Signal processing unit and method for determining respiratory signal

Abstract

A signal processing unit and method for determining a respiratory signal. The invention relates to a signal processing unit and a method of determining an estimate for a respiratory signal. The respiratory signal is a measure of the patient's own spontaneous respiratory activity and / or artificial respiration. A sum signal is generated from measurements measured in and / or at a body of a patient, the sum signal including a respiratory signal and a cardiac signal. An intermediate signal is calculated by compensating for the effects of cardiac activity on the sum signal. The reference attenuation signal segments describe an average time variation process of the contribution of the cardiac signal to the intermediate signal. For each heartbeat detected, an intermediate signal segment is generated. An attenuated intermediate signal segment is generated from the intermediate signal segment, for which purpose the adapted attenuated signal segment is applied to the intermediate signal segment. An adapted attenuated signal segment is calculated from the reference attenuated signal segment using at least one quality metric.

Description

TECHNICAL FIELD

[0001] The present invention relates to a signal processing unit and a method of determining an estimate of a respiratory signal. The respiratory signal is a measure of a patient's own respiratory activity and / or of an artificial respiration. The patient's own respiratory activity is caused by his autonomous breathing and / or by an external stimulation of his respiratory muscles. Not only the own respiratory activity but also the artificial respiration causes a patient's lung ventilation. For example, the respiratory signal is required for determining a state of the patient's respiratory muscles or for adapting the artificial respiration to the patient's own respiratory activity. BACKGROUND

[0002] Generally, the respiratory signal cannot be measured directly. Rather, only a signal is measured which results from a superposition of the sought respiratory signal with a cardiological signal and, optionally, with an interfering signal and which is called a sum signal. The cardiological signal is a measure of the patient's heart activity. SUMMARY

[0003] The task on which the present invention is based is to provide a signal processing unit and a method which are able to acquire the respiratory signal from the sum signal better than known signal processing units and methods, wherein the sum signal results from a measurement which has been measured on a patient and comprises a superposition of the respiratory signal and the cardiological signal and wherein an interference can occur at the time of the measurement. In other words: the respiratory signal should be able to be acquired from the sum signal with a higher reliability.

[0004] The task is solved by a signal processing unit having the features of claim 1 and by a method having the features of claim 7. Advantageous design solutions of the signal processing unit according to the invention are advantageous design solutions of the method according to the invention as far as they make sense and vice versa.

[0005] The signal processing unit according to the invention and the method according to the invention are able to determine an estimate for a respiratory signal. The respiratory signal to be estimated is related to a patient's lung ventilation, i.e. to a lung ventilation and expiration. The lung ventilation is caused by the patient's own respiratory activity and / or by an artificial respiration. The patient's own respiratory activity is caused by his autonomous breathing and, in one design solution, additionally or instead by an external stimulation of his respiratory muscles, for example by an artificial respiration or by generating his own respiratory activity in a magnetic field.

[0006] The reference heartbeat period and the usage phase are predefined in a computer-evaluable form. The reference heartbeat period can be used for describing a typical course of a heartbeat, more precisely: of the cardiological signal in the course of the heartbeat period. In the usage phase, an estimate of the respiratory signal is determined.

[0007] The at least one sum signal sensor is capable of measuring a signal generated in and / or at the patient's body, for example by means of measuring electrodes or by means of a measuring instrument in the patient's body. Optionally, a plurality of sum signal sensors is used. In one design variant, the sum signal sensor or the sum signal sensors comprise a plurality of electrodes positioned on the patient's skin. The signal generated at or in the patient's body is generated by the patient's own respiratory activity and / or artificial respiration and by his or her cardiac activity.

[0008] According to the application, the signal processing unit generates at least one sum signal and for this purpose uses (processes) the measured values of the sum signal sensor or of the at least one sum signal sensor. Optionally, the signal processing unit generates a sum signal for each sum signal sensor separately. The or each generated sum signal comprises a superimposition of a respiratory signal and a cardiogenic signal which should be determined approximately. The cardiogenic signal describes the patient's cardiac activity. Optionally, at least one interference signal is included into the sum signal.

[0009] The signal processing unit detects a plurality of heartbeats of the patient made during the use phase using the sum signal or at least one sum signal. Furthermore, the signal processing unit detects a characteristic heartbeat period for each heartbeat detected separately. The heartbeat occurs in this heartbeat period. In this heartbeat period, the sum signal is essentially prescribed by the cardiogenic signal, i.e. over the entire heartbeat period or at least a part of it, while outside the heartbeat period it is essentially prescribed by the respiratory signal. The corresponding applies to the reference heartbeat period as well.

[0010] The signal processing unit generates an intermediate signal. For generating the intermediate signal, the signal processing unit at least approximately computationally compensates the influence of the cardiac activity, i.e. the cardiogenic signal, on the sum signal, for example by subtraction. Preferably, the intermediate signal is the result of this compensation.

[0011] The signal processing unit determines at least one reference attenuation signal segment. In a first alternative, the signal processing unit calculates the reference attenuation signal segment; in a second alternative, the signal processing unit determines the reference attenuation signal segment by reading access to a data store. This or each determined reference attenuation signal segment is related to the average time course of the contribution of the cardiogenic signal to the intermediate signal, i.e. to the contribution within a predefined reference heartbeat period. The reference attenuation signal segment relates to the reference heartbeat period and is at least approximately applicable to a multitude of heartbeat periods of this patient.

[0012] The respiratory signal to be determined relates to the use phase. For each heartbeat detected falling into the use phase, the following steps are performed:

[0013] - As already mentioned, for each detected heartbeat a characteristic heartbeat period is detected. The signal processing unit produces an intermediate signal segment as a segment of the intermediate signal. The intermediate signal segment is located in the heartbeat period of the heartbeat and is, for example, that segment of the intermediate signal which falls into the heartbeat period. For each detected heartbeat, thus, an intermediate signal segment is produced, respectively.

[0014] - The signal processing unit produces for each detected heartbeat a damped intermediate signal segment, respectively.

[0015] - For producing the damped intermediate signal segment, the signal processing unit applies, in case of the first alternative, the reference damping signal segment and, in case of the second alternative, the adapted damping signal segment to the intermediate signal segment.

[0016] The damped intermediate signal segment for the detected heartbeat has the following property: The influence of the cardiogenic signal on the damped intermediate signal segment is less than or at most as great as the influence of the cardiogenic signal on the (undamped) intermediate signal segment, but not greater. Ideally, the cardiogenic signal has no influence on the damped intermediate signal segment at all.

[0017] The signal processing unit combines the damped intermediate signal segments into the sought estimate for the respiratory signal. For this composition, the signal processing unit uses the detected characteristic heartbeat moments. The damped intermediate signal segments are thus composed in a time-correct manner. Optionally, gaps between adjacent damped intermediate signal segments are connected to each other using corresponding segments of the intermediate signal.

[0018] The signal processing unit calculates at least one of four quality measures. Three of the four quality measures describe the respective reliability of the following determinations and calculations:

[0019] - The reliability with which the or each sum signal sensor is used to measure the respective measurement value, and / or the reliability with which the signal processing unit is used to produce the respective sum signal from these measurement values,

[0020] - The reliability with which the signal processing unit is used in the use phase to detect the respective characteristic heartbeat moment of the heartbeat for a plurality of heartbeats,

[0021] - The reference damping signal segment can be used to computationally compensate for the reliability of the contribution of the cardiogenic signal to the intermediate signal in the reference heartbeat period.

[0022] The fourth quality measure assesses the shape of the respective intermediate signal segment for the heartbeat.

[0023] Preferably, the better the respective evaluation, the larger the quality measure. If the better the evaluation, the smaller the quality measure, the following description can be modified accordingly.

[0024] According to a first alternative, the signal processing unit applies a reference attenuation signal segment to the intermediate signal segment. The signal processing unit has previously calculated this reference attenuation signal segment, i.e. preferably by means of samples and preferably before the use phase, using at least one of the four quality measures described above. It is possible for the signal processing unit to continuously update the reference attenuation signal segment during the use phase.

[0025] According to a second alternative, the signal processing unit applies an adapted attenuation signal segment to the intermediate signal segment. The adapted attenuation signal segment for the detected heartbeat is produced by the following steps:

[0026] The signal processing unit calculates the adapted attenuation signal segment, for which it uses the determined, i.e. calculated or determined by reading, reference attenuation signal segment and at least one calculated quality measure.

[0027] The calculation occurs as follows:

[0028] - the adapted attenuation signal segment is smaller or at most exactly as large as the reference attenuation signal segment.

[0029] - the smaller the or each calculated and applied quality measure, the smaller the adapted attenuation signal segment.

[0030] The actual cardiogenic signal is denoted by Sig kar , the actual respiratory signal by Sig res . The estimate for the respiratory signal Sig res produced according to the application is denoted by Sig res，est . In many cases, a measure P aw for the pressure in the airway and / or a measure P es for the pressure in the esophagus can be derived from the measurement values of optional further sensors. From these measures, a pneumatic measure P mus can be deduced, which is likewise a measure for the patient's own respiratory activity. By determining on the one hand an estimate Sig res for the electrical or mechanical respiratory signal Sig res，est and on the other hand the pneumatic measure P mus, the patient's own respiratory activity can be determined with higher reliability than when only one signal is derived, and it is possible to deduce how well the patient's respiratory muscles convert electrical stimulation in the patient's body into pneumatic respiratory activity (neuromechanical efficiency). The invention can also be used in applications where an EMG signal or MMG signal is generated but no pneumatic measure P for respiratory activity is generated. mus in the design plan.

[0031] The estimated respiration signal Sig determined according to the present invention res，est For example, it is used for the following tasks:

[0032] -Determine the neuromechanical efficiency of the patient's respiratory muscles.

[0033] - Determination of the state of the patient's respiratory muscles (particularly fatigue determination) - for this purpose, no pneumatic measurement P is required mus ,

[0034] - Detection of asynchronies in the patient's own respiratory activity - for this purpose no pneumatic measurement P is required either mus ,

[0035] - For monitoring the patient, the estimated respiratory signal Sig res，est and respiratory EMG power are determined and output as two vital parameters in a form perceptible to humans, preferably visually in each case as a time course, optionally in conjunction with the airway pressure P aw and / or esophageal pressure P es are output together,

[0036] -The patient performs his own breathing activities and artificial respiration is performed on the patient in an assisted manner. res，est The patient's own breathing activity is derived from the air pressure measurement P mus The artificial respiration caused by the ventilator is synchronized as well as possible with the patient's own breathing activity. During artificial respiration, the ventilator preferably performs a series of artificial respiration strokes and delivers a certain amount of gas mixture containing oxygen to the patient in each artificial respiration stroke. Preferably, the estimated respiration signal Sig res，est For example, the artificial respiration machine performs an artificial respiration stroke according to the estimated respiration signal Sig res，est Triggering an artificial respiration stroke and / or ending the artificial respiration stroke and / or according to the estimated respiration signal Sig res，est The corresponding amplitude of each artificial respiration stroke and / or the time variation frequency of the artificial respiration stroke can also be determined based on the estimated respiration signal Sig res，est To regulate the end of artificial respiration.

[0037] According to the application, an intermediate signal is calculated from the sum signal. In the intermediate signal, the influence of the cardiac activity, i.e. the cardiogenic signal, on the sum signal is approximately compensated in calculation. According to the application, this intermediate signal is attenuated. The application is based on the recognition that, in the entire heartbeat period or at least in a segment of the heartbeat period, the cardiogenic signal Sig kar has a much greater influence on the sum signal than the respiratory signal Sig res . Preferably, it is at least 50 times greater than the influence of the respiratory signal Sig res , particularly preferably at least 100 times greater than the influence of the respiratory signal Sig res . While the sum signal in the period between two successive heartbeat periods is mainly or even exclusively determined by the respiratory signal Sig res . Ideally, the influence of the cardiac activity is completely compensated in the intermediate signal, but in practice only partially. The attenuation at least approximately compensates for that influence of the cardiogenic signal Sig kar which remains after the calculation-based compensation.

[0038] The use of at least one quality measure according to the application takes particular account of the fact that, in the course of the use phase, various disturbances can occur while the or at least one sum signal sensor measures the respective sum signal. These disturbances can lead to a relatively large cardiogenic signal component still being obtained in the intermediate signal. According to the generated quality measure, this component is reduced.

[0039] According to a first alternative, the signal processing unit calculates a reference attenuation signal segment. Preferably, the signal processing unit calculates the reference attenuation signal segment in an initialization phase, wherein the initialization phase precedes the use phase in time. Preferably, the initialization phase and the use phase are carried out for the same patient. For the calculation, the signal processing unit uses a sample having a plurality of sample elements. Each sample element respectively relates to a heartbeat. Each sample element respectively comprises an intermediate signal segment. The intermediate signal segment is a segment of the intermediate signal and lies within the heartbeat period of the heartbeat.

[0040] For each sample element, the signal processing unit respectively generates a power measure sample element. The power measure sample element is a time course of the measure of the electrical power in the heartbeat period of the heartbeat.

[0041] The signal processing unit generates from the sample elements an average power signal segment, i.e. as a weighted average over the power measure sample elements. The weighted average comprises weighting factors. These weighting factors are calculated in case of using a power quality measure. The smaller the power quality measure for the sample element, the smaller the weighting factor for the power measure sample element. The power quality measure is a quality measure describing the shape of the power signal segment of the sample element. All weighting factors can be of the same size, i.e. forming an arithmetic average.

[0042] The signal processing unit uses the calculated average power signal segment for calculating a reference attenuation signal segment.

[0043] In one design, a plurality of frequency bands is predefined. The just described plurality of steps is performed, preferably in parallel, for each frequency band. In particular, the signal processing unit performs for each predefined frequency band the following steps: the signal processing unit calculates, respectively, a component of the reference attenuation signal segment, or determines this component by a read access to the data memory. Each component relates to the frequency band, respectively.

[0044] For each predefined frequency band and for each detected heartbeat in the using phase, the signal processing unit furthermore performs the following steps:

[0045] - the signal processing unit generates a component of the intermediate signal segment for the detected heartbeat, wherein the component occurs within the frequency band.

[0046] - the signal processing unit generates a component of the attenuated intermediate signal segment for the heartbeat period, wherein the component occurs within the frequency band. For this purpose, the signal processing unit uses the component of the intermediate signal segment for the frequency band.

[0047] The signal processing unit generates the attenuated intermediate signal segment for the heartbeat period from the components for the frequency bands which have been calculated as just described.

[0048] In case of the first alternative, the signal processing unit performs the following steps:

[0049] - the signal processing unit calculates, as just described, for each detected heartbeat, respectively, a component of the intermediate signal segment for the heartbeat. The component relates to the frequency band.

[0050] - the signal processing unit determines, respectively, for each frequency band, a component of the reference attenuation signal segment. The component relates to the frequency band, too. For calculating the component, the signal processing unit uses at least one quality measure.

[0051] - the signal processing unit applies the component of the reference attenuation signal segment to the component of the intermediate signal segment. This application provides the component of the attenuated intermediate signal segment.

[0052] In case of the second alternative, the signal processing unit performs the following steps:

[0053] - The signal processing unit determines for each frequency band separately a component of the reference attenuation signal segment. The component relates to the frequency band.

[0054] - The signal processing unit calculates for each frequency band separately a component of the adapted attenuation signal segment for each detected heartbeat. The component relates to the frequency band. For calculating the component, the signal processing unit uses at least one quality measure.

[0055] - The signal processing unit applies the component of the adapted attenuation signal segment to the component of the intermediate signal segment. The application provides a component of the attenuated intermediate signal segment.

[0056] The present invention furthermore relates to a device having a signal processing unit according to the present invention and at least one and signal sensor. The or each and signal sensor of the device is capable of measuring a signal generated in and / or at the body of a patient. The or each and signal sensor provides a measurement value. The signal processing unit receives the measurement values and generates from the received measurement values at least one and signal, in one design variant one and signal for each and signal sensor. BRIEF DESCRIPTION OF DRAWINGS

[0057] The present invention is described in the following according to an embodiment. In this case,

[0058] Figure 1 An exemplary segment of a heart-originating signal is shown over the course of a single heartbeat;

[0059] Figure 2 It is schematically shown which sensors measure which different variables, which are used for determining the estimated respiration signal;

[0060] Figure 3 An exemplary course of an and signal is shown and two heartbeat instants and four respiration periods are exemplarily shown;

[0061] Figure 4 A compensation function block and an attenuation function block are shown schematically;

[0062] Figure 5 It is exemplarily shown how a heart-originating reference signal segment is generated under ideal conditions;

[0063] Figure 6 Segments of a plurality of time correct positioning of a compensation signal are shown without and with interference;

[0064] Figure 7 It is shown Figure 4two functional blocks of the compensation function block, in which the attenuation caused by the compensation function block is shown in more detail;

[0065] Fig. 8 shows a plurality of exemplary components of the attenuation function;

[0066] Figure 9 shows the average power signal segment Pow com，av (n) for the n levels (frequency bands) and the computed threshold com，av (n) and the computed threshold

[0067] Figure 10 shows the average power signal segment Pow com，av (5) for the 5th level;

[0068] Figure 11 shows the reference attenuation signal segments for the n levels;

[0069] Figure 12 shows the attenuation function block of Figure 4 in more detail;

[0070] Figure 13 shows the measurement value processor and the functional block for computing the quality measure for the measurement value processor;

[0071] Figure 14 shows the design for computing the average curve (baseline) of the original signal;

[0072] Figure 15 shows the functional block for providing the two quality measures in detail;

[0073] Figure 16 shows exemplary average power signal segments and reference attenuation signal segments;

[0074] Figure 17 exemplarily shows the reference attenuation signal segment and the adapted attenuation signal segment for the heartbeat period. DETAILED DESCRIPTION

[0075] In this embodiment, the application is used for automatically determining an estimate Sig res of a respiratory signal Sig res，est , wherein the respiratory signal Sig res to be estimated is related to the own respiratory activity of the patient P and thus at least approximately describes the own respiratory activity. This own respiratory activity can be triggered by electrical impulses within the body of the patient P, wherein the patient P generates these impulses himself, so that the own respiratory activity is spontaneous breathing, and / or is stimulated from the outside, for example in a magnetic field. The index est indicates that the respiratory signal Sig res is estimated, not precisely measured.

[0076] In one application of this embodiment, when determining the estimated respiration signal Sig res，est During this time, the patient P is at least temporarily artificially ventilated, ie by assisted artificial respiration. In another application, the invention is used for monitoring the patient P and in particular his own respiratory activity, and for this purpose uses the respiratory signal Sig to be estimated. res , without the need for continuous artificial respiration of the patient P.

[0077] The breathing signal Sig res cannot be measured directly. It is possible to position a measuring probe in the body of the patient P and to generate measurement values ​​from the probe. It is also possible to obtain the measurement values ​​in a non-invasive manner, in particular in such a way that electrodes on the skin of the patient P record the measurement values. Usually, it is not possible to directly measure the pulses that "control" the respiratory muscles generated in the body of the patient P in either an invasive or a non-invasive manner, but only to measure the electrical measurement values ​​that are generated when the muscle fibers of the respiratory muscles contract, or the effect of such electrical measurement values ​​on the pneumatic signal, for example. In addition, the electrical pulses that are caused by the cardiac activity of the patient P, more precisely: the myocardial contraction, are superimposed on the electrical pulses that cause the patient P's own respiratory activity. Therefore, after corresponding processing of the measurement values, only the sum signal Sig can be directly measured. Sum The sum signal Sig Sum The respiratory signal Sig sought is related to the patient P's own respiratory activity res and cardiac signal Sig related to its cardiac activity kar The sum signal Sig is formed by superposition. Sum It can be influenced by other signals, in particular by signals acting on the transmission path from the signal source in the patient's body to the measurement location, as well as by external signal sources. These other signals are usually interference variables. At the measurement location, a measured value is measured, from which a sum signal Sig is generated. Sum .

[0078] exist Figure 1 Figure 2 shows the cardiogenic signal Sig measured electrically during a single heartbeat. kar The reference heartbeat period H_Zr is shown on the x-axis as an example. ref , the signal value is shown on the y-axis, for example, in millivolts. Five peaks can be seen: P, Q, R, S, and T. A characteristic heartbeat moment is, for example, the Q peak, R peak, S peak, or the midpoint between the Q and S peaks, or the midpoint between the P and T peaks of the heartbeat.

[0079] Figure 2which signals can be generated from the measurement values in such a way that measurement values are generated at and / or in the body of the patient P and the measurement values are automatically processed in an appropriate manner. It is schematically shown

[0080] - a patient P, who is artificially respirated,

[0081] - an esophagus Sp and a diaphragm Zw of the patient P,

[0082] - an artificial respirator 1 (ventilator), which artificially respirates the patient P at least temporarily and which comprises a signal processing unit 5, wherein the signal processing unit 5 has at least temporary read and write access to a data memory 9,

[0083] - an intercostal pair 2.1 with two measurement electrodes 2.1.1 and 2.1.2, which are arranged on the right and left side of the breastbone and between two respective ribs of the patient P, i.e. in a region close to the heart,

[0084] - a pair 2.2 close to the diaphragm with two other measurement electrodes 2.2.1 and 2.2.2, which are arranged close to the diaphragm Zw of the patient P, i.e. in a region away from the heart,

[0085] - an electrode for grounding, not shown,

[0086] - a pneumatic sensor 3, which is spatially remote from the body of the patient P and which comprises a measurement value sensor element, for example arranged in front of the mouth of the patient P, and a data processing evaluation unit, which can be arranged in the artificial respirator 1,

[0087] - an optional optical sensor 4, which comprises an image recording device and an image evaluation unit and which is aimed at the body of the patient P,

[0088] - an optional pneumatic sensor 6 in the form of a probe or air bag, which is located in the esophagus Sp and close to the diaphragm Zw of the patient P,

[0089] - a cuff 7, which is schematically shown around the wrist of the patient P, wherein this cuff 7 holds a catheter 17 in order to invasively measure the time course of the blood pressure,

[0090] - two finger clips 8.1, 8.2, which are placed on a finger of the patient P or positioned at another location on the skin of the patient P, respectively, wherein one finger clip 8.1 non-invasively measures the oxygen saturation of the blood, preferably by means of plethysmography, and the other finger clip 8.2 non-invasively measures the blood pressure of the patient P, and

[0091] - optionally an electrode, not shown, in the esophagus of the patient P,

[0092] - a screen on which the time course of the signal is displayed.

[0093] The intercostal pair 2.1 and the ground electrode provide, after signal processing, a first sum signal Sig Sum (1). The pair 2.2 close to the diaphragm and the ground electrode provide, after signal processing, a second sum signal Sig Sum (2). The other sensors described above can provide further sum signals Sig Sum (n), n >= 3. It is also possible that the same sensor device provides two different sum signals, for example by applying different measurement methods. Such sensor devices are described, for example, in DE 10 2009 035 018 Al and US 2011 / 0028819 Al. In the following, reference is made to the "sum signal Sig Sum ".

[0094] Instead of electrical signals (EMG signals), it is also possible to generate and use sum signals Sig Sum in the form of myographic (MMG signals).

[0095] In order to adjust the artificial respirator 1 when artificially respirating the patient P or in order to monitor the patient P, and using the estimated respiration signal Sig res，est for the adjustment or monitoring, the estimated respiration signal Sig res，est is determined at a high sampling frequency, i.e. at each sampling instant t, the signal processing unit 5 provides a new signal value Sig res，est (t). By "high sampling frequency" is understood that there is an interval of less than five milliseconds, preferably less than three milliseconds, between two successive sampling instants. In particular for the determination of fatigue, the sampling frequency is preferably at least 1 kHz, particularly preferably at least 2 kHz. In this embodiment, some steps of the method described below are performed at a low sampling frequency, i.e. at a frequency lying in the range of the heart beat frequency, i.e. between 1 Hz and 2 Hz.

[0096] Figure 3 An exemplary time course of a sum signal Sig Sum with four breaths and a number of heart beats is shown. On the x-axis, time is plotted, and on the y-axis, a quantity measured by the sum signal sensor, for example a voltage in millivolts. Four time intervals Atm(1),..., Atm(4) of four breaths are shown, and two characteristic heart beat instants H_Zp(x) and H_Zp(y) are shown exemplarily. It can be seen that the cardiogenic signal Sig kar within a heart beat period H_Zp(x), H_Zp(y) is the respiration signal Sig resHowever, outside the heartbeat period, the respiratory signal Sig res Cardiac signal Sig kar is strong enough, and thus can be obtained from the sum signal Sig Sum To be determined.

[0097] Figure 4 The two functional blocks 20 and 21 of the signal processing unit 5 are schematically shown, wherein the functional blocks 20, 21 respectively perform different signal processing steps in order to calculate the sum signal Sig Sum The measured sum signal Sig is at least partially compensated for by cardiac activity. Sum The output signal of the compensation function block 20, ie, the compensation signal Sig described below com As input signal, the attenuation function block 21 is applied. As output signal, the attenuation function block 21 provides the sought estimate Sig res，est .

[0098] The functional unit 10 of the compensation functional block 20 generates a synthetic cardiogenic signal Sig kar，syn , the synthesized cardiogenic signal is the cardiogenic signal Sig kar It is an approximation (estimate) of and consists of signal segments (hence the name synthetic). Each signal segment describes the heart's activity during a heartbeat. Figure 1 Such signal segments are shown by way of example in FIG. The signal segments are positioned in a time-correct manner, optionally adapted and combined to form a synthetic cardiogenic signal Sig kar，syn Synthetic cardiogenic signal Sig kar，syn is the actual cardiac signal Sig kar DE 10 2019 006 866 A1 and US 2022 / 0330837 A1 describe a method for adapting signal segments.

[0099] The compensation function block 20 calculates and compensates the synthesized cardiogenic signal Sig by, for example, subtraction. kar，syn Sum signal Sig Sum The contribution of , and thus generate the compensation signal Sig com , the compensation signal acts as an intermediate signal.

[0100] Figure 5 The compensation signal Sig is shown com This exemplary time variation is formed by the compensation function block 20 processing the compensation function block 20 as just described. Figure 3 The sum signal Sig is shown as an example in Sum In addition, Figure 5Two exemplary heartbeat periods H_Zp(x) and H_Zp(y) are shown in the following figure. It is illustrated how the two heartbeat periods H_Zp(x) and H_Zp(y) are mapped to the same reference heartbeat period H_Zr ref .

[0101] Figure 4 The compensation function block 20 generates in an initialization phase a cardiac reference signal segment SigA kar，ref which is stored in the data memory 9 and which is re-applied for each detected heartbeat in a subsequent usage phase. The following steps are performed:

[0102] - the functional unit 12 identifies in the sum signal Sig Sum the respective start and the respective end and / or the respective QRS phase of each heartbeat, i.e. the respective characteristic heartbeat period H_Zr(x), H_Zr(y).

[0103] - the functional unit 13 determines the respective accurate characteristic heartbeat instant H_Zp(x), H_Zp(y) of each heartbeat, i.e. preferably with a tolerance of a few milliseconds. It is particularly preferred that the tolerance is at most half of the time interval between two successive sampling instants of the sum signal Sig Sum , wherein this time interval is preferably below 1 millisecond.

[0104] - the functional units 12 and 13 require a plurality of values of the sum signal Sig Sum for a plurality of successive sampling instants in order to determine the accurate heartbeat instant H_Zp(x) of each heartbeat. In one design, an optional functional unit 32 delays the sum signal Sig Sum for a corresponding time period for the subsequent steps, see Figure 4 . Thereby, the accurate heartbeat instant H_Zp(x) is available for the subsequent steps. This optional functional unit 32 is omitted in the following figures. This delay is applied only if the respective application does not require the estimated respiration signal Sig res，est in real time.

[0105] In the initialization phase, N heartbeats are detected. The segments SigA Sum (x) of the sum signal Sig Sum belong to each heartbeat number x. Thus, these N heartbeats provide N sample elements for the sample.

[0106] In the initialization phase, the following steps are additionally performed:

[0107] - the functional unit 14 computationally superimposes the N sum signal segments SigA N (x) for the last N heartbeats x1,..., x Sum(x1), ..., SigA Sum (x N ), i.e. in a time-correct manner. If necessary, these N sum signal segments are cut, compressed or stretched to a consistent length.

[0108] - preferably a signal segment SigA for N heartbeats Sum (x1), ..., SigA Sum (x N ) are superimposed so that the signal segments have the same length and the R peaks or other characteristic heartbeat moments overlap. Thus, each signal segment relates to the same reference heartbeat period H_Zr ref , see Figure 5 The reference heartbeat period H_Zr ref The relative time in the relative heartbeat period is represented by τ. The relative time τ=τ(t) in the relative heartbeat period corresponds to the sum signal segment SigA Sum Instead of the term "relative time", the term "cardiac cycle φ" having a value range of 0° to 360° or 0 to 2π can also be used.

[0109] The functional unit 15 receives the N signal segments SigA generated by the functional unit 14 Sum (x1), ..., SigA Sum (x N ) to generate a cardiac reference signal fragment (template) SigA kar，ref The cardiac reference signal fragment SigA kar，ref Approximately describes the cardiac signal Sig during a single heartbeat kar The change process of , and also involves the reference heartbeat period H_Zr ref Preferably, the characteristic heartbeat moment H_Zp(x) is at τ=0. As already mentioned, during a heartbeat, the sum signal Sig Sum The cardiogenic component in is a multiple of the respiratory component, and the respiratory component during the heartbeat period is largely "filtered out" by averaging over N signal segments.

[0110] - Functional unit 15 preferably applies the learning method to N signal segments for the respectively last N heartbeats. Cardiogenic reference signal segment SigA kar，ref Preferably stored in the data memory 9. The cardiac reference signal segment SigA kar，ref The patient P and his current state are involved, so it is not an averaging over the signals of different patients.

[0111] In the subsequent use phase, perform the following steps:

[0112] - Functional units 32 and 13 are in sum signal Sig Sum Heartbeats are detected and a corresponding characteristic heartbeat moment of each detected heartbeat is determined.

[0113] - For each heartbeat number x, reuse the cardiac-derived reference signal segment SigA kar，ref In one design, the sum signal segment SigA of the heartbeat period H_Zr(x) for heartbeat x is obtained. Sum The cardiogenic reference signal segment is unchanged subtracted from (x) (sample subtraction).

[0114] Alternatively, the functional unit 16 uses the value of at least one anthropological parameter that influences the cardiac activity and thus the cardiogenic signal Sig kar and has been measured at the time of this heartbeat number x. The measure of the lung filling level and the current posture of the patient P as well as the interval RR between the R peaks of two consecutive heartbeats are examples of such anthropological parameters. For each heartbeat, the functional unit 16 converts the cardiogenic reference signal segment SigA kar，ref Adapted to the or each anthropological parameter value measured during the heartbeat and generating therefrom the cardiogenic signal segment SigA kar (x). Such actions are described, for example, in DE 10 2019 006 866 A1 (US 2022 / 0330837 A1) and DE 10 2020 002 572 A1 (US 2021 / 0338176 A1).

[0115] The functional unit 16 generates the sum signal segment SigA numbered x relative to the current heartbeat in a time-correct manner, ie, in synchronization with the QRS. Sum (x) Cardiac reference signal fragment SigA kar，ref or optionally adapted cardiac signaling fragment SigA kar (x) is positioned. This generates a synthetic cardiogenic signal Sig kar，syn New synchronization segment SigA kar，syn (x). Preferably, the synthesized cardiogenic signal Sig kar，syn is output in a form perceivable by humans, such as Figure 2 on the screen unit.

[0116] - for example by the functional unit 11 from the latest sum signal fragment SigA Sum (x) Subtract the cardiac reference signal fragment SigA kar，ref or the adapted cardiac signaling fragment SigA kar (x), the functional unit 11 is in the latest sum signal segment SigA Sum(x) compensating the heart-originating signal Sig kar influences. The result is a compensated signal Sig com of new segments SigA com (x).

[0117] At the beginning of the method, i.e. after the patient P has been connected to the measuring electrodes 2.1.1 to 2.2.2, an initialization phase is performed which comprises a period of N detected heartbeats. In this initialization phase, the compensation function block 20 generates an initial heart-originating reference signal segment SigA Sum (x1),..., SigA Sum (x N ) from the sum signal segments SigA kar，ref (x) for the last N heartbeats as described above. During the method, the compensation function block 20 preferably adapts the heart-originating reference signal segment SigA kar，ref to the respective last N heartbeats and stores the result in the data memory 9. The steps in the initialization phase and the adaptation to the respective last N heartbeats are performed at a low sampling frequency which is approximately equal to the heart rate.

[0118] Preferably, the segments for one heartbeat are superimposed at a double time resolution of the sum signal Sig Sum . This means that the values of the sum signal Sig Sum are determined at a high sampling frequency f, i.e. the interval At between two sampling instants is 1 / f. For example, the signal value Sig Sum (t+At / 2) is positioned computationally, e.g. by interpolation, between the two signal values Sig Sum (t) and Sig Sum (t+At) derived from the measurement values, the time resolution is computationally enlarged to e.g. 2f or 3f.

[0119] After the initialization phase, the following steps are performed at a high sampling frequency (a few milliseconds or even only a few tenths of a millisecond):

[0120] - the signal processing unit 5 derives from the measurement values the new values Sig Sum (t) for the sum signal Sig Sum .

[0121] - the function units 12 and 13 identify in the sum signal Sig Sum the beginning of a heartbeat period H_Zr(x) or the exact characteristic instant H_Zp(x) of a heartbeat x and determine therefrom a new sum signal segment SigA Sum (x).

[0122] - the compensation function block 20 optionally adapts the heart-originating reference signal segment SigAkar，ref to the respective value of at least one anthropological parameter. The compensation function block 20 determines the assigned relative time instant τ = τ(t) and generates, by time-correct positioning, a further signal segment, namely a synthesized cardiac signal Sig kar，syn of the latest in time segment SigA kar，syn (x).

[0123] - The functional unit 11 subtracts from the cardiac reference signal segment SigA Sum or the adapted cardiac signal segment SigA kar，ref the value SigA kar [τ(t)] or SigA kar，ref (x)[τ(t)] of the same relative time instant τ from the new value Sig kar (t), namely

[0124] Sig com (t) = Sig Sum (t) - SigA kar，syn [τ(t)]

[0125] or otherwise compensates for the cardiac influence.

[0126] - The compensation function block 20 outputs the new signal segment SigA com (x) for the compensation signal Sig com .

[0127] Ideally, the compensation signal Sig com contains all contributions of the cardiac activity Sig kar to the signal Sig Sum . But this is not the case in reality. There are primarily two possible reasons for this:

[0128] - Possible disturbances in the initialization phase lead to a cardiac reference signal segment SigA kar，ref which deviates in a relevant manner from the true situation.

[0129] - Possible disturbances in the usage phase affect the signal Sig Sum .

[0130] Figure 6 The effect of possible disturbances is illustrated. In both diagrams, a plurality of signal segments of the temporal course of the electrical power of the signal are shown, wherein there is the signal segment Pow com，av (6) which is further explained below. Each signal segment covers a single heartbeat period H_Zr(x), H_Zr(y). In the left diagram, no disturbances occur, while in the right diagram a plurality of disturbances occur which lead to a compensation signal Sig comlarge oscillations. These disturbances occur, for example, when the measurement values are generated. Without appropriate countermeasures, these large oscillations can lead to false results.

[0131] In this embodiment, an attenuation function block 21 is applied to the compensation signal Sig com for post-processing, see Figure 4 . The output signal of the compensation function block 20, i.e. the compensation signal Sig com is applied as an input signal to the attenuation function block 21.

[0132] The functional unit 23 of the attenuation function block 21 generates from the compensation signal Sig com an attenuation signal segment Mod(i) which is described further below. The functional unit 26 applies this attenuation signal segment Mod(i) to the compensation signal Sig com , thereby computationally causing a reduction, in particular an attenuation, of the electrical power, and thereby generating the estimated respiration signal Sig res，est .

[0133] The attenuation function block 21 is described in more detail below with reference to Figure 7 . The compensation signal Sig com is applied to the attenuation function block 21.

[0134] A number n of frequency bands is predefined, which are also referred to as "levels" in the case of a wavelet transformation. In this case, n is a predefined number. Preferably, n lies between 5 and 10, and particularly preferably is 8. Level 1 belongs to the frequency band with the highest frequencies, and level n belongs to the frequency band with the lowest frequencies.

[0135] The following description relates to the use phase, unless otherwise stated.

[0136] The functional unit 30 generates from the compensation signal Sig com a compensation signal segment SigA com (x) for the most recent detected heartbeat x. To this end, it uses the characteristic heartbeat time H_Zp(x) and the heartbeat period H_Zr(x), which the functional units 12 and 13 have detected in the use and signal Sig Sum .

[0137] The functional unit 22 decomposes the compensation signal segment SigA com (x) of the compensation signal Sig com into n signal component segments SigA com (1)(x),..., SigA com(n) (x). The functional unit 22 preferably performs a wavelet transform, preferably a stationary wavelet transform or an àtrous transform. If the signal component segment SigA com (i) (x) are joined (combined) in a time-correct manner, the signal component Sig com (i) (i = 1,..., n).

[0138] The attenuation function block 21 comprises a functional unit 22 for decomposition, a functional unit 25 for inverse transformation and, for each level i, one functional unit 23(i) and two functional units 24 = 24(i) and 26 = 26(i) respectively. In Figure 7 In the middle, only one functional unit 24 and one functional unit 26 are shown, namely for level i.

[0139] In the initialization phase, the functional unit 23(i) generates a reference attenuation signal segment Mod(i) for each level i (i = 1,..., n) respectively, i.e. a total of n reference attenuation signal segments Mod(1),..., Mod(n). Each reference attenuation signal segment Mod(i) describes a time-varying course and covers the reference heartbeat period H_Zr ref Each signal value Mod(i)(t) is a number between 0 and 1 inclusive. For each level i, the reference attenuation signal segment Mod(i) is thus generated in the initialization phase respectively. These n reference attenuation signal segments Mod(1),..., Mod(n) are stored in the data memory 9 and used in the usage phase.

[0140] For each level i, the reference attenuation signal segment Mod(i) is thus generated in the initialization phase respectively. Figure 7 The arrow Akt in block 23(i) in the middle indicates that, in one design variant, the reference attenuation signal segment Mod(i) is continuously updated even in the usage phase. How this happens is described further below.

[0141] In the usage phase, for each heartbeat x and for each level i, the respective functional unit 23(i) is applied to the signal component segment SigA com (i) (x), i = 1,..., n. The functional unit 24 = 24(i) of the functional unit 23(i) generates an adapted attenuation signal segment Mod(i)(x) from the reference attenuation signal segment Mod(i), wherein the adapted attenuation signal segment Mod(i)(x) describes a time-varying course and covers the heartbeat period H_Zr(x), and wherein each signal value Mod(i)(x)(t) is a number between 0 and 1 inclusive.

[0142] The functional unit 26 = 26(i) applies in the use phase an adapted attenuation signal segment Mod(i)(x) to the signal component segment SigA for the heartbeat x, which correctly positions the time com (i)(x), and produces the attenuated signal component segment SigA com，d (i)(x)(i = 1,..., n). For example, the functional unit 26 multiplies the two signal values SigA com (i)(x)(t) and Mod(i)(x)[τ(t)] with one another and thereby produces for each sampling instant t the attenuated signal component segment SigA com，d (i)(x) the value SigA com，d (i)(x)(t), for example according to the calculation rule

[0143] SigA com，d (i)(x)(t) = SigA com (i)(x)(t)*Mod(i)(x)(t).

[0144] Further possible implementations are described below with reference to Fig. 8.

[0145] This modification provides the signal component segment SigA com (i)(x) the attenuation SigA com，d (i)(x). The sign of each signal value is preserved in the case of the attenuation. Alternative design solutions for the attenuation are described further below.

[0146] Fig. 8 illustrates how from the signal component segment SigA com (i)(x) the attenuated signal component segment SigA com，d (i)(x) is produced. Due to the attenuation, the signal component segment SigA com (i)(x) is divided into a respiratory component SigA com，d (i) and a heart-related component, also referred to as ECG.

[0147] Possibility a) is the design solution just set out, multiplied by a factor Mod(i)(x), where the slope Mod(i)(x)(t) of the straight line depends on t. Possibility b) indicates a hard threshold (hard th res hold) α, where this threshold α = α(t) likewise depends on t. Possibility c) indicates a soft threshold (soft th res hold). Possibility d) is a hybrid form. Possibility e) is described further below.

[0148] The attenuated signal component segment SigAcom，d (i)(x), the attenuated signal component segment relates to the time period H_Zr(x) of the last heartbeat number x and to the level number i.

[0149] Functional unit 25 converts the attenuated signal component segment SigA com，d (1)(x),...,SigA com，d (n)(x) is combined into the attenuated signal component segment SigA com，d (x), wherein the functional unit 25 preferably performs an inverse wavelet transformation and outputs the attenuated signal component segment SigA as an output signal com，d (x).

[0150] Functional unit 31 generates the sought estimated respiration signal Sig res，est To this end, the functional unit uses the characteristic heartbeat instant H_Zp(x), the heartbeat period H_Zr(x) and the attenuated signal component segment SigA com，d (x). For the segment between two consecutive heartbeat periods H_Zr(x) and H_Zr(x+1), the functional unit 31 preferably uses the compensation signal Sig com The corresponding segment is used as the estimated respiratory signal Sig res，est Functional unit 31 outputs the estimated respiratory signal Sig generated in this way res，est .

[0151] Once another heartbeat is complete, Figure 4 The functional units 14 and 15 shown in FIG generate the adapted cardiogenic signal segment SigA kar (x), the functional unit updates the cardiac reference signal segment SigA kar，ref Furthermore, the functional unit 23 ( i ) adapts the reference attenuated signal segments Mod(i) for n levels and generates therefrom adapted attenuated signal segments Mod(i)(x), namely preferably once another heartbeat has been completed (i=1, . . . , n).

[0152] The following describes how to generate n reference attenuated signal segments Mod(1), ..., Mod(n) in the initialization phase. Figure 11 Eight reference attenuated signal segments Mod(1), ..., Mod(8) are shown as an example, ie n = 8. In one embodiment, in the initialization phase, the functional unit 24 generates for each level i and for each signal component segment SigA of the heartbeat x. com (i)(x)(i=1, ..., n) respectively perform the steps described below:

[0153] In the initialization phase, the functional unit 24 determines an average signal segment Pow com，av (i) for the temporal course of the electrical power, wherein the power signal segment Pow com，av (i) covers the reference heartbeat period H_Zr ref and relates to the hierarchy number i. The average power signal segment Pow com，av (i) is calculated as a weighted average over the power values of M signal segment components SigA com (i)(x) of M heartbeats x. For example,

[0154] Pow com (i)(x)(τ) = Abs[SigA com (i)(τ)] (absolute value) or

[0155] Pow com (i)(x)(τ) = RMS[SigA com (i)(τ)] (root mean square, RMS, effective value).

[0156] Figure 6 The average signal segment Pow com，av (6) for the hierarchy number 6 is exemplarily shown, which has been calculated as an arithmetic average. The following further refers to Figure 12 how the functional unit 24 forms the weighting factors for the weighted average.

[0157] In the initialization phase, M power signal segments Pow com (i)(x) are thus calculated for M heartbeats x. The number M and the number N (of heartbeats for calculating the cardiogenic reference signal segment SigA kar，ref ) can be identical or different from each other. Preferably, each power signal segment Pow com (i)(x) is calculated with the use of a suitable filter, wherein the values of the compensation signal Sig com are suitably smoothed.

[0158] Each power signal segment Pow com (i)(x) of a heartbeat x covers the heartbeat period H_Zr(x), respectively. The functional unit 24 superimposes the M power signal segments Pow com (i)(x) onto the M heartbeats in a heartbeat-synchronous (time-correct) manner and subsequently forms a weighted average over the superimposed M segments. Thereby, the average power signal segment Pow com，av (i) for the hierarchy number i is determined, which is the compensation signal Sig com(i) the average electric power in the reference heartbeat period H_Zr ref during which the determined average electric power depends on the relative time instant τ. By averaging, influences that are not due to the heart activity of the patient P but due to respiratory activity, e.g. coughing, are "averaged out".

[0159] Figure 9 shows a piece of the average power signal Pow com，av (i) that is generated by the heartbeat-synchronous superposition. ref and the reference heartbeat time instant H_Zp ref In this example, eight different levels are distinguished, i.e. n = 8. The time instant t = 0 on the x-axis has been placed in the reference heartbeat time instant H_Zr ref Furthermore, Figure 9 shows n = 8 pieces of the average power signal Pow com，av (1),..., Pow com，av (8) for n = 8 levels.

[0160] Figure 10 shows a piece of the average power signal Pow com，av (5) for level No. 5.

[0161] From the piece of the average power signal Pow com，av (i) for level No. i, an average signal value Avg(i) is derived, and a threshold value (threshold) is derived in the case of use of the average signal value Avg(i) The average signal value Avg(i) and the threshold value Generally, from level i1 to level i2, and if the average signal value Avg(i) and the threshold value are continuously updated according to the last M heartbeats, respectively, then also for a single level i from heartbeat to heartbeat. By means of this threshold value com that depends on the compensation signal Sig The noise in the compensation signal Sig com which is essentially generated by the cardiogenic signal Sig kar is later at least partially eliminated in a calculation, wherein. Due to the just described action, the threshold value is calculated at runtime and does not need to be pre-given.

[0162] The average signal value Avg(i) is calculated, for example, as the average of R successive relative sampling time instants τ1,..., τ ref of the reference heartbeat time instant H_Zr R The average power signal piece Pow com，av(i) The arithmetic mean or median of the R signal values. Compared with the arithmetic mean, the median is less sensitive to outliers, but its calculation requires more computing time.

[0163] To calculate the threshold The factor α is predetermined, for example α=2. For example, it is calculated according to the following calculation rules

[0164]

[0165] Figure 9 Furthermore, n threshold values ​​for n levels are shown.

[0166] Average power signal segment Pow com，av (i) Signal value Pow com，av (i)(τ) in the reference heartbeat period H_Zr ref The larger the corresponding relative time τ(t), the greater the compensation signal Sig com The signal component SigA com (i) Signal value SigA of (x) com (i)(x)(t) should be attenuated more strongly because large signal values ​​are derived from the cardiogenic signal Sig due to averaging over N heartbeat periods. kar Therefore, the attenuation depends on the current determination of the sum signal Sig Sum As already mentioned, according to this design, the attenuation also depends on the reference heartbeat period H_Zr ref In this way, the attenuation can be adapted to the current cardiac activity of the patient P even in the event of irregularities in the cardiac activity.

[0167] In one design, if τ is within the reference heartbeat period H_Zr ref In, and If applicable, then the average power signal segment Pow com，av The reference attenuated signal segment Mod(i) is generated in (i), for example, according to the following calculation rule:

[0168] Mod(i)(τ)=min{Avg(i) / Pow com，av (i)(τ),1},

[0169] And otherwise, Mod(i)(τ)=1.

[0170] Each signal value Mod(i)(τ) of the reference attenuated signal segment Mod(i) is a number between 0 and 1, inclusive.

[0171] In reference to the heart beat period H_Zr ref The design of setting the signal value Mod(i)(τ) to 1 outside the reference decay signal segment Mod(i) ensures that the reference decay signal segment Mod(i) only causes decay for the current heart beat.

[0172] In the generalization, for each value of Mod(i) is calculated according to the following calculation rule:

[0173] Mod(i)(τ) = min{F[Pow com，av (i)(τ)], 1},

[0174] where F = F(u) is a decreasing function with respect to u [the larger u, the smaller F(u)], and the value range has 0 to y, and where y is greater than or equal to 1.

[0175] As shown in Fig. 8, there is an alternative to the design of achieving decay by multiplication. In Figure 8b ) to Figure 8d ) several design schemes are shown, in which a threshold value a X = a X (τ) is used. Figure 8d ) a design is shown, in which additionally two other threshold values b X = b X (τ) and b Y = b Y (τ) are used.

[0176] Figure 12 A functional block diagram of the extension according to the application of Fig. 8 is shown. Identical reference signs have the same meaning as in Fig. 8. Figure 7 Figure 7

[0177] Figure 12 The measurement value processor 19 is shown schematically. The measurement value processor 19 processes the raw signal Sig raw provided by the sensors 2.1.1 to 2.2.2 after signal amplification. The measurement value processor 19 removes low-frequency oscillations computationally, normalizes the raw signal Sig raw and provides the sum signal Sig Sum .

[0178] In one design, the measurement value processor 19 subtracts an average curve (baseline) BL from the raw signal Sig raw . Figure 14 A preferred design for calculating the average curve (baseline) BL is elucidated. Segments of the raw signal Sig raw are shown, which raw signal comprises six heart beats x1,..., x6. It is determined that at each two consecutive heart beat periods H_Zr(x n ​​) and H_Zr(x n+1 ) and H_Zr(x n+1 ) and H_Zr(x n+2 ) and H_Zr(x raw ) and H_Zr(x raw ) and H_Zr(x n，n+1 ) and H_Zr(x raw ) and H_Zr(x n+1，n+2 ) and H_Zr(x raw ) and H_Zr(x 1，2 ) and H_Zr(x raw ) and H_Zr(x n，n+1 ) and H_Zr(x n ) and H_Zr(x n+1 ) and H_Zr(x

[0179] For each segment Sig raw (x 1，2 ), Sig raw (x 2，3 ), support points Stp(1,2), Stp(2,3),... are determined, respectively. Stp(k,k+1 ) denotes the support point of the segment Sig raw (x k，k+1 )(k = 1,2,...). The spline is drawn through this sequence of support points Stp(1,2), Stp(2,3),.... The segment of the spline between two adjacent support points is a polynomial. Preferably, a Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) is used as the spline, wherein a cubic polynomial occurs between two adjacent support points.

[0180] The following described groups of quality measures (quality assessment, quality measures) can be distinguished. These groups result in the quality measures Q

[30] , Q[31 ], Q

[32] , Q

[33] . These quality measures are calculated and applied in the initialization phase and / or in the usage phase, which is described in further more detail below.

[0181] Q

[30] : How good is the resulting sum signal Sig Sum from the sensor's measurement values? Possible sources of errors are:

[0182] - The sensor's measurement values at or within the patient's P body are erroneous, e.g. due to a bad or even false contact of the measurement electrodes with the patient's P body, which leads to an erroneous electrode resistance.

[0183] - the measurement values of the sensor are superimposed by disturbances, e.g. by interference from a fixed power supply grid, galvanic disturbances (the measurement electrode is touched by hand), other electromagnetic interferences from nearby electrical or electronic devices.

[0184] - the process of transmitting the measurement values of the sensor to the signal processing unit 5 is disturbed, e.g. by cable breakage or connection breakage.

[0185] - technical disturbances occur at the measurement value processor 19, e.g. out of range in the case of an A-D converter, a dead battery / internal communication interruption.

[0186] Furthermore, how well the baseline BL has been mathematically removed is included into the quality measure Q

[30] .

[0187] Q

[31] : With which reliability is the heartbeat period and / or the heartbeat instant of a heartbeat detected in the signal Sig Sum ? Possible influencing factors on the quality measure Q

[31] are:

[0188] - how regular the heartbeats are?

[0189] - are the course of change of the individual heartbeats similar enough, see Figure 1 ?

[0190] - are the signal segments for the individual heartbeats found to be sufficiently valid?

[0191] Q

[32] : How reliable are the reference attenuation signal segments Mod(1),..., Mod(n) or the adapted attenuation signal segments Mod(1)(x),..., Mod(n)(x) to adapt to the contribution of the cardiogenic signal Sig kar in the intermediate signal Sig com ? This reliability can refer to the individual heartbeat period, i.e. the heartbeat-to-heartbeat variation, or to the reference heartbeat period H_Zr ref (preferably). In one design, the attenuation signal segments are derived from the power signal segments. Thus, one design for deriving the reliability Q

[32] is as follows: Is the power signal segment Pow com (i)(x) or the average power signal segment Pow com，av (i) reasonable, i.e. does it fit the expectation for the power signal segment of a single heartbeat and / or does it fit the expectation for the average power signal segment Pow com，av (i)? In other words: How well does the power signal segment Pow com (i)(x) or the average power signal segment Pow com，av (i) describe the cardiogenic signal Sig karContribution of the intermediate signal Sig to the heartbeat period H_Zr(x) com

[0192] In one design, the quality measure Q

[32] of a heartbeat x is calculated as a power quality measure and serves as a weighting factor in the calculation of a weighted average of a plurality of power measure sample elements Pow com (1),..., Pow com (n) to derive an average power signal segment Pow com，av (i). In one design, the quality measure Q

[32] of the average power signal segment Pow com，av (i) serves as a measure of reliability, wherein the reference attenuation signal segment Mod(i) of the frequency band (level) i describes the contribution of the intermediate signal segment SigA res to the heartbeat period H_Zr(x), H_Zr(y) or the reference heartbeat period H_Zr ref . com com (x), SigA com (y).

[0193] Q

[33] : Does the intermediate signal segment SigA com (x) of a heartbeat x meet a given expectation for an intermediate signal segment? The intermediate signal segment SigA kar，ref (x) is generated from a cardiac signal segment SigA kar (x). Thus, one design is as follows: For each heartbeat, a cardiac reference signal segment SigA karkar，ref or a cardiac signal segment SigA kar (x) adapted to the heartbeat x, does the adapted cardiac signal segment SigA kar (x) match a pre-given expectation for a cardiac signal segment? In particular: Does the adapted cardiac signal segment SigA Sum (x) have a time course from Q to T as shown in Figure 1 ?

[0194] In Figure 7 and Figure 12 three additional functional blocks for calculating these quality measures Q

[30] , Q

[31] , Q

[32] , Q

[33] are shown:

[0195] - The functional block 130 evaluates the quality of the cardiac signal Sig Sum that has been generated. The functional block 130 provides a quality measure Q

[30] which for each heartbeat x comprises a value

[0196] - The functional block 131 provides a quality measure Q

[31] which for each heartbeat x comprises a value

[0197] Function block 132 provides quality measures Q

[32] and Q

[33] . In one embodiment, the respective quality measure Q

[32] comprises a single value for each heartbeat x, in another embodiment, a time profile of the value.

[0198] - Corresponding content applies to the quality measure Q

[33] .

[0199] Figure 13 By way of example, a plurality of functional units of the measurement value processor 19 and a functional block 130 are shown, which evaluates the quality

[30] with which the measurement value processor 19 obtains the original signal Sig raw Generated and signal Sig Sum .

[0200] The cardiac activity of the patient P may act on at least two different sum signals, in particular on sum signals of different sensors. In one embodiment, different heartbeat moments are detected. However, the heartbeat moments all come from the same heart and are therefore different estimates of the same event. In one embodiment, the heartbeat moments H_Zp(x), H_Zp(y) are selected from the signal. In one embodiment, a function block 131 evaluates to what extent the estimates of the heartbeat moments H_Zp(x), H_Zp(y) differ from one another and calculates a quality measure Q based on the differences

[31] .

[0201] Figure 15 The functional block 132 is shown in detail. As already explained, the functional block 132 evaluates the cardiogenic reference signal segment SigA determined for the heartbeat x. kar，ref or the adapted cardiac signaling fragment SigA kar (x) Does it match the pre-given expectations for the cardiac signal segment? Function block 132 provides a quality measure Q

[33] . Furthermore, function block 132 calculates the quality measure Q

[32] .

[0202] exist Figure 15 The following functional units are shown:

[0203] - As already mentioned, the functional unit 12 generates the sum signal Sig Sum The corresponding heartbeat period H_Zr(x) of each heartbeat x is identified, preferably the QRS phase.

[0204] - The functional unit 13 determines the respective characteristic heartbeat time H_Zp(x) for each heartbeat x.

[0205] - As already mentioned, the functional unit 14 will calculate for the last N heartbeats x1, ..., x N N times correctly positioned and signal fragment SigA Sum(x1),..., SigA Sum (x N ) superimposed.

[0206] - The functional unit 15 generates the cardiogenic reference signal segment SigA Sum (x1),..., SigA Sum (x N ) from the superimposition of the N sum signal segments SigA kar，ref .

[0207] - The optional functional unit 56 calculates a shape change factor for the cardiogenic reference signal segment SigA kar，ref from anthropometric parameter values of the patient P during the heartbeat x and generates therefrom an adapted cardiogenic signal segment SigA kar (x) for the heartbeat x. Anthropometric parameters are for example the current lung filling level or the current position of the patient P. An exemplary mode of operation of this functional unit is described in DE 10 2019 006 866 A1 and US 2022 / 0330837 A1.

[0208] - The functional unit 11 subtracts the cardiogenic reference signal segment SigA Sum or the adapted cardiogenic signal segment SigA kar，ref (x) from the sum signal Sig kar .

[0209] - The optional attenuation functional block 21 attenuates the cardiogenic reference signal segment SigA kar，ref or the adapted cardiogenic signal segment SigA kar (x) in order to remove the remaining components of the cardiogenic signal Sig kar .

[0210] - The functional unit 57 performs a residual power analysis and for this exchanges signals with the attenuation functional block 21. In such a residual power analysis, the signal strength of the attenuated signal segment Mod(i) is checked and optionally an attenuation is performed. Exemplary reference is made to Figure 7 to Figure 11 Attenuation has already been described.

[0211] The functional units 12, 13, 16 and 21 perform the respective calculation steps with a high sampling frequency of a few milliseconds, so that the respective results are already present during the respective heartbeats. The functional units 14, 15 and 57 perform the calculation steps with a lower material frequency, for example the above-mentioned low sampling frequency, and process the N sum signal segments SigA Sum (x1),..., SigA Sum (x N ) of N completed heartbeats.

[0212] As already further mentioned above, the average power signal segments Pow com，av (i) are calculated Figure 12 The average power signal segments Pow com，av (i) describe a time-varying process of the electrical power for the i-th level number, wherein the time-varying process encompasses a single relative heartbeat period T. The average power signal segments Pow com，av (i) are calculated as a weighted average over M signal component segments SigA com (i) of M heartbeats. The functional block 101 time-correctly positions the M signal component segments SigA ref to each other. The functional unit 24 generates the average power signal segments Pow com (i) from the time-correctly positioned M signal component segments SigA com (i) and generates therefrom the reference attenuation signal segments Mod(i), just as this has been further described above. com，av

[0213] Figure 7 and Figure 12 The functional unit 24 uses for these tasks at least one of the four quality measures Q

[30] to Q

[34] , respectively:

[0214] - in the initialization phase, for the task of calculating the weighting factors by means of which the respective average power signal segments Pow com，av (i) are calculated for each i-th level number,

[0215] - also in the initialization phase, for the task of generating the reference attenuation signal segments Mod(i),

[0216] - in the usage phase, for the optional task of updating the reference attenuation signal segments Mod(i), and

[0217] - in the usage phase, for the task of calculating an adapted attenuation signal segment Mod(i)(x) for a heartbeat in the case of using the reference attenuation signal segments Mod(i).

[0218] For each of these tasks, the functional unit 24 calculates a total quality measure Q, respectively, and uses at least one quality measure Q

[30] to Q

[34] , preferably a plurality of quality measures, for this calculation. The rule is that the worse the total quality measure Q, the lower the above-mentioned and used weighting factors are. Furthermore, the adapted attenuation signal segment Mod(i)(x) is smaller than or at most exactly as large as the reference attenuation signal segment Mod(i), and the worse the total quality measure Q, the smaller it is.

[0219] ​In the usage phase, the signal processing unit 5 uses the previously determined reference attenuation signal segment Mod(i) for the heartbeat and for the i-th level of hierarchy in order to generate an adapted attenuation signal segment Mod(i)(x). The effect of this attenuation is as follows: In the usage phase, if and as long as a poor total quality measure Q has been determined, the attenuation is enhanced. Thus, signal segments of the signal Sig com with poor quality Q are more strongly attenuated than other signal segments.

[0220] In particular, the following implementation forms are possible: How in the usage phase the adapted attenuation signal segment Mod(i)(x) is changed depending on the total quality measure Q:

[0221] - each value of the adapted attenuation signal segment Mod(i)(x) is multiplied by a factor a < 1, wherein this factor a < 1 is derived from the quality measures Q

[30] , Q

[31] , Q

[32] , Q

[33] and the poorer the total quality measure Q, the smaller the factor.

[0222] - only those values of the adapted attenuation signal segment Mod(i)(x) which are smaller or equal to a pre-given upper limit β are multiplied by a factor a < 1, wherein it applies that 0 < β < 1.

[0223] - each value of the adapted attenuation signal segment Mod(i)(x) is reduced by a fixed value Δ >= 0, wherein the poorer the total quality measure Q, the larger the fixed value Δ. However, the values of the adapted attenuation signal segment Mod(i)(x) are at most reduced to 0, so that no negative values occur.

[0224] - only those values of the adapted attenuation signal segment Mod(i)(x) which are smaller or equal to the above-mentioned upper limit β are reduced by a fixed value Δ.

[0225] - each value of the adapted attenuation signal segment Mod(i)(x) is multiplied by a factor a or reduced by a fixed value Δ depending on which action leads to the smaller result. Again, values smaller than zero are avoided.

[0226] Additionally or instead of the implementation forms just mentioned, the adapted attenuation signal segment Mod(i)(x) is smoothed computationally, in particular by applying moving average filtering.

[0227] The factor α and / or the just mentioned fixed value Δ can be the same for each hierarchy i, i.e. for each frequency band. It is also possible that, in the use phase, up to three separate quality measures Q

[30] (i), Q

[31] (i), Q

[32] (i) are determined for each hierarchy i (i = 1,..., n) and from them a total quality measure Q = Q(i) is derived for itself. Correspondingly, a factor α(i) and / or a fixed value Δ(i) for itself is derived for each hierarchy i and used as just described.

[0228] Figure 16 The improvement achieved by the present application is illustrated. In the left column, the time course of the average power signal segment Pow com，av (6) is shown, in the right column the time course of the resulting reference attenuation signal segment Mod(6) is shown. The upper row illustrates the result without using the method of the present application, the lower row illustrates the result according to the method of the present application. In each diagram, the time course in the case of no interference and the course in the case of an interference are shown separately. In detail

[0229] Pow com，av (6) dist denotes the average power signal segment in the case of an interference, realized according to the prior art,

[0230] Pow com，av (6) inv denotes the average power signal segment in the case of an interference, realized according to the present application,

[0231] Pow com，av (6) ref denotes the average power signal segment in the case of no interference,

[0232] Mod(6) dist denotes the reference attenuation signal segment in the case of an interference, realized according to the prior art,

[0233] Mod(6) inv denotes the reference attenuation signal segment in the case of an interference, realized according to the present application,

[0234] Mod(6) ref denotes the reference attenuation signal segment in the case of no interference.

[0235] Figure 17 The reference attenuation signal segment Mod(6) and the adapted attenuation signal segment Mod(6)(x) for the heart beat x are illustrated exemplarily. The time t is plotted on the x-axis, the signal value between 0 and 1 on the y-axis.

[0236] List of reference signs

[0237]

[0238]

[0239]

[0240]

[0241]

[0242]

[0243]

Claims

1. A signal processing unit (5) for determining an estimate (Sig res,est ) of a respiratory signal (Sig res ). wherein the respiratory signal (Sig res ) is related to ventilation of the lungs of a patient (P) and the ventilation of the lungs is caused by spontaneous breathing activity and / or artificial respiration of the patient (P), wherein a pre-given reference heartbeat period (H_Zr ref ) and a usage phase, wherein the signal processing unit (5) is designed to automatically receive measurement values from at least one and-signal sensor (2.1.1 to 2.2.2), wherein the or each used and-signal sensor (2.1.1 to 2.2.2) is designed to measure a signal generated in and / or at the body of the patient (P), generating and signal (Sig Sum ), wherein the sum signal (Sig Sum ) comprises - a respiratory signal (Sig res ) to be estimated, and - superimposition of a cardiological signal (Sig kar ) related to the heart activity of said patient (P), In the case of using the sum signal (Sig Sum ) - detecting a plurality of heartbeats and - for each detected heartbeat, respectively detecting a characteristic heartbeat period [H_Zr(x), H_Zr(y)] in which the heartbeat occurs, computing an intermediate signal (Sig com ), and at least approximately computationally compensating for an influence of the heart activity on the sum signal (Sig Sum ) for computing the intermediate signal (Sig com ), in a first alternative, calculating at least one reference attenuation signal segment [Mod(1),..., Mod(n)], and in a second alternative, determining the or each reference attenuation signal segment [Mod(1),..., Mod(n)] by a read access to a data memory (9), wherein the or each reference attenuation signal segment [Mod(l),...,Mod(n)] is related to an average time course of contributions of the reference cardiac signal (Sig kar ) to the intermediate signal (Sig ref ) in the reference heartbeat period (H_Zr com ), for each detected heartbeat falling into the use phase, - generating an intermediate signal segment [SigA com (x)] as a segment of the intermediate signal (Sig com ), respectively, wherein said intermediate signal segment [SigA com (x)] is located within a heartbeat period [H_Zr(x), H_Zr(y)] of the heartbeat, and - generating an attenuated intermediate signal segment [SigA com (x)] from the intermediate signal segment [SigA com,d (x)] for the heartbeat period [H_Zr(x), H_Zr(y)] of the heartbeat, wherein the influence of the cardiogenic signal (Sig kar ) on the attenuated intermediate signal segment [SigA com,d (x)] is less than or at most exactly as large as the influence of the cardiogenic signal (Sig kar ) on the intermediate signal segment [SigA com (x)], and combining the attenuated intermediate signal segments [SigA com,d (x)] into an estimate (Sig res ) for the respiratory signal (Sig res,est ) using the detected characteristic heartbeat period [H_Zr(x), H_Zr(y)], wherein the signal processing unit (5) is furthermore designed to, for each detected heartbeat - in the case of the first alternative, the reference attenuation signal segment [Mod(1),..., Mod(n)] and - applying the adapted decay signal segments [Mod(1)(x),..., Mod(n)(x)] to the intermediate signal segments [SigA com (x)] in case of the second alternative and generating an attenuated intermediate signal segment [SigA com,d (x)] for this heartbeat by applying, wherein the signal processing unit (5) is furthermore designed to calculate at least one of the following quality measures (Q[30], Q[31], Q[32], Q[33]): - a quality measure (Q[30]) of the reliability of the sum signal (Sig Sum ) produced by the signal processing unit (5) from the measurement values of the or each sum signal sensor (2.1.1 to 2.2.2) used, - for at least one heartbeat, preferably for multiple heartbeats, respectively for the heartbeats (x1, . . . , x N )’s corresponding characteristic heartbeat moments [H_Zp(x1), ..., H_Zp(x N )] is a quality measure of reliability (Q[31]), - as reference attenuated signal segments [Mod(1), ..., Mod(n)] to computationally compensate the cardiogenic signal (Sig kar ) in the heartbeat period or in the reference heartbeat period (H_Zr ref ) in the intermediate signal (Sig com ) is a measure of the reliability of the contribution of the quality metric (Q[32]), and - a quality measure (Q[33]) of the shape of the intermediate signal segment [SigA com (x)] for the heartbeat, and wherein the signal processing unit (5) is furthermore designed to in the case of the first alternative, calculating the or each reference attenuation signal segment [Mod(1),..., Mod(n)] using at least one quality measure (Q[30],..., Q[33]), and In case of the second alternative, for each heartbeat detected in the use phase, for the attenuated intermediate signal segment [SigA com,d (x)] in use - the determined reference attenuation signal segment [Mod(1),..., Mod(n)] and - at least one quality measure (Q[30],..., Q[33]) calculating an adapted attenuation signal segment [Mod(1)(x),..., Mod(n)(x)] such that - the adapted attenuation signal segment [Mod(1)(x),..., Mod(n)(x)] is smaller or at most exactly as large as the reference attenuation signal segment [Mod(1),..., Mod(n)], and - the smaller the used quality measure (Q[30],..., Q[33]) is, the smaller.

2. The signal processing unit (5) according to claim 1, characterized in that the signal processing unit (5) is designed to - generate a sample having a plurality of sample elements such that Each sample element relates to a heartbeat, respectively, and comprises an intermediate signal segment [SigA com (x)] as a segment of the intermediate signal (Sig com ), wherein the segment is located in a heartbeat period [H_Zr(x)] of the heartbeat, respectively, and - for each sample element, respectively generate a power measure sample element, which is a measure of the temporal course of the electrical power in the heartbeat period [H_Zr(x)] of the heartbeat, wherein the signal processing unit (5) is designed to, when calculating the reference attenuation signal segment [Mod(1),..., Mod(n)] or the reference attenuation signal segment [Mod(1),..., Mod(n)], generating an average power signal segment [Pow com,av (i)] as an average over the power measure sample elements, and In case the average power signal segment [Pow com,av (i)] is used, the reference attenuation signal segments [Mod(1),..., Mod(n)] are calculated, In particular, the average power signal segment [Pow com，av (i)] as the reference attenuated signal segments [Mod(1), ..., Mod(n)], and causing to store the reference attenuation signal segments [Mod(1),...,Mod(n)] in the data memory (9).

3. The signal processing unit (5) according to claim 2, characterized in that The signal processing unit (5) is furthermore set up for calculating, in the case of the first alternative, the average value over the power measure sample elements [Pow com (1),..., Pow com (n)] as a weighted average value, wherein the signal processing unit (5) is furthermore set up for For each power metric sample element [Pow com (1), ..., Pow com (n)] are used to calculate the average power signal segment Pow using the power quality metric (Q[32]) com,av The weighting factor of (i) is such that The smaller the power quality measure (Q[32]) is, the smaller the weighting factor is.

4. The signal processing unit (5) according to claim 3, characterized in that The quality measure (Q[32]) used for calculating the weighting factors is the reference attenuated signal segments [Mod(1), ..., Mod(n)] that are computationally compensated for the cardiogenic signal (Sig kar ) in the reference heartbeat period (H_Zr ref ) in the intermediate signal (Sig com )'s contribution, wherein the measure is in particular a quality measure of the shape of the average power signal segment [Pow com (i)] or of the power measure sample elements.

5. The signal processing unit (5) according to any one of the preceding claims, characterized in that a plurality of frequency bands is predefined, and the signal processing unit (5) is designed for for each predefined frequency band, respectively, calculating or determining by read access to the data memory (9) a reference attenuation signal segment component [Mod(1),...,Mod(n)], wherein the signal processing unit (5) is designed for, for each predefined frequency band and for each detected heartbeat falling into the use phase, - calculating for this heartbeat or for this frequency band, respectively, at least one adapted attenuation signal segment [Mod(1)(x),...,Mod(n)(x)] using the or at least one quality measure (Q[30],...,Q[33]) and the reference attenuation signal segment component [Mod(1),...,Mod(n)] predefined or calculated for this frequency band, The adapted attenuated signal segment components [Mod(1)(x), ..., Mod(n)(x)] and the cardiogenic signal (Sig kar ) in the heartbeat period (H_Zr(x)) of the intermediate signal (Sig com ) is related to the average time variation of the contribution of - generating an intermediate signal segment [SigA com (x)] of a component [SigA com (1)(x),..., SigA com (n)(x)] of a heartbeat period [H_Zr(x)] for the detected heartbeat occurring in the frequency band, respectively, - components [SigA com (1)(x),...,SigA com (n)(x)] of the intermediate signal segment [SigA com (x)] occurring in the frequency band in the case of use of adapted attenuation signal segment components [Mod(1)(x),...,Mod(n)(x)] for the frequency band generating an attenuated intermediate signal segment [SigA com,d (x)] for the heartbeat period [H_Zr(x)] that has components [SigA com,d (1)(x),..., SigA com,d (n)(x)] occurring in the frequency band.

6. An apparatus comprising - at least one and signal sensor (2.1.1 to 2.2.2) and - a signal processing unit (5) according to any one of the preceding claims, wherein the or each and signal sensor (2.1.1 to 2.2.2) used is designed for measuring a signal generated in or at the body of a patient (P), and wherein the signal processing unit (5) is designed for - receiving measurement values from the or each and signal sensor (2.1.1 to 2.2.2), and - generating the or each sum signal (Sig Sum ) using the received measurement values.

7. A method for determining an estimate (Sig res ) for a respiratory signal (Sig res,est ), wherein the respiratory signal (Sig res ) is related to ventilation of the lungs of a patient (P) and the ventilation of the lungs is caused by spontaneous breathing activity and / or artificial respiration of the patient (P), wherein a reference heartbeat period (H_Zr ref ) and a usage phase are pre-given for the method, wherein the method is performed automatically using a signal processing unit (5), and comprising the steps of: the signal processing unit (5) receives measurement values from at least one and signal sensor (2.1.1 to 2.2.2), wherein the or each and signal sensor (2.1.1 to 2.2.2) used measures a signal generated in and / or at the body of a patient (P), generating and signal (Sig Sum ), wherein the sum signal (Sig Sum ) comprises - a respiratory signal (Sig res ) to be estimated, and - superimposition of a cardiological signal (Sig kar ) related to the heart activity of said patient (P), In the case of using the sum signal (Sig Sum ) - detects a plurality of heartbeats and - for each detected heartbeat, respectively, detects a characteristic heartbeat period [H_Zr(x)], in which the heartbeat occurs, computing an intermediate signal (Sig com ), and at least approximately computationally compensating for an influence of the heart activity on the sum signal (Sig Sum ) for computing the intermediate signal (Sig com ), in a first alternative, at least one reference attenuation signal segment [Mod(1),...,Mod(n)] is calculated, and in a second alternative, the or each reference attenuation signal segment [Mod(1),...,Mod(n)] is determined by read access to a data memory (9), wherein the or each reference attenuation signal segment [Mod(l),...,Mod(n)] is related to an average time course of contributions of the cardiogenic signal (Sig kar ) to the intermediate signal (Sig ref ) in the reference heartbeat period (H_Zr com ), for each detected heartbeat [H_Zr(x),H_Zr(y)] falling into the use phase, - generating an intermediate signal segment [SigA com (x)] as a segment of the intermediate signal (Sig com ), respectively, wherein said intermediate signal segment [SigA com (x)] is located within a heartbeat period [H_Zr(x), H_Zr(y)] of the heartbeat, and - generating an attenuated intermediate signal segment [SigA com (x)] from the intermediate signal segment [SigA com,d (x)] for the heartbeat period [H_Zr(x), H_Zr(y)], wherein the influence of the cardiogenic signal (Sig kar ) on the attenuated intermediate signal segment [SigA com,d (x)] is less than or at most exactly as large as the influence of the cardiogenic signal (Sig kar ) on the intermediate signal segment [SigA com (x)], and combining the attenuated intermediate signal segments [SigA com,d (x)] into an estimate (Sig res ) for the respiration signal (Sig res,est ) using the detected characteristic heartbeat period [H_Zr(x), H_Zr(y)], wherein the signal processing unit (5) for each detected heartbeat - In the case of a first alternative, the reference attenuated signal segments [Mod(1), ..., Mod(n)] and In the case of the second alternative, the adapted attenuated signal segments [Mod(1)(x), ..., Mod(n)(x)] is applied to the corresponding intermediate signal segment [SigA com (x)], and by applying a decayed intermediate signal segment [SigA com,d (x)] for this heartbeat is generated, The method further comprises the step of: the signal processing unit (5) calculating at least one of the following quality measures (Q[30], Q[31], Q[32], Q[33]): - a quality measure (Q[30]) of the reliability of the or each sum signal (Sig Sum ) produced by the signal processing unit (5) from the measurement values of the or each sum signal sensor (2.1.1 to 2.2.2) used, - for at least one heartbeat, preferably for a plurality of heartbeats, a quality measure (Q[31]) for the reliability of the respective characteristic heartbeat moment [H_Zp(x1),..., H_Zp(x N )] that has been detected for the heartbeat (x1,..., x N ) respectively, - a quality measure (Q[32]) for the reliability of the contribution of the reference attenuation signal segments [Mod(1),...,Mod(n)] to the calculation of the cardiogenic signal (Sig kar ) in the reference heartbeat period (H_Zr ref ) to the intermediate signal (Sig com ) and - a quality measure (Q[33]) on the shape of the intermediate signal segment [SigA com (x)] for the heartbeat, and In the case of a first alternative, the or each reference attenuated signal segment [Mod(1), ..., Mod(n)] is calculated using at least one quality measure (Q[30], ..., Q[33]), and In case of the second alternative, for each heartbeat detected in the use phase, for the attenuated intermediate signal segment [SigA com,d (x)] in use - the determined reference attenuated signal segments [Mod(1), ..., Mod(n)] and - In the case of at least one quality measure (Q[30], ..., Q[33]) Calculate the adapted attenuated signal segment [Mod(1)(x), ..., Mod(n)(x)] so that the adapted attenuated signal segment [Mod(1)(x), ..., Mod(n)(x)] - is smaller than or at most exactly as large as said reference attenuation signal segments [Mod(1), ..., Mod(n)], and - The smaller the quality measure used (Q[30], ..., Q[33]), the smaller it is.

8. The method according to claim 7, characterized in that The method comprises the additional step of: the signal processing unit (5) - generates a sample with multiple sample elements, such that each sample element relates to a heartbeat, respectively, and comprises an intermediate signal segment [SigA com (x)] as a segment of the intermediate signal (Sig com ), Wherein the segment is located in the heartbeat period [H_Zr(x)] of the heartbeat, and - generating a power measure sample element for each sample element, respectively, which is the time course of the measure of the electrical power within the heartbeat period [H_Zr(x)] of that heartbeat, and The step of calculating the reference attenuation signal segment [Mod(1), ..., Mod(n)] or the reference attenuation signal segment [Mod(1), ..., Mod(n)] by the signal processing unit (5) comprises the following steps: - generating an average power signal segment [Pow com,av (i)] as an average over the power measure sample elements [Pow com,av (1),..., Pow com,av (n)], - in case of using the average power signal segments Pow com,av (i) to calculate the reference attenuation signal segments [Mod(1),..., Mod(n)], In particular, the average power signal segment Pow com,av (i) as the reference attenuation signal segments [Mod(l),...,Mod(n)], - causing said reference attenuated signal segments [Mod(1), ..., Mod(n)] to be stored in said data memory (9).

9. The method according to claim 8, characterized in that In the case of the first alternative the average value over the power measure sample elements is a weighted average value, wherein a weighting factor for calculating the average power signal segment [Pow com,av (i)] is calculated in case at least one quality measure (Q[32]) is used, such that The smaller the quality measure (Q[32]), the smaller the weighting factor.

10. The method according to claim 9, characterized in that The quality measure (Q[32]) or the quality measure (Q[32]) used for calculating the weighting factor is a reference attenuated signal segment [Mod(1), ..., Mod(n)] that is computationally compensated for the cardiogenic signal (Sig kar ) in the reference heartbeat period (H_Zr ref ) in the intermediate signal (Sig com )'s contribution, wherein in particular said measure is a quality measure of the shape of said average power signal segment [Pow com,av (i)].

11. The method according to any one of claims 7 to 10, characterized in that Predetermining multiple frequency bands, The method comprises the following additional steps: the signal processing unit (5) performs a - in the case of a first alternative, respectively calculating the components [Mod(1), ..., Mod(n)] of said reference attenuated signal segments, and - in the case of the second alternative, the components [Mod(l),...,Mod(n)] are determined by a read access to the data memory (9), wherein the components relate to frequency bands, and The method furthermore comprises the following additional steps: the signal processing unit (5) determines for each pre-specified frequency band and for each detected heartbeat falling into the use phase, - generating, respectively, components [SigA com (x),..., SigA com (n)(x)] of the intermediate signal segment [SigA com (x)] of the heartbeat period [H_Zr(x)] against the detected heartbeat, which occur in the frequency band, and - the components [SigA com (1)(x),..., SigA com (n)(x)] in the frequency band that occur from the intermediate signal segment [SigA com,d (x)] in the frequency band that occur from the attenuated intermediate signal segment [SigA com,d (1)(x),..., SigA com,d (n)(x)] of the heartbeat period [H_Zr(x)], wherein the signal processing unit (5) consists for each detected heart beat falling into a usage phase of a component [SigA com,d (1)(x),..., SigA com,d (n)(x)] for the heart beat period [H_Zr(x), H_Zr(y)] of an attenuated intermediate signal segment [SigA com,d (x)], wherein the signal processing unit (5) for each pre-specified frequency band In order to generate the attenuated intermediate signal segments [SigA com,d (x)] of the components [SigA com，d (1)(x),...,SigA com,d (n)(x)] occurring in this frequency band - in the case of the first alternative, the components [Mod(l),...,Mod(n)] of the reference attenuation signal segment for this frequency band, and - in the case of the second alternative, the components [Mod(l)(x),...,Mod(n)(x)] of the adapted attenuation signal segment for this frequency band applying a component [SigA com (x)] to the intermediate signal segment [SigA com (1)(x),...,SigA com (n)(x)] and wherein the signal processing unit (5) for each pre-specified frequency band In the case of the first alternative, for each pre-specified frequency band, the respective component [Mod(l),...,Mod(n)] for this frequency band of the reference attenuation signal segment is calculated using at least one quality measure (Q[30],...,Q[33]), and In the case of the second alternative for each heartbeat detected in the use phase calculating the attenuated mid signal segment [SigA com,d (x)] in the frequency band from the reference attenuation signal segment and the at least one quality measure (Q[30],..., Q[33]) or the component [Mod(1),..., Mod(n)] of the at least one quality measure (Q[30],..., Q[33]) determined for the frequency band com,d calculating the attenuated mid signal segment [SigA com,d (1)(x),..., SigA (n)(x)] in the frequency band from the reference attenuation signal segment and the at least one quality measure (Q[30],..., Q[33]) or the component [Mod(1),..., Mod(n)] of the at least one quality measure (Q[30],..., Q[33]) determined for the frequency band such that the components [SigA com,d (x)] of the attenuated intermediate signal segment [SigA com,d (1)(x),...,SigA com,d (n)(x)] - is smaller or at most as large as the reference attenuation signal segment [Mod(l),...,Mod(n)] for the frequency band, and - the smaller the quality measure (Q[30],...,Q[33]) used is, the smaller it is.

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