplitude alternating current and two for sensing voltage. A constant voltage may also be used while the current is measured. The electrodes may for example be measuring a voltage difference measured from both arms, or the electrodes may be supplying a current to allow the impedance measurement. Electrode pairs for the same parameter are always positioned at a distance from each other. Supplying a current and measuring a voltage may be combined in a single sensor as an electrode pair.

[0024] In impedance pulmonary graphy, a small high frequency current is passed through a pair of skin electrodes and another pair of electrodes is used to record the generated voltage, which is proportional to the impedance and therefore to the lung volume. Cardiogenic oscillations can be removed by filtering techniques described in Finnish patent application FI20115110, which is incorporated herein by reference.

[0025] The placement of electrodes 11, 12 on the arms 2, 3 significantly improves the linearity of the impedance versus lung volume measurements, especially at the lower lung volume scales. One exemplary electrode placement is between the biceps and triceps. This placement of the electrodes on the arms is referred to as supra-axillary placement. Preventing skin contact between the arms and sides improves the measurements since skin contact does not contribute to the bioimpedance value.

[0026] An example method for filtering cardiogenic oscillations from a thoracic impedance signal is presented herein.

[0027] The vibration signal Sosc is suppressed by providing a composite signal S including the vibration signal Sosc and a modulated signal Smod; high pass filtering the composite signal S with a high pass filter to generate an estimate of the vibration signal Sosc and an estimate of the modulated signal Smod; the estimate of the vibration signal Sosc includes a first oscillation during a first state of the modulated signal Smod and a second oscillation during a second state of the modulated signal Smod; defining 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 a state determined from the estimate of the modulated signal Smod and assigning the second bin to the second oscillation according to a state determined from the estimate of the modulated 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 vibration 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 may be suppressed from a composite signal S including the vibration signal Sosc and the modulation signal Smod without removing any portion of the modulation signal Smod. The composite signal S is high pass filtered to generate an estimate of the vibration signal Sosc and an estimate of the modulation signal Smod. The estimate of the vibration signal Sosc includes at least 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. A first bin associated with the first state and a second bin associated with the second state are defined, and the first oscillation is assigned to the first bin according to the state defined from the estimate of the modulation signal Smod and the second oscillation is assigned to the second bin according to the state defined from the estimate of the modulation signal Smod. 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 are formed. The first and second average waveforms are then subtracted from the composite signal S at each state of the first and second average waveforms to form a modulated signal Smod. The method may, for example, be applied to suppress cardiogenic oscillations in an impedance pulmonography signal, the cardiogenic oscillations and the impedance pulmonography signal forming a transthoracic impedance signal.

[0029] FIG. 3 depicts an embodiment of a method according to the invention.

[0030] At 302, a measurement means device may be used or configured to collect measurement data pertaining to respiratory measurements, or a source of information, such as a database, containing measurement data pertaining to respiratory measurements may be accessed to obtain the measurement data.

[0031] At 304, respiratory measurement data corresponding to a plurality of respiratory cycles is obtained. Such respiratory data may include air volume and respiratory flow rate measurement data corresponding to respiratory flow rate and volume, or respiratory flow rate and time measurement data corresponding to respiratory flow rate and respiratory time, or air volume and time measurement data corresponding to air volume over a period of breathing, such data including 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 time, such as at least a few minutes, several hours, such as 5 hours or more, or nighttime sleep time, and the measurement of respiratory cycles over a period of time is preferably continuous and consecutive, at least during a preferred time window, such as a particular sleep stage. The respiratory measurement data analyzed should only belong to a single person, and preferably the respiratory cycles are composed of continuous respiratory cycles over a continuous period of time, such as respiratory cycles over a night's sleep, or other such sufficient period 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 multiple respiratory cycles over multiple sleep stages may provide the method with more robust data quality. Alternatively, respiratory measurements belonging to one or more particular sleep stages may be obtained and used, as desired. Alternatively, the respiratory measurement data may belong to a continuous respiratory cycle over a continuous period during a non-sleep stage, such as a wakeful state. Different individuals, or even the same individual at different times, may have different variations in their periodic breathing, and therefore the method is preferably performed with respiratory measurement data belonging to respiratory measurements made on an individual over a time frame, such that the measurements are essentially continuous or the respiratory cycles comprise a continuous respiratory cycle with respect to time.

[0032] Although respiratory measurements are generally referred to herein, respiratory measurement data may be derived from measurements pertaining only to the expiratory phase of the respiratory cycle.

[0033] Obtaining respiration measurement data may also include a threshold for the amount of respiration cycle measurements required, i.e., the amount of measurement data and / or sufficient time span of respiration cycle measurements required for the respiration measurement data to be considered as capable or sufficient to be analyzed by the method. For example, such a threshold may include TB expiratory phase flow rate-volume, flow rate-time, or time-volume measurements of the respiration cycle over a period of at least 5 hours. Those skilled in the art will understand that while an increase in the amount of measurement data may increase the accuracy of the analysis of periodic breathing variations over time, the sufficiency of the data as well as the type of data (e.g., whether it belongs to a respiration cycle during several sleep stages and / or whether it belongs to a respiration cycle during a wakeful state) may vary, for example, taking into account the application of the method and the quality or type of measurement data as well as the desired accuracy of the method.

[0034] Respiratory measurement data of TB expiratory phase flow rate-volume, flow rate-time, or time-volume measurements of the respiratory cycle may be measured with impedance pneumotachography measurement means as described above. Some other possible measurement means and techniques for measuring respiratory volume, time, and / or flow rate data include sensor measurement devices placed on the bed, mattress, blanket, etc., usually based on volume measurements such as ballistocardiography. Some further possible measurement devices include wearable devices such as clothing or straps that measure elongation, one example being inductance respiratory plethysmography (RIP). In addition, Doppler radar sensor devices (e.g. described in DOI:10.1109 / TMTT.2013.2256924), photoelectric plethysmography (e.g. by PneumaCare), electromagnetic induction plethysmography (e.g. by VoluSense), and accelerometer-based devices may be used. Clearly, other suitable means for obtaining flow-volume, flow-time, or time-volume measurements of the respiratory cycle from periodic breathing may also be used.

[0035] The measurement data preferably includes TB respiratory cycle measurements made on a single person at rest, such as a person asleep, whether at night or during the day. The method may be performed on an existing data set, such as by obtaining measurement data for using the method from a database, cloud, or other such source. Thus, the method does not have to include performing actual measurements to collect the measurement data. The respiratory measurement data may also be obtained from a data set belonging to measurements of only the exhalation phase of a person. Obviously, respiratory measurement data belonging to multiple respiratory cycles may also be obtained from a data set corresponding to respiratory measurement data of multiple people, the data being filtered such that relevant respiratory cycle data belonging only to a single person is selected.

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

[0037] At 306, data corresponding to the inhalation phase of the respiratory cycle may be excluded. This section of the method is not required if the measurement data only includes measurement data for the exhalation phase, e.g., if the inhalation phase is not measured and is omitted, or if the respiratory measurement data is provided to the method such that the respiratory measurement data only includes measurement data for the exhalation phase.

[0038] At 308, the measurement data may be normalized such that the expiratory volume or time is normalized to a certain range, such as 0-100%. Furthermore, the measurement data is normalized such that the expiratory flow rate is normalized such that the time integral of the expiratory flow rate is equal to the time integral of the expiratory volume. Optionally, the measurement data may already be in a normalized form, in which case this item of the method is not required. However, normalization of the data is not required, and the measurement data may include measurement data that does not belong to an absolute measurement of the respiratory volume or the flow rate of air out of the lungs. The measurement data may be, for example, a time-dependent measurement of the expiratory volume, calculated from the measured respiratory flow rate and time, t ptef / t e (t ptef = time to peak cyclic expiratory flow rate, t e = total duration of expiration) ratio, or calculated from the measured respiratory flow rate and volume, V ptef / V e (V ptef = volume at peak expiratory flow rate, V e The ratio may be in a relative form, such as the ratio of air volume at maximum periodic expiratory flow rate (t) to air volume at maximum periodic expiratory flow rate (t). ptef / t e and V ptef / V e Measurement of pulmonary function has been described in the prior art, e.g., 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 averaging 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 has the benefit of making the calculation of correlation between respiratory cycles more efficient, since the correlation may be calculated from multiple averaged respiratory cycles rather than all individual respiratory cycles, which 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, the variability of the first half of the expiratory volume of the expiratory phase between individual or averaged respiratory cycles over time is calculated. The variability may be calculated, for example, from correlation between individual or averaged expiratory phases of flow-volume, flow-time, or time-volume measurements of respiratory cycles corresponding to respiratory cycles over a period of time. Other means for calculating the variability between individual and / or averaged expiratory phases of flow-volume, flow-time, or time-volume measurements of respiratory cycles may also be used. Examples of the variability between averaged expiratory phases of respiratory cycles on a flow-volume scale are shown in Figures 5-7.

[0041] At 314, the calculated correlation and / or the calculated variability may be used to determine the variability of the exhalation during periodic breathing. The level of variability in the first half of the exhalation phase has been shown to be associated with the presence of airway obstruction, e.g. a lower level of variability in the exhalation phase indicates the presence of some airway obstruction, while a higher level of variability in the exhalation phase indicates healthy periodic breathing. This may therefore be used as a basis for lung disease diagnosis, such as diagnosing asthma. Similarly, the determined level of variability in the exhalation phase may be used to determine drug or treatment efficiency. Obviously, this step of the method is not essential to the method, but provides an example of some practical applications of the invention.

[0042] The method of the invention is preferably a computer-implemented method and may be performed on a computer, a computer network or similar computing means. The device of the invention may use impedance pulmonary measurement means according to Fig. 1 or Fig. 2 or other such described measurement means for measuring the respiratory flow rate and volume, or the respiratory flow rate and time, or the respiratory time and volume, over a period of time, and may use computing means such as a computer, a computer network, at least functionally connected to the measurement means, to collect measurement data from the measurement means and to perform an analysis of the variability of the expiratory phase of the flow rate-volume, flow rate-time or time-volume measurement of the respiratory cycle, the variability during the expiratory phase of the respiratory cycle being analyzed from the measurement data of the first half of the expiratory volume range of the expiratory phase of the respiratory cycle. The signal analysis as described may also be performed on a computing means, a computer network or the like.

[0043] Figure 4 depicts a diagram illustrating the p-values ​​of the comparison between measurements of samples from two groups. The first group included 70 patients aged 2.5 years (0.-5.7 years, median and range) with lower airway obstruction attended by at least three emergency physicians, from whom a sample of 60 measurements of those in the group who had stopped ICS medication for 4 weeks were obtained. The second group, to which the samples from 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-volume measurements at different ranges. Variability was evaluated as the interquartile range (r15-45IQR) of the correlation values ​​for each overnight recording. p-values ​​were calculated using the Wilcoxon rank sum test between the two groups. From the different ranges calculated herein, it is clear that a variation in the correlation of the measurements ranging from 15 to 45% significantly indicates a difference between the measurements of the samples of the first and second groups, as indicated by the p-values.

[0044] The measurements include TBFV measurements taken over time from multiple individuals during sleep, regardless of sleep stage. As stated, measurements in the range of 15-45% of the exhaled volume best show the difference between healthy and asthmatic groups, but significant differences may also be found in the range of 10-50% or 20-40%. Thus, the first half of the exhaled volume or time of the respiratory cycle may refer to other ranges, with the range not exceeding a maximum of about 60%.

[0045] Clinical experimental evidence indicates that the variability inherently present in periodic breathing is reduced in the presence of obstructive airway diseases such as asthma or chronic obstructive pulmonary disease (COPD). This change results from the reaction of the respiratory nervous control center, which integrates complex sensory information (pulmonary baroreceptors, chemoreceptors, etc.) modulated by dyspnea. As shown in Figure 7, the small amount of variability in the expiratory phase in the presence of asthma is clearly more pronounced in the early part of the expiratory flow-volume curve than in the later part, compared to the early part of the expiratory flow-volume curve in Figures 5 and 6. This is probably due to the fact that at the start of expiration, the activation of the inspiratory muscles (diaphragm, intercostal muscles) does not end abruptly. Instead, the activity of the inspiratory muscles continues and declines during the first part of expiration, and in the later part of expiration, expiration becomes completely passive, driven only by the mechanical recoil of the lungs and thorax. This means that early expiration is influenced by respiratory neural control that is sensitive to airway obstruction and therefore is a better way to assess periodic respiratory variability if the aim is to detect the presence of airway obstruction.

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

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

[0048] FIG. 5 depicts a graph illustrating multiple expiratory flow rate-volume curves (i.e. excluding inspiration) obtained from a single person during continuous sleep measurements over a time frame. In this case, the sample includes an asthmatic patient on inhaled corticosteroid (ICS) medication. From the data, significant respiratory variability over time can be detected in the early range of the expiratory volume.

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

[0050] Figure 7 depicts another graph illustrating multiple expiratory flow-volume curves (excluding inspiration) obtained from a single individual during continuous sleep measurements over a time frame. In this case, the sample includes an asthmatic patient who has been off ICS medication for 4 weeks. From the data, very little respiratory variability over time can be detected in the early range of the expiratory volume.

[0051] The scope of the present invention is determined by the appended claims together with their equivalents. Those skilled in the art will again appreciate the fact that the disclosed embodiments have been constructed for illustrative purposes only, and that the innovative principles described herein will encompass further embodiments, combinations of embodiments, modifications, and equivalents that are better suited to each particular use case of the invention.

Claims

1. 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, or respiratory flow rate and time, or respiratory time and volume, over a period of time, said measurement data belonging to measurements of at least the expiratory phase of said respiratory cycles, the method comprising analysing variability in the expiratory phase of a flow-volume, flow-time or time-volume measurement of the respiratory cycle, the measurement being over a period of time; The variation during the expiratory phase of the respiratory cycle is analyzed from the measurement data of the expiratory volume in a first half range of the expiratory phase of the respiratory cycle; The variability is used to detect the presence of an airway obstruction; The measured respiratory cycle is analyzed from measurement data in a range of 15-45% of the expiratory volume of the expiratory phase of the respiratory cycle.

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

3. The method according to claim 1 or 2, wherein the method comprises signal processing for removing cardiogenic vibrations from some 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 parts distorted by movement, talking, crying or coughing or the like.

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

6. The method of any one of claims 1 to 5, wherein the breathing cycle comprises a continuous breathing cycle 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 measurements from a continuous respiratory measurement.

8. The method of any one of claims 1 to 7, wherein the period of time comprises at least a few minutes, a few hours, or a night's sleep period.

9. The method according to any one of claims 1 to 8, wherein the measurement data is normalised such that the expiratory volume or time is normalised 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 normalised such that the expiratory flow rate is normalised such that the time integral of the expiratory flow rate is equal to the time integral of the expiratory volume.

11. 1. An apparatus for measuring changes in breathing, comprising measuring means for measuring respiratory flow and volume, or respiratory flow and time, or respiratory time and volume, over a period of time, wherein such measurements belong at least to the expiratory phase of the breathing cycle; the apparatus further comprises computing means arranged to analyse variability in the expiratory phase of a flow-volume, flow-time or time-volume measurement of the respiratory cycle, the measurement being over a period of time; The variation during the expiratory phase of the respiratory cycle is analyzed from the measurement data of the expiratory volume in a first half range of the expiratory phase of the respiratory cycle; The variability is used to detect the presence of an airway obstruction; The measured respiratory cycle is analyzed from measurement data in a range of 15-45% of the expiratory volume of the expiratory phase of the respiratory cycle.

12. 12. The apparatus of claim 11, wherein the measuring means comprises an impedance pneumothorography means.

13. 13. The apparatus of claim 12, wherein the impedance pneumotachography means includes using at least one electrode configured for skin contact with an arm of the human body and at least one electrode configured for skin contact with a chest of the human body, and determining impedance signal changes related to respiratory volume changes or time-differential impedance signal changes 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 perform the method of claim 1.

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